diff --git "a/assets/index-CHouKU67.js" "b/assets/index-CHouKU67.js"
new file mode 100644--- /dev/null
+++ "b/assets/index-CHouKU67.js"
@@ -0,0 +1,1838 @@
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+*
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+* @license React
+* react-dom.production.js
+*
+* Copyright (c) Meta Platforms, Inc. and affiliates.
+*
+* This source code is licensed under the MIT license found in the
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+*
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uh={bundleType:0,version:"19.1.0",rendererPackageName:"react-dom",currentDispatcherRef:F,reconcilerVersion:"19.1.0"};if(typeof __REACT_DEVTOOLS_GLOBAL_HOOK__<"u"){var Ki=__REACT_DEVTOOLS_GLOBAL_HOOK__;if(!Ki.isDisabled&&Ki.supportsFiber)try{In=Ki.inject(uh),Mt=Ki}catch{}}return reactDomClient_production.createRoot=function(t,r){if(!p(t))throw Error(l(299));var i=!1,h="",w=Ec,T=Sc,I=Oc,L=null;return r!=null&&(r.unstable_strictMode===!0&&(i=!0),r.identifierPrefix!==void 0&&(h=r.identifierPrefix),r.onUncaughtError!==void 0&&(w=r.onUncaughtError),r.onCaughtError!==void 0&&(T=r.onCaughtError),r.onRecoverableError!==void 0&&(I=r.onRecoverableError),r.unstable_transitionCallbacks!==void 0&&(L=r.unstable_transitionCallbacks)),r=Zd(t,1,!1,null,null,i,h,w,T,I,L,null),t[wn]=r.current,Sl(t),new Vl(r)},reactDomClient_production.hydrateRoot=function(t,r,i){if(!p(t))throw Error(l(299));var h=!1,w="",T=Ec,I=Sc,L=Oc,V=null,ae=null;return i!=null&&(i.unstable_strictMode===!0&&(h=!0),i.identifierPrefix!==void 0&&(w=i.identifierPrefix),i.onUncaughtError!==void 0&&(T=i.onUncaughtError),i.onCaughtError!==void 0&&(I=i.onCaughtError),i.onRecoverableError!==void 0&&(L=i.onRecoverableError),i.unstable_transitionCallbacks!==void 0&&(V=i.unstable_transitionCallbacks),i.formState!==void 0&&(ae=i.formState)),r=Zd(t,1,!0,r,i??null,h,w,T,I,L,V,ae),r.context=ef(null),i=r.current,h=gn(),h=Qn(h),w=Pr(h),w.callback=null,Ar(i,w,h),i=h,r.current.lanes=i,un(r,i),Xn(r),t[wn]=r.current,Sl(t),new Yi(r)},reactDomClient_production.version="19.1.0",reactDomClient_production}var hasRequiredClient;function requireClient(){if(hasRequiredClient)return client.exports;hasRequiredClient=1;function v(){if(!(typeof __REACT_DEVTOOLS_GLOBAL_HOOK__>"u"||typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.checkDCE!="function"))try{__REACT_DEVTOOLS_GLOBAL_HOOK__.checkDCE(v)}catch(o){console.error(o)}}return v(),client.exports=requireReactDomClient_production(),client.exports}var clientExports=requireClient();function dispatchCallback(v,o){v&&v(o)}function reverseDictionary(v){return Object.fromEntries(Object.entries(v).map(([o,d])=>[d,o]))}const Callable=class{constructor(){let v=function(...o){return v._call(...o)};return Object.setPrototypeOf(v,new.target.prototype)}_call(...v){throw Error("Must implement _call method in subclass")}};function isTypedArray(v){var o,d,l;return((l=(d=(o=v==null?void 0:v.prototype)==null?void 0:o.__proto__)==null?void 0:d.constructor)==null?void 0:l.name)==="TypedArray"}function isIntegralNumber(v){return Number.isInteger(v)||typeof v=="bigint"}function exists(v){return v!=null}function calculateDimensions(v){const o=[];let d=v;for(;Array.isArray(d);)o.push(d.length),d=d[0];return o}function mergeArrays(...v){return Array.prototype.concat.apply([],v)}function calculateReflectOffset(v,o){return Math.abs((v+o)%(2*o)-o)}const sharp={},ONNX_NODE=Object.freeze(Object.defineProperty({__proto__:null,default:sharp},Symbol.toStringTag,{value:"Module"}));var ortWeb_min$1={exports:{}};const backends={},backendsSortedByPriority=[],registerBackend=(v,o,d)=>{if(o&&typeof o.init=="function"&&typeof o.createSessionHandler=="function"){const l=backends[v];if(l===void 0)backends[v]={backend:o,priority:d};else{if(l.priority>d)return;if(l.priority===d&&l.backend!==o)throw new Error(`cannot register backend "${v}" using priority ${d}`)}if(d>=0){const p=backendsSortedByPriority.indexOf(v);p!==-1&&backendsSortedByPriority.splice(p,1);for(let b=0;b<backendsSortedByPriority.length;b++)if(backends[backendsSortedByPriority[b]].priority<=d){backendsSortedByPriority.splice(b,0,v);return}backendsSortedByPriority.push(v)}return}throw new TypeError("not a valid backend")},resolveBackend=async v=>{const o=v.length===0?backendsSortedByPriority:v,d=[];for(const l of o){const p=backends[l];if(p){if(p.initialized)return p.backend;if(p.aborted)continue;const b=!!p.initPromise;try{return b||(p.initPromise=p.backend.init()),await p.initPromise,p.initialized=!0,p.backend}catch(c){b||d.push({name:l,err:c}),p.aborted=!0}finally{delete p.initPromise}}}throw new Error(`no available backend found. ERR: ${d.map(l=>`[${l.name}] ${l.err}`).join(", ")}`)};class EnvImpl{constructor(){this.wasm={},this.webgl={},this.logLevelInternal="warning"}set logLevel(o){if(o!==void 0){if(typeof o!="string"||["verbose","info","warning","error","fatal"].indexOf(o)===-1)throw new Error(`Unsupported logging level: ${o}`);this.logLevelInternal=o}}get logLevel(){return this.logLevelInternal}}const env$2=new EnvImpl,isBigInt64ArrayAvailable=typeof BigInt64Array<"u"&&typeof BigInt64Array.from=="function",isBigUint64ArrayAvailable=typeof BigUint64Array<"u"&&typeof BigUint64Array.from=="function",NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP=new Map([["float32",Float32Array],["uint8",Uint8Array],["int8",Int8Array],["uint16",Uint16Array],["int16",Int16Array],["int32",Int32Array],["bool",Uint8Array],["float64",Float64Array],["uint32",Uint32Array]]),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP=new Map([[Float32Array,"float32"],[Uint8Array,"uint8"],[Int8Array,"int8"],[Uint16Array,"uint16"],[Int16Array,"int16"],[Int32Array,"int32"],[Float64Array,"float64"],[Uint32Array,"uint32"]]);isBigInt64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("int64",BigInt64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigInt64Array,"int64"));isBigUint64ArrayAvailable&&(NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.set("uint64",BigUint64Array),NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.set(BigUint64Array,"uint64"));const calculateSize=v=>{let o=1;for(let d=0;d<v.length;d++){const l=v[d];if(typeof l!="number"||!Number.isSafeInteger(l))throw new TypeError(`dims[${d}] must be an integer, got: ${l}`);if(l<0)throw new RangeError(`dims[${d}] must be a non-negative integer, got: ${l}`);o*=l}return o};let Tensor$2=class po{constructor(o,d,l){let p,b,c;if(typeof o=="string")if(p=o,c=l,o==="string"){if(!Array.isArray(d))throw new TypeError("A string tensor's data must be a string array.");b=d}else{const _=NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.get(o);if(_===void 0)throw new TypeError(`Unsupported tensor type: ${o}.`);if(Array.isArray(d))b=_.from(d);else if(d instanceof _)b=d;else throw new TypeError(`A ${p} tensor's data must be type of ${_}`)}else if(c=d,Array.isArray(o)){if(o.length===0)throw new TypeError("Tensor type cannot be inferred from an empty array.");const _=typeof o[0];if(_==="string")p="string",b=o;else if(_==="boolean")p="bool",b=Uint8Array.from(o);else throw new TypeError(`Invalid element type of data array: ${_}.`)}else{const _=NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.get(o.constructor);if(_===void 0)throw new TypeError(`Unsupported type for tensor data: ${o.constructor}.`);p=_,b=o}if(c===void 0)c=[b.length];else if(!Array.isArray(c))throw new TypeError("A tensor's dims must be a number array");const m=calculateSize(c);if(m!==b.length)throw new Error(`Tensor's size(${m}) does not match data length(${b.length}).`);this.dims=c,this.type=p,this.data=b,this.size=m}static bufferToTensor(o,d){if(o===void 0)throw new Error("Image buffer must be defined");if(d.height===void 0||d.width===void 0)throw new Error("Image height and width must be defined");const{height:l,width:p}=d,b=d.norm;let c,m;b===void 0||b.mean===void 0?c=255:c=b.mean,b===void 0||b.bias===void 0?m=0:m=b.bias;const _=d.bitmapFormat!==void 0?d.bitmapFormat:"RGBA",f=d.tensorFormat!==void 0&&d.tensorFormat!==void 0?d.tensorFormat:"RGB",u=l*p,n=f==="RGBA"?new Float32Array(u*4):new Float32Array(u*3);let e=4,a=0,s=1,g=2,y=3,x=0,E=u,S=u*2,P=-1;_==="RGB"&&(e=3,a=0,s=1,g=2,y=-1),f==="RGBA"?P=u*3:f==="RBG"?(x=0,S=u,E=u*2):f==="BGR"&&(S=0,E=u,x=u*2);for(let O=0;O<u;O++,a+=e,g+=e,s+=e,y+=e)n[x++]=(o[a]+m)/c,n[E++]=(o[s]+m)/c,n[S++]=(o[g]+m)/c,P!==-1&&y!==-1&&(n[P++]=(o[y]+m)/c);return f==="RGBA"?new po("float32",n,[1,4,l,p]):new po("float32",n,[1,3,l,p])}static async fromImage(o,d){const l=typeof HTMLImageElement<"u"&&o instanceof HTMLImageElement,p=typeof ImageData<"u"&&o instanceof ImageData,b=typeof ImageBitmap<"u"&&o instanceof ImageBitmap,c=typeof String<"u"&&(o instanceof String||typeof o=="string");let m,_={};if(l){const f=document.createElement("canvas"),u=f.getContext("2d");if(u!=null){let n=o.naturalHeight,e=o.naturalWidth;if(d!==void 0&&d.resizedHeight!==void 0&&d.resizedWidth!==void 0&&(n=d.resizedHeight,e=d.resizedWidth),d!==void 0){if(_=d,d.tensorFormat!==void 0)throw new Error("Image input config format must be RGBA for HTMLImageElement");if(_.tensorFormat="RGBA",d.height!==void 0&&d.height!==n)throw new Error("Image input config height doesn't match HTMLImageElement height");if(_.height=n,d.width!==void 0&&d.width!==e)throw new Error("Image input config width doesn't match HTMLImageElement width");_.width=e}else _.tensorFormat="RGBA",_.height=n,_.width=e;f.width=e,f.height=n,u.drawImage(o,0,0,e,n),m=u.getImageData(0,0,e,n).data}else throw new Error("Can not access image data")}else if(p){const f="RGBA";let u,n;if(d!==void 0&&d.resizedWidth!==void 0&&d.resizedHeight!==void 0?(u=d.resizedHeight,n=d.resizedWidth):(u=o.height,n=o.width),d!==void 0){if(_=d,d.bitmapFormat!==void 0&&d.bitmapFormat!==f)throw new Error("Image input config format must be RGBA for ImageData");_.bitmapFormat="RGBA"}else _.bitmapFormat="RGBA";if(_.height=u,_.width=n,d!==void 0){const e=document.createElement("canvas");e.width=n,e.height=u;const a=e.getContext("2d");if(a!=null)a.putImageData(o,0,0),m=a.getImageData(0,0,n,u).data;else throw new Error("Can not access image data")}else m=o.data}else if(b){if(d===void 0)throw new Error("Please provide image config with format for Imagebitmap");if(d.bitmapFormat!==void 0)throw new Error("Image input config format must be defined for ImageBitmap");const f=document.createElement("canvas").getContext("2d");if(f!=null){const u=o.height,n=o.width;if(f.drawImage(o,0,0,n,u),m=f.getImageData(0,0,n,u).data,d!==void 0){if(d.height!==void 0&&d.height!==u)throw new Error("Image input config height doesn't match ImageBitmap height");if(_.height=u,d.width!==void 0&&d.width!==n)throw new Error("Image input config width doesn't match ImageBitmap width");_.width=n}else _.height=u,_.width=n;return po.bufferToTensor(m,_)}else throw new Error("Can not access image data")}else{if(c)return new Promise((f,u)=>{const n=document.createElement("canvas"),e=n.getContext("2d");if(!o||!e)return u();const a=new Image;a.crossOrigin="Anonymous",a.src=o,a.onload=()=>{n.width=a.width,n.height=a.height,e.drawImage(a,0,0,n.width,n.height);const s=e.getImageData(0,0,n.width,n.height);if(d!==void 0){if(d.height!==void 0&&d.height!==n.height)throw new Error("Image input config height doesn't match ImageBitmap height");if(_.height=n.height,d.width!==void 0&&d.width!==n.width)throw new Error("Image input config width doesn't match ImageBitmap width");_.width=n.width}else _.height=n.height,_.width=n.width;f(po.bufferToTensor(s.data,_))}});throw new Error("Input data provided is not supported - aborted tensor creation")}if(m!==void 0)return po.bufferToTensor(m,_);throw new Error("Input data provided is not supported - aborted tensor creation")}toImageData(o){var d,l;const p=document.createElement("canvas").getContext("2d");let b;if(p!=null){const c=this.dims[3],m=this.dims[2],_=this.dims[1],f=o!==void 0&&o.format!==void 0?o.format:"RGB",u=o!==void 0&&((d=o.norm)===null||d===void 0?void 0:d.mean)!==void 0?o.norm.mean:255,n=o!==void 0&&((l=o.norm)===null||l===void 0?void 0:l.bias)!==void 0?o.norm.bias:0,e=m*c;if(o!==void 0){if(o.height!==void 0&&o.height!==m)throw new Error("Image output config height doesn't match tensor height");if(o.width!==void 0&&o.width!==c)throw new Error("Image output config width doesn't match tensor width");if(o.format!==void 0&&_===4&&o.format!=="RGBA"||_===3&&o.format!=="RGB"&&o.format!=="BGR")throw new Error("Tensor format doesn't match input tensor dims")}const a=4;let s=0,g=1,y=2,x=3,E=0,S=e,P=e*2,O=-1;f==="RGBA"?(E=0,S=e,P=e*2,O=e*3):f==="RGB"?(E=0,S=e,P=e*2):f==="RBG"&&(E=0,P=e,S=e*2),b=p.createImageData(c,m);for(let k=0;k<m*c;s+=a,g+=a,y+=a,x+=a,k++)b.data[s]=(this.data[E++]-n)*u,b.data[g]=(this.data[S++]-n)*u,b.data[y]=(this.data[P++]-n)*u,b.data[x]=O===-1?255:(this.data[O++]-n)*u}else throw new Error("Can not access image data");return b}reshape(o){return new po(this.type,this.data,o)}};const Tensor$1=Tensor$2;let InferenceSession$2=class df{constructor(o){this.handler=o}async run(o,d,l){const p={};let b={};if(typeof o!="object"||o===null||o instanceof Tensor$1||Array.isArray(o))throw new TypeError("'feeds' must be an object that use input names as keys and OnnxValue as corresponding values.");let c=!0;if(typeof d=="object"){if(d===null)throw new TypeError("Unexpected argument[1]: cannot be null.");if(d instanceof Tensor$1)throw new TypeError("'fetches' cannot be a Tensor");if(Array.isArray(d)){if(d.length===0)throw new TypeError("'fetches' cannot be an empty array.");c=!1;for(const f of d){if(typeof f!="string")throw new TypeError("'fetches' must be a string array or an object.");if(this.outputNames.indexOf(f)===-1)throw new RangeError(`'fetches' contains invalid output name: ${f}.`);p[f]=null}if(typeof l=="object"&&l!==null)b=l;else if(typeof l<"u")throw new TypeError("'options' must be an object.")}else{let f=!1;const u=Object.getOwnPropertyNames(d);for(const n of this.outputNames)if(u.indexOf(n)!==-1){const e=d[n];(e===null||e instanceof Tensor$1)&&(f=!0,c=!1,p[n]=e)}if(f){if(typeof l=="object"&&l!==null)b=l;else if(typeof l<"u")throw new TypeError("'options' must be an object.")}else b=d}}else if(typeof d<"u")throw new TypeError("Unexpected argument[1]: must be 'fetches' or 'options'.");for(const f of this.inputNames)if(typeof o[f]>"u")throw new Error(`input '${f}' is missing in 'feeds'.`);if(c)for(const f of this.outputNames)p[f]=null;const m=await this.handler.run(o,p,b),_={};for(const f in m)Object.hasOwnProperty.call(m,f)&&(_[f]=new Tensor$1(m[f].type,m[f].data,m[f].dims));return _}static async create(o,d,l,p){let b,c={};if(typeof o=="string"){if(b=o,typeof d=="object"&&d!==null)c=d;else if(typeof d<"u")throw new TypeError("'options' must be an object.")}else if(o instanceof Uint8Array){if(b=o,typeof d=="object"&&d!==null)c=d;else if(typeof d<"u")throw new TypeError("'options' must be an object.")}else if(o instanceof ArrayBuffer||typeof SharedArrayBuffer<"u"&&o instanceof SharedArrayBuffer){const f=o;let u=0,n=o.byteLength;if(typeof d=="object"&&d!==null)c=d;else if(typeof d=="number"){if(u=d,!Number.isSafeInteger(u))throw new RangeError("'byteOffset' must be an integer.");if(u<0||u>=f.byteLength)throw new RangeError(`'byteOffset' is out of range [0, ${f.byteLength}).`);if(n=o.byteLength-u,typeof l=="number"){if(n=l,!Number.isSafeInteger(n))throw new RangeError("'byteLength' must be an integer.");if(n<=0||u+n>f.byteLength)throw new RangeError(`'byteLength' is out of range (0, ${f.byteLength-u}].`);if(typeof p=="object"&&p!==null)c=p;else if(typeof p<"u")throw new TypeError("'options' must be an object.")}else if(typeof l<"u")throw new TypeError("'byteLength' must be a number.")}else if(typeof d<"u")throw new TypeError("'options' must be an object.");b=new Uint8Array(f,u,n)}else throw new TypeError("Unexpected argument[0]: must be 'path' or 'buffer'.");const m=(c.executionProviders||[]).map(f=>typeof f=="string"?f:f.name),_=await(await resolveBackend(m)).createSessionHandler(b,c);return new df(_)}startProfiling(){this.handler.startProfiling()}endProfiling(){this.handler.endProfiling()}get inputNames(){return this.handler.inputNames}get outputNames(){return this.handler.outputNames}};const InferenceSession$1=InferenceSession$2,lib=Object.freeze(Object.defineProperty({__proto__:null,InferenceSession:InferenceSession$1,Tensor:Tensor$1,env:env$2,registerBackend},Symbol.toStringTag,{value:"Module"})),require$$0=getAugmentedNamespace(lib);/*!
+* ONNX Runtime Web v1.14.0
+* Copyright (c) Microsoft Corporation. All rights reserved.
+* Licensed under the MIT License.
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A=this.high,$=this.low;return[A>>>24,A>>>16&255,A>>>8&255,255&A,$>>>24,$>>>16&255,$>>>8&255,255&$]},d.fromBytes=function(A,$,W){return W?d.fromBytesLE(A,$):d.fromBytesBE(A,$)},d.fromBytesLE=function(A,$){return new d(A[0]|A[1]<<8|A[2]<<16|A[3]<<24,A[4]|A[5]<<8|A[6]<<16|A[7]<<24,$)},d.fromBytesBE=function(A,$){return new d(A[4]<<24|A[5]<<16|A[6]<<8|A[7],A[0]<<24|A[1]<<16|A[2]<<8|A[3],$)}},1446:(v,o,d)=>{var l,p,b,c=d(2100),m=c.Reader,_=c.Writer,f=c.util,u=c.roots.default||(c.roots.default={});u.onnx=((b={}).Version=(l={},(p=Object.create(l))[l[0]="_START_VERSION"]=0,p[l[1]="IR_VERSION_2017_10_10"]=1,p[l[2]="IR_VERSION_2017_10_30"]=2,p[l[3]="IR_VERSION_2017_11_3"]=3,p[l[4]="IR_VERSION_2019_1_22"]=4,p[l[5]="IR_VERSION"]=5,p),b.AttributeProto=function(){function n(e){if(this.floats=[],this.ints=[],this.strings=[],this.tensors=[],this.graphs=[],e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.name="",n.prototype.refAttrName="",n.prototype.docString="",n.prototype.type=0,n.prototype.f=0,n.prototype.i=f.Long?f.Long.fromBits(0,0,!1):0,n.prototype.s=f.newBuffer([]),n.prototype.t=null,n.prototype.g=null,n.prototype.floats=f.emptyArray,n.prototype.ints=f.emptyArray,n.prototype.strings=f.emptyArray,n.prototype.tensors=f.emptyArray,n.prototype.graphs=f.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.name!=null&&e.hasOwnProperty("name")&&a.uint32(10).string(e.name),e.f!=null&&e.hasOwnProperty("f")&&a.uint32(21).float(e.f),e.i!=null&&e.hasOwnProperty("i")&&a.uint32(24).int64(e.i),e.s!=null&&e.hasOwnProperty("s")&&a.uint32(34).bytes(e.s),e.t!=null&&e.hasOwnProperty("t")&&u.onnx.TensorProto.encode(e.t,a.uint32(42).fork()).ldelim(),e.g!=null&&e.hasOwnProperty("g")&&u.onnx.GraphProto.encode(e.g,a.uint32(50).fork()).ldelim(),e.floats!=null&&e.floats.length){a.uint32(58).fork();for(var 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y=e.uint32();switch(y>>>3){case 1:g.name=e.string();break;case 21:g.refAttrName=e.string();break;case 13:g.docString=e.string();break;case 20:g.type=e.int32();break;case 2:g.f=e.float();break;case 3:g.i=e.int64();break;case 4:g.s=e.bytes();break;case 5:g.t=u.onnx.TensorProto.decode(e,e.uint32());break;case 6:g.g=u.onnx.GraphProto.decode(e,e.uint32());break;case 7:if(g.floats&&g.floats.length||(g.floats=[]),(7&y)==2)for(var x=e.uint32()+e.pos;e.pos<x;)g.floats.push(e.float());else g.floats.push(e.float());break;case 8:if(g.ints&&g.ints.length||(g.ints=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.ints.push(e.int64());else g.ints.push(e.int64());break;case 9:g.strings&&g.strings.length||(g.strings=[]),g.strings.push(e.bytes());break;case 10:g.tensors&&g.tensors.length||(g.tensors=[]),g.tensors.push(u.onnx.TensorProto.decode(e,e.uint32()));break;case 11:g.graphs&&g.graphs.length||(g.graphs=[]),g.graphs.push(u.onnx.GraphProto.decode(e,e.uint32()));break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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")&&!f.isString(e.name))return"name: string expected";if(e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&!f.isString(e.refAttrName))return"refAttrName: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!f.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")&&!(f.isInteger(e.i)||e.i&&f.isInteger(e.i.low)&&f.isInteger(e.i.high)))return"i: integer|Long expected";if(e.s!=null&&e.hasOwnProperty("s")&&!(e.s&&typeof e.s.length=="number"||f.isString(e.s)))return"s: buffer expected";if(e.t!=null&&e.hasOwnProperty("t")&&(s=u.onnx.TensorProto.verify(e.t)))return"t."+s;if(e.g!=null&&e.hasOwnProperty("g")&&(s=u.onnx.GraphProto.verify(e.g)))return"g."+s;if(e.floats!=null&&e.hasOwnProperty("floats")){if(!Array.isArray(e.floats))return"floats: array expected";for(var a=0;a<e.floats.length;++a)if(typeof e.floats[a]!="number")return"floats: number[] expected"}if(e.ints!=null&&e.hasOwnProperty("ints")){if(!Array.isArray(e.ints))return"ints: array expected";for(a=0;a<e.ints.length;++a)if(!(f.isInteger(e.ints[a])||e.ints[a]&&f.isInteger(e.ints[a].low)&&f.isInteger(e.ints[a].high)))return"ints: integer|Long[] expected"}if(e.strings!=null&&e.hasOwnProperty("strings")){if(!Array.isArray(e.strings))return"strings: array expected";for(a=0;a<e.strings.length;++a)if(!(e.strings[a]&&typeof e.strings[a].length=="number"||f.isString(e.strings[a])))return"strings: buffer[] expected"}if(e.tensors!=null&&e.hasOwnProperty("tensors")){if(!Array.isArray(e.tensors))return"tensors: array expected";for(a=0;a<e.tensors.length;++a)if(s=u.onnx.TensorProto.verify(e.tensors[a]))return"tensors."+s}if(e.graphs!=null&&e.hasOwnProperty("graphs")){if(!Array.isArray(e.graphs))return"graphs: array expected";for(a=0;a<e.graphs.length;++a){var s;if(s=u.onnx.GraphProto.verify(e.graphs[a]))return"graphs."+s}}return null},n.fromObject=function(e){if(e instanceof u.onnx.AttributeProto)return e;var a=new u.onnx.AttributeProto;switch(e.name!=null&&(a.name=String(e.name)),e.refAttrName!=null&&(a.refAttrName=String(e.refAttrName)),e.docString!=null&&(a.docString=String(e.docString)),e.type){case"UNDEFINED":case 0:a.type=0;break;case"FLOAT":case 1:a.type=1;break;case"INT":case 2:a.type=2;break;case"STRING":case 3:a.type=3;break;case"TENSOR":case 4:a.type=4;break;case"GRAPH":case 5:a.type=5;break;case"FLOATS":case 6:a.type=6;break;case"INTS":case 7:a.type=7;break;case"STRINGS":case 8:a.type=8;break;case"TENSORS":case 9:a.type=9;break;case"GRAPHS":case 10:a.type=10}if(e.f!=null&&(a.f=Number(e.f)),e.i!=null&&(f.Long?(a.i=f.Long.fromValue(e.i)).unsigned=!1:typeof e.i=="string"?a.i=parseInt(e.i,10):typeof e.i=="number"?a.i=e.i:typeof e.i=="object"&&(a.i=new f.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber())),e.s!=null&&(typeof e.s=="string"?f.base64.decode(e.s,a.s=f.newBuffer(f.base64.length(e.s)),0):e.s.length&&(a.s=e.s)),e.t!=null){if(typeof e.t!="object")throw TypeError(".onnx.AttributeProto.t: object expected");a.t=u.onnx.TensorProto.fromObject(e.t)}if(e.g!=null){if(typeof e.g!="object")throw TypeError(".onnx.AttributeProto.g: object expected");a.g=u.onnx.GraphProto.fromObject(e.g)}if(e.floats){if(!Array.isArray(e.floats))throw TypeError(".onnx.AttributeProto.floats: array expected");a.floats=[];for(var s=0;s<e.floats.length;++s)a.floats[s]=Number(e.floats[s])}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(a.graphs=[],s=0;s<e.graphs.length;++s){if(typeof e.graphs[s]!="object")throw TypeError(".onnx.AttributeProto.graphs: object expected");a.graphs[s]=u.onnx.GraphProto.fromObject(e.graphs[s])}}return a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.floats=[],s.ints=[],s.strings=[],s.tensors=[],s.graphs=[]),a.defaults){if(s.name="",s.f=0,f.Long){var g=new f.Long(0,0,!1);s.i=a.longs===String?g.toString():a.longs===Number?g.toNumber():g}else s.i=a.longs===String?"0":0;a.bytes===String?s.s="":(s.s=[],a.bytes!==Array&&(s.s=f.newBuffer(s.s))),s.t=null,s.g=null,s.docString="",s.type=a.enums===String?"UNDEFINED":0,s.refAttrName=""}if(e.name!=null&&e.hasOwnProperty("name")&&(s.name=e.name),e.f!=null&&e.hasOwnProperty("f")&&(s.f=a.json&&!isFinite(e.f)?String(e.f):e.f),e.i!=null&&e.hasOwnProperty("i")&&(typeof e.i=="number"?s.i=a.longs===String?String(e.i):e.i:s.i=a.longs===String?f.Long.prototype.toString.call(e.i):a.longs===Number?new f.LongBits(e.i.low>>>0,e.i.high>>>0).toNumber():e.i),e.s!=null&&e.hasOwnProperty("s")&&(s.s=a.bytes===String?f.base64.encode(e.s,0,e.s.length):a.bytes===Array?Array.prototype.slice.call(e.s):e.s),e.t!=null&&e.hasOwnProperty("t")&&(s.t=u.onnx.TensorProto.toObject(e.t,a)),e.g!=null&&e.hasOwnProperty("g")&&(s.g=u.onnx.GraphProto.toObject(e.g,a)),e.floats&&e.floats.length){s.floats=[];for(var y=0;y<e.floats.length;++y)s.floats[y]=a.json&&!isFinite(e.floats[y])?String(e.floats[y]):e.floats[y]}if(e.ints&&e.ints.length)for(s.ints=[],y=0;y<e.ints.length;++y)typeof e.ints[y]=="number"?s.ints[y]=a.longs===String?String(e.ints[y]):e.ints[y]:s.ints[y]=a.longs===String?f.Long.prototype.toString.call(e.ints[y]):a.longs===Number?new f.LongBits(e.ints[y].low>>>0,e.ints[y].high>>>0).toNumber():e.ints[y];if(e.strings&&e.strings.length)for(s.strings=[],y=0;y<e.strings.length;++y)s.strings[y]=a.bytes===String?f.base64.encode(e.strings[y],0,e.strings[y].length):a.bytes===Array?Array.prototype.slice.call(e.strings[y]):e.strings[y];if(e.tensors&&e.tensors.length)for(s.tensors=[],y=0;y<e.tensors.length;++y)s.tensors[y]=u.onnx.TensorProto.toObject(e.tensors[y],a);if(e.graphs&&e.graphs.length)for(s.graphs=[],y=0;y<e.graphs.length;++y)s.graphs[y]=u.onnx.GraphProto.toObject(e.graphs[y],a);return e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),e.type!=null&&e.hasOwnProperty("type")&&(s.type=a.enums===String?u.onnx.AttributeProto.AttributeType[e.type]:e.type),e.refAttrName!=null&&e.hasOwnProperty("refAttrName")&&(s.refAttrName=e.refAttrName),s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n.AttributeType=function(){var e={},a=Object.create(e);return a[e[0]="UNDEFINED"]=0,a[e[1]="FLOAT"]=1,a[e[2]="INT"]=2,a[e[3]="STRING"]=3,a[e[4]="TENSOR"]=4,a[e[5]="GRAPH"]=5,a[e[6]="FLOATS"]=6,a[e[7]="INTS"]=7,a[e[8]="STRINGS"]=8,a[e[9]="TENSORS"]=9,a[e[10]="GRAPHS"]=10,a}(),n}(),b.ValueInfoProto=function(){function n(e){if(e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.name="",n.prototype.type=null,n.prototype.docString="",n.create=function(e){return new n(e)},n.encode=function(e,a){return a||(a=_.create()),e.name!=null&&e.hasOwnProperty("name")&&a.uint32(10).string(e.name),e.type!=null&&e.hasOwnProperty("type")&&u.onnx.TypeProto.encode(e.type,a.uint32(18).fork()).ldelim(),e.docString!=null&&e.hasOwnProperty("docString")&&a.uint32(26).string(e.docString),a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.ValueInfoProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.name=e.string();break;case 2:g.type=u.onnx.TypeProto.decode(e,e.uint32());break;case 3:g.docString=e.string();break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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")&&!f.isString(e.name))return"name: string expected";if(e.type!=null&&e.hasOwnProperty("type")){var a=u.onnx.TypeProto.verify(e.type);if(a)return"type."+a}return e.docString!=null&&e.hasOwnProperty("docString")&&!f.isString(e.docString)?"docString: string expected":null},n.fromObject=function(e){if(e instanceof u.onnx.ValueInfoProto)return e;var a=new u.onnx.ValueInfoProto;if(e.name!=null&&(a.name=String(e.name)),e.type!=null){if(typeof e.type!="object")throw TypeError(".onnx.ValueInfoProto.type: object expected");a.type=u.onnx.TypeProto.fromObject(e.type)}return e.docString!=null&&(a.docString=String(e.docString)),a},n.toObject=function(e,a){a||(a={});var s={};return a.defaults&&(s.name="",s.type=null,s.docString=""),e.name!=null&&e.hasOwnProperty("name")&&(s.name=e.name),e.type!=null&&e.hasOwnProperty("type")&&(s.type=u.onnx.TypeProto.toObject(e.type,a)),e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.NodeProto=function(){function n(e){if(this.input=[],this.output=[],this.attribute=[],e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.input=f.emptyArray,n.prototype.output=f.emptyArray,n.prototype.name="",n.prototype.opType="",n.prototype.domain="",n.prototype.attribute=f.emptyArray,n.prototype.docString="",n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.input!=null&&e.input.length)for(var s=0;s<e.input.length;++s)a.uint32(10).string(e.input[s]);if(e.output!=null&&e.output.length)for(s=0;s<e.output.length;++s)a.uint32(18).string(e.output[s]);if(e.name!=null&&e.hasOwnProperty("name")&&a.uint32(26).string(e.name),e.opType!=null&&e.hasOwnProperty("opType")&&a.uint32(34).string(e.opType),e.attribute!=null&&e.attribute.length)for(s=0;s<e.attribute.length;++s)u.onnx.AttributeProto.encode(e.attribute[s],a.uint32(42).fork()).ldelim();return e.docString!=null&&e.hasOwnProperty("docString")&&a.uint32(50).string(e.docString),e.domain!=null&&e.hasOwnProperty("domain")&&a.uint32(58).string(e.domain),a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.NodeProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.input&&g.input.length||(g.input=[]),g.input.push(e.string());break;case 2:g.output&&g.output.length||(g.output=[]),g.output.push(e.string());break;case 3:g.name=e.string();break;case 4:g.opType=e.string();break;case 7:g.domain=e.string();break;case 5:g.attribute&&g.attribute.length||(g.attribute=[]),g.attribute.push(u.onnx.AttributeProto.decode(e,e.uint32()));break;case 6:g.docString=e.string();break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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 a=0;a<e.input.length;++a)if(!f.isString(e.input[a]))return"input: string[] expected"}if(e.output!=null&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(a=0;a<e.output.length;++a)if(!f.isString(e.output[a]))return"output: string[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!f.isString(e.name))return"name: string expected";if(e.opType!=null&&e.hasOwnProperty("opType")&&!f.isString(e.opType))return"opType: string expected";if(e.domain!=null&&e.hasOwnProperty("domain")&&!f.isString(e.domain))return"domain: string expected";if(e.attribute!=null&&e.hasOwnProperty("attribute")){if(!Array.isArray(e.attribute))return"attribute: array expected";for(a=0;a<e.attribute.length;++a){var s=u.onnx.AttributeProto.verify(e.attribute[a]);if(s)return"attribute."+s}}return e.docString!=null&&e.hasOwnProperty("docString")&&!f.isString(e.docString)?"docString: string expected":null},n.fromObject=function(e){if(e instanceof u.onnx.NodeProto)return e;var a=new u.onnx.NodeProto;if(e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.NodeProto.input: array expected");a.input=[];for(var s=0;s<e.input.length;++s)a.input[s]=String(e.input[s])}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.NodeProto.output: array expected");for(a.output=[],s=0;s<e.output.length;++s)a.output[s]=String(e.output[s])}if(e.name!=null&&(a.name=String(e.name)),e.opType!=null&&(a.opType=String(e.opType)),e.domain!=null&&(a.domain=String(e.domain)),e.attribute){if(!Array.isArray(e.attribute))throw TypeError(".onnx.NodeProto.attribute: array expected");for(a.attribute=[],s=0;s<e.attribute.length;++s){if(typeof e.attribute[s]!="object")throw TypeError(".onnx.NodeProto.attribute: object expected");a.attribute[s]=u.onnx.AttributeProto.fromObject(e.attribute[s])}}return e.docString!=null&&(a.docString=String(e.docString)),a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.input=[],s.output=[],s.attribute=[]),a.defaults&&(s.name="",s.opType="",s.docString="",s.domain=""),e.input&&e.input.length){s.input=[];for(var g=0;g<e.input.length;++g)s.input[g]=e.input[g]}if(e.output&&e.output.length)for(s.output=[],g=0;g<e.output.length;++g)s.output[g]=e.output[g];if(e.name!=null&&e.hasOwnProperty("name")&&(s.name=e.name),e.opType!=null&&e.hasOwnProperty("opType")&&(s.opType=e.opType),e.attribute&&e.attribute.length)for(s.attribute=[],g=0;g<e.attribute.length;++g)s.attribute[g]=u.onnx.AttributeProto.toObject(e.attribute[g],a);return e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),e.domain!=null&&e.hasOwnProperty("domain")&&(s.domain=e.domain),s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.ModelProto=function(){function n(e){if(this.opsetImport=[],this.metadataProps=[],e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.irVersion=f.Long?f.Long.fromBits(0,0,!1):0,n.prototype.opsetImport=f.emptyArray,n.prototype.producerName="",n.prototype.producerVersion="",n.prototype.domain="",n.prototype.modelVersion=f.Long?f.Long.fromBits(0,0,!1):0,n.prototype.docString="",n.prototype.graph=null,n.prototype.metadataProps=f.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.irVersion!=null&&e.hasOwnProperty("irVersion")&&a.uint32(8).int64(e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&a.uint32(18).string(e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&a.uint32(26).string(e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&a.uint32(34).string(e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&a.uint32(40).int64(e.modelVersion),e.docString!=null&&e.hasOwnProperty("docString")&&a.uint32(50).string(e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&u.onnx.GraphProto.encode(e.graph,a.uint32(58).fork()).ldelim(),e.opsetImport!=null&&e.opsetImport.length)for(var s=0;s<e.opsetImport.length;++s)u.onnx.OperatorSetIdProto.encode(e.opsetImport[s],a.uint32(66).fork()).ldelim();if(e.metadataProps!=null&&e.metadataProps.length)for(s=0;s<e.metadataProps.length;++s)u.onnx.StringStringEntryProto.encode(e.metadataProps[s],a.uint32(114).fork()).ldelim();return a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.ModelProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.irVersion=e.int64();break;case 8:g.opsetImport&&g.opsetImport.length||(g.opsetImport=[]),g.opsetImport.push(u.onnx.OperatorSetIdProto.decode(e,e.uint32()));break;case 2:g.producerName=e.string();break;case 3:g.producerVersion=e.string();break;case 4:g.domain=e.string();break;case 5:g.modelVersion=e.int64();break;case 6:g.docString=e.string();break;case 7:g.graph=u.onnx.GraphProto.decode(e,e.uint32());break;case 14:g.metadataProps&&g.metadataProps.length||(g.metadataProps=[]),g.metadataProps.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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")&&!(f.isInteger(e.irVersion)||e.irVersion&&f.isInteger(e.irVersion.low)&&f.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 a=0;a<e.opsetImport.length;++a)if(s=u.onnx.OperatorSetIdProto.verify(e.opsetImport[a]))return"opsetImport."+s}if(e.producerName!=null&&e.hasOwnProperty("producerName")&&!f.isString(e.producerName))return"producerName: string expected";if(e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&!f.isString(e.producerVersion))return"producerVersion: string expected";if(e.domain!=null&&e.hasOwnProperty("domain")&&!f.isString(e.domain))return"domain: string expected";if(e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&!(f.isInteger(e.modelVersion)||e.modelVersion&&f.isInteger(e.modelVersion.low)&&f.isInteger(e.modelVersion.high)))return"modelVersion: integer|Long expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!f.isString(e.docString))return"docString: string expected";if(e.graph!=null&&e.hasOwnProperty("graph")&&(s=u.onnx.GraphProto.verify(e.graph)))return"graph."+s;if(e.metadataProps!=null&&e.hasOwnProperty("metadataProps")){if(!Array.isArray(e.metadataProps))return"metadataProps: array expected";for(a=0;a<e.metadataProps.length;++a){var s;if(s=u.onnx.StringStringEntryProto.verify(e.metadataProps[a]))return"metadataProps."+s}}return null},n.fromObject=function(e){if(e instanceof u.onnx.ModelProto)return e;var a=new u.onnx.ModelProto;if(e.irVersion!=null&&(f.Long?(a.irVersion=f.Long.fromValue(e.irVersion)).unsigned=!1:typeof e.irVersion=="string"?a.irVersion=parseInt(e.irVersion,10):typeof e.irVersion=="number"?a.irVersion=e.irVersion:typeof e.irVersion=="object"&&(a.irVersion=new f.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber())),e.opsetImport){if(!Array.isArray(e.opsetImport))throw TypeError(".onnx.ModelProto.opsetImport: array expected");a.opsetImport=[];for(var s=0;s<e.opsetImport.length;++s){if(typeof e.opsetImport[s]!="object")throw TypeError(".onnx.ModelProto.opsetImport: object expected");a.opsetImport[s]=u.onnx.OperatorSetIdProto.fromObject(e.opsetImport[s])}}if(e.producerName!=null&&(a.producerName=String(e.producerName)),e.producerVersion!=null&&(a.producerVersion=String(e.producerVersion)),e.domain!=null&&(a.domain=String(e.domain)),e.modelVersion!=null&&(f.Long?(a.modelVersion=f.Long.fromValue(e.modelVersion)).unsigned=!1:typeof e.modelVersion=="string"?a.modelVersion=parseInt(e.modelVersion,10):typeof e.modelVersion=="number"?a.modelVersion=e.modelVersion:typeof e.modelVersion=="object"&&(a.modelVersion=new f.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber())),e.docString!=null&&(a.docString=String(e.docString)),e.graph!=null){if(typeof e.graph!="object")throw TypeError(".onnx.ModelProto.graph: object expected");a.graph=u.onnx.GraphProto.fromObject(e.graph)}if(e.metadataProps){if(!Array.isArray(e.metadataProps))throw TypeError(".onnx.ModelProto.metadataProps: array expected");for(a.metadataProps=[],s=0;s<e.metadataProps.length;++s){if(typeof e.metadataProps[s]!="object")throw TypeError(".onnx.ModelProto.metadataProps: object expected");a.metadataProps[s]=u.onnx.StringStringEntryProto.fromObject(e.metadataProps[s])}}return a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.opsetImport=[],s.metadataProps=[]),a.defaults){if(f.Long){var g=new f.Long(0,0,!1);s.irVersion=a.longs===String?g.toString():a.longs===Number?g.toNumber():g}else s.irVersion=a.longs===String?"0":0;s.producerName="",s.producerVersion="",s.domain="",f.Long?(g=new f.Long(0,0,!1),s.modelVersion=a.longs===String?g.toString():a.longs===Number?g.toNumber():g):s.modelVersion=a.longs===String?"0":0,s.docString="",s.graph=null}if(e.irVersion!=null&&e.hasOwnProperty("irVersion")&&(typeof e.irVersion=="number"?s.irVersion=a.longs===String?String(e.irVersion):e.irVersion:s.irVersion=a.longs===String?f.Long.prototype.toString.call(e.irVersion):a.longs===Number?new f.LongBits(e.irVersion.low>>>0,e.irVersion.high>>>0).toNumber():e.irVersion),e.producerName!=null&&e.hasOwnProperty("producerName")&&(s.producerName=e.producerName),e.producerVersion!=null&&e.hasOwnProperty("producerVersion")&&(s.producerVersion=e.producerVersion),e.domain!=null&&e.hasOwnProperty("domain")&&(s.domain=e.domain),e.modelVersion!=null&&e.hasOwnProperty("modelVersion")&&(typeof e.modelVersion=="number"?s.modelVersion=a.longs===String?String(e.modelVersion):e.modelVersion:s.modelVersion=a.longs===String?f.Long.prototype.toString.call(e.modelVersion):a.longs===Number?new f.LongBits(e.modelVersion.low>>>0,e.modelVersion.high>>>0).toNumber():e.modelVersion),e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),e.graph!=null&&e.hasOwnProperty("graph")&&(s.graph=u.onnx.GraphProto.toObject(e.graph,a)),e.opsetImport&&e.opsetImport.length){s.opsetImport=[];for(var y=0;y<e.opsetImport.length;++y)s.opsetImport[y]=u.onnx.OperatorSetIdProto.toObject(e.opsetImport[y],a)}if(e.metadataProps&&e.metadataProps.length)for(s.metadataProps=[],y=0;y<e.metadataProps.length;++y)s.metadataProps[y]=u.onnx.StringStringEntryProto.toObject(e.metadataProps[y],a);return s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.StringStringEntryProto=function(){function n(e){if(e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.key="",n.prototype.value="",n.create=function(e){return new n(e)},n.encode=function(e,a){return a||(a=_.create()),e.key!=null&&e.hasOwnProperty("key")&&a.uint32(10).string(e.key),e.value!=null&&e.hasOwnProperty("value")&&a.uint32(18).string(e.value),a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.StringStringEntryProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.key=e.string();break;case 2:g.value=e.string();break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(e)),this.decode(e,e.uint32())},n.verify=function(e){return typeof e!="object"||e===null?"object expected":e.key!=null&&e.hasOwnProperty("key")&&!f.isString(e.key)?"key: string expected":e.value!=null&&e.hasOwnProperty("value")&&!f.isString(e.value)?"value: string expected":null},n.fromObject=function(e){if(e instanceof u.onnx.StringStringEntryProto)return e;var a=new u.onnx.StringStringEntryProto;return e.key!=null&&(a.key=String(e.key)),e.value!=null&&(a.value=String(e.value)),a},n.toObject=function(e,a){a||(a={});var s={};return a.defaults&&(s.key="",s.value=""),e.key!=null&&e.hasOwnProperty("key")&&(s.key=e.key),e.value!=null&&e.hasOwnProperty("value")&&(s.value=e.value),s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.TensorAnnotation=function(){function n(e){if(this.quantParameterTensorNames=[],e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.tensorName="",n.prototype.quantParameterTensorNames=f.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&a.uint32(10).string(e.tensorName),e.quantParameterTensorNames!=null&&e.quantParameterTensorNames.length)for(var s=0;s<e.quantParameterTensorNames.length;++s)u.onnx.StringStringEntryProto.encode(e.quantParameterTensorNames[s],a.uint32(18).fork()).ldelim();return a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.TensorAnnotation;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.tensorName=e.string();break;case 2:g.quantParameterTensorNames&&g.quantParameterTensorNames.length||(g.quantParameterTensorNames=[]),g.quantParameterTensorNames.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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")&&!f.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 a=0;a<e.quantParameterTensorNames.length;++a){var s=u.onnx.StringStringEntryProto.verify(e.quantParameterTensorNames[a]);if(s)return"quantParameterTensorNames."+s}}return null},n.fromObject=function(e){if(e instanceof u.onnx.TensorAnnotation)return e;var a=new u.onnx.TensorAnnotation;if(e.tensorName!=null&&(a.tensorName=String(e.tensorName)),e.quantParameterTensorNames){if(!Array.isArray(e.quantParameterTensorNames))throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: array expected");a.quantParameterTensorNames=[];for(var s=0;s<e.quantParameterTensorNames.length;++s){if(typeof e.quantParameterTensorNames[s]!="object")throw TypeError(".onnx.TensorAnnotation.quantParameterTensorNames: object expected");a.quantParameterTensorNames[s]=u.onnx.StringStringEntryProto.fromObject(e.quantParameterTensorNames[s])}}return a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.quantParameterTensorNames=[]),a.defaults&&(s.tensorName=""),e.tensorName!=null&&e.hasOwnProperty("tensorName")&&(s.tensorName=e.tensorName),e.quantParameterTensorNames&&e.quantParameterTensorNames.length){s.quantParameterTensorNames=[];for(var g=0;g<e.quantParameterTensorNames.length;++g)s.quantParameterTensorNames[g]=u.onnx.StringStringEntryProto.toObject(e.quantParameterTensorNames[g],a)}return s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.GraphProto=function(){function n(e){if(this.node=[],this.initializer=[],this.input=[],this.output=[],this.valueInfo=[],this.quantizationAnnotation=[],e)for(var a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.node=f.emptyArray,n.prototype.name="",n.prototype.initializer=f.emptyArray,n.prototype.docString="",n.prototype.input=f.emptyArray,n.prototype.output=f.emptyArray,n.prototype.valueInfo=f.emptyArray,n.prototype.quantizationAnnotation=f.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.node!=null&&e.node.length)for(var s=0;s<e.node.length;++s)u.onnx.NodeProto.encode(e.node[s],a.uint32(10).fork()).ldelim();if(e.name!=null&&e.hasOwnProperty("name")&&a.uint32(18).string(e.name),e.initializer!=null&&e.initializer.length)for(s=0;s<e.initializer.length;++s)u.onnx.TensorProto.encode(e.initializer[s],a.uint32(42).fork()).ldelim();if(e.docString!=null&&e.hasOwnProperty("docString")&&a.uint32(82).string(e.docString),e.input!=null&&e.input.length)for(s=0;s<e.input.length;++s)u.onnx.ValueInfoProto.encode(e.input[s],a.uint32(90).fork()).ldelim();if(e.output!=null&&e.output.length)for(s=0;s<e.output.length;++s)u.onnx.ValueInfoProto.encode(e.output[s],a.uint32(98).fork()).ldelim();if(e.valueInfo!=null&&e.valueInfo.length)for(s=0;s<e.valueInfo.length;++s)u.onnx.ValueInfoProto.encode(e.valueInfo[s],a.uint32(106).fork()).ldelim();if(e.quantizationAnnotation!=null&&e.quantizationAnnotation.length)for(s=0;s<e.quantizationAnnotation.length;++s)u.onnx.TensorAnnotation.encode(e.quantizationAnnotation[s],a.uint32(114).fork()).ldelim();return a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.GraphProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:g.node&&g.node.length||(g.node=[]),g.node.push(u.onnx.NodeProto.decode(e,e.uint32()));break;case 2:g.name=e.string();break;case 5:g.initializer&&g.initializer.length||(g.initializer=[]),g.initializer.push(u.onnx.TensorProto.decode(e,e.uint32()));break;case 10:g.docString=e.string();break;case 11:g.input&&g.input.length||(g.input=[]),g.input.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 12:g.output&&g.output.length||(g.output=[]),g.output.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 13:g.valueInfo&&g.valueInfo.length||(g.valueInfo=[]),g.valueInfo.push(u.onnx.ValueInfoProto.decode(e,e.uint32()));break;case 14:g.quantizationAnnotation&&g.quantizationAnnotation.length||(g.quantizationAnnotation=[]),g.quantizationAnnotation.push(u.onnx.TensorAnnotation.decode(e,e.uint32()));break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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 a=0;a<e.node.length;++a)if(s=u.onnx.NodeProto.verify(e.node[a]))return"node."+s}if(e.name!=null&&e.hasOwnProperty("name")&&!f.isString(e.name))return"name: string expected";if(e.initializer!=null&&e.hasOwnProperty("initializer")){if(!Array.isArray(e.initializer))return"initializer: array expected";for(a=0;a<e.initializer.length;++a)if(s=u.onnx.TensorProto.verify(e.initializer[a]))return"initializer."+s}if(e.docString!=null&&e.hasOwnProperty("docString")&&!f.isString(e.docString))return"docString: string expected";if(e.input!=null&&e.hasOwnProperty("input")){if(!Array.isArray(e.input))return"input: array expected";for(a=0;a<e.input.length;++a)if(s=u.onnx.ValueInfoProto.verify(e.input[a]))return"input."+s}if(e.output!=null&&e.hasOwnProperty("output")){if(!Array.isArray(e.output))return"output: array expected";for(a=0;a<e.output.length;++a)if(s=u.onnx.ValueInfoProto.verify(e.output[a]))return"output."+s}if(e.valueInfo!=null&&e.hasOwnProperty("valueInfo")){if(!Array.isArray(e.valueInfo))return"valueInfo: array expected";for(a=0;a<e.valueInfo.length;++a)if(s=u.onnx.ValueInfoProto.verify(e.valueInfo[a]))return"valueInfo."+s}if(e.quantizationAnnotation!=null&&e.hasOwnProperty("quantizationAnnotation")){if(!Array.isArray(e.quantizationAnnotation))return"quantizationAnnotation: array expected";for(a=0;a<e.quantizationAnnotation.length;++a){var s;if(s=u.onnx.TensorAnnotation.verify(e.quantizationAnnotation[a]))return"quantizationAnnotation."+s}}return null},n.fromObject=function(e){if(e instanceof u.onnx.GraphProto)return e;var a=new u.onnx.GraphProto;if(e.node){if(!Array.isArray(e.node))throw TypeError(".onnx.GraphProto.node: array expected");a.node=[];for(var s=0;s<e.node.length;++s){if(typeof e.node[s]!="object")throw TypeError(".onnx.GraphProto.node: object expected");a.node[s]=u.onnx.NodeProto.fromObject(e.node[s])}}if(e.name!=null&&(a.name=String(e.name)),e.initializer){if(!Array.isArray(e.initializer))throw TypeError(".onnx.GraphProto.initializer: array expected");for(a.initializer=[],s=0;s<e.initializer.length;++s){if(typeof e.initializer[s]!="object")throw TypeError(".onnx.GraphProto.initializer: object expected");a.initializer[s]=u.onnx.TensorProto.fromObject(e.initializer[s])}}if(e.docString!=null&&(a.docString=String(e.docString)),e.input){if(!Array.isArray(e.input))throw TypeError(".onnx.GraphProto.input: array expected");for(a.input=[],s=0;s<e.input.length;++s){if(typeof e.input[s]!="object")throw TypeError(".onnx.GraphProto.input: object expected");a.input[s]=u.onnx.ValueInfoProto.fromObject(e.input[s])}}if(e.output){if(!Array.isArray(e.output))throw TypeError(".onnx.GraphProto.output: array expected");for(a.output=[],s=0;s<e.output.length;++s){if(typeof e.output[s]!="object")throw TypeError(".onnx.GraphProto.output: object expected");a.output[s]=u.onnx.ValueInfoProto.fromObject(e.output[s])}}if(e.valueInfo){if(!Array.isArray(e.valueInfo))throw TypeError(".onnx.GraphProto.valueInfo: array expected");for(a.valueInfo=[],s=0;s<e.valueInfo.length;++s){if(typeof e.valueInfo[s]!="object")throw TypeError(".onnx.GraphProto.valueInfo: object expected");a.valueInfo[s]=u.onnx.ValueInfoProto.fromObject(e.valueInfo[s])}}if(e.quantizationAnnotation){if(!Array.isArray(e.quantizationAnnotation))throw TypeError(".onnx.GraphProto.quantizationAnnotation: array expected");for(a.quantizationAnnotation=[],s=0;s<e.quantizationAnnotation.length;++s){if(typeof e.quantizationAnnotation[s]!="object")throw TypeError(".onnx.GraphProto.quantizationAnnotation: object expected");a.quantizationAnnotation[s]=u.onnx.TensorAnnotation.fromObject(e.quantizationAnnotation[s])}}return a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.node=[],s.initializer=[],s.input=[],s.output=[],s.valueInfo=[],s.quantizationAnnotation=[]),a.defaults&&(s.name="",s.docString=""),e.node&&e.node.length){s.node=[];for(var g=0;g<e.node.length;++g)s.node[g]=u.onnx.NodeProto.toObject(e.node[g],a)}if(e.name!=null&&e.hasOwnProperty("name")&&(s.name=e.name),e.initializer&&e.initializer.length)for(s.initializer=[],g=0;g<e.initializer.length;++g)s.initializer[g]=u.onnx.TensorProto.toObject(e.initializer[g],a);if(e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),e.input&&e.input.length)for(s.input=[],g=0;g<e.input.length;++g)s.input[g]=u.onnx.ValueInfoProto.toObject(e.input[g],a);if(e.output&&e.output.length)for(s.output=[],g=0;g<e.output.length;++g)s.output[g]=u.onnx.ValueInfoProto.toObject(e.output[g],a);if(e.valueInfo&&e.valueInfo.length)for(s.valueInfo=[],g=0;g<e.valueInfo.length;++g)s.valueInfo[g]=u.onnx.ValueInfoProto.toObject(e.valueInfo[g],a);if(e.quantizationAnnotation&&e.quantizationAnnotation.length)for(s.quantizationAnnotation=[],g=0;g<e.quantizationAnnotation.length;++g)s.quantizationAnnotation[g]=u.onnx.TensorAnnotation.toObject(e.quantizationAnnotation[g],a);return s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n}(),b.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 a=Object.keys(e),s=0;s<a.length;++s)e[a[s]]!=null&&(this[a[s]]=e[a[s]])}return n.prototype.dims=f.emptyArray,n.prototype.dataType=0,n.prototype.segment=null,n.prototype.floatData=f.emptyArray,n.prototype.int32Data=f.emptyArray,n.prototype.stringData=f.emptyArray,n.prototype.int64Data=f.emptyArray,n.prototype.name="",n.prototype.docString="",n.prototype.rawData=f.newBuffer([]),n.prototype.externalData=f.emptyArray,n.prototype.dataLocation=0,n.prototype.doubleData=f.emptyArray,n.prototype.uint64Data=f.emptyArray,n.create=function(e){return new n(e)},n.encode=function(e,a){if(a||(a=_.create()),e.dims!=null&&e.dims.length){a.uint32(10).fork();for(var s=0;s<e.dims.length;++s)a.int64(e.dims[s]);a.ldelim()}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&a.uint32(16).int32(e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&u.onnx.TensorProto.Segment.encode(e.segment,a.uint32(26).fork()).ldelim(),e.floatData!=null&&e.floatData.length){for(a.uint32(34).fork(),s=0;s<e.floatData.length;++s)a.float(e.floatData[s]);a.ldelim()}if(e.int32Data!=null&&e.int32Data.length){for(a.uint32(42).fork(),s=0;s<e.int32Data.length;++s)a.int32(e.int32Data[s]);a.ldelim()}if(e.stringData!=null&&e.stringData.length)for(s=0;s<e.stringData.length;++s)a.uint32(50).bytes(e.stringData[s]);if(e.int64Data!=null&&e.int64Data.length){for(a.uint32(58).fork(),s=0;s<e.int64Data.length;++s)a.int64(e.int64Data[s]);a.ldelim()}if(e.name!=null&&e.hasOwnProperty("name")&&a.uint32(66).string(e.name),e.rawData!=null&&e.hasOwnProperty("rawData")&&a.uint32(74).bytes(e.rawData),e.doubleData!=null&&e.doubleData.length){for(a.uint32(82).fork(),s=0;s<e.doubleData.length;++s)a.double(e.doubleData[s]);a.ldelim()}if(e.uint64Data!=null&&e.uint64Data.length){for(a.uint32(90).fork(),s=0;s<e.uint64Data.length;++s)a.uint64(e.uint64Data[s]);a.ldelim()}if(e.docString!=null&&e.hasOwnProperty("docString")&&a.uint32(98).string(e.docString),e.externalData!=null&&e.externalData.length)for(s=0;s<e.externalData.length;++s)u.onnx.StringStringEntryProto.encode(e.externalData[s],a.uint32(106).fork()).ldelim();return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&a.uint32(112).int32(e.dataLocation),a},n.encodeDelimited=function(e,a){return this.encode(e,a).ldelim()},n.decode=function(e,a){e instanceof m||(e=m.create(e));for(var s=a===void 0?e.len:e.pos+a,g=new u.onnx.TensorProto;e.pos<s;){var y=e.uint32();switch(y>>>3){case 1:if(g.dims&&g.dims.length||(g.dims=[]),(7&y)==2)for(var x=e.uint32()+e.pos;e.pos<x;)g.dims.push(e.int64());else g.dims.push(e.int64());break;case 2:g.dataType=e.int32();break;case 3:g.segment=u.onnx.TensorProto.Segment.decode(e,e.uint32());break;case 4:if(g.floatData&&g.floatData.length||(g.floatData=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.floatData.push(e.float());else g.floatData.push(e.float());break;case 5:if(g.int32Data&&g.int32Data.length||(g.int32Data=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.int32Data.push(e.int32());else g.int32Data.push(e.int32());break;case 6:g.stringData&&g.stringData.length||(g.stringData=[]),g.stringData.push(e.bytes());break;case 7:if(g.int64Data&&g.int64Data.length||(g.int64Data=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.int64Data.push(e.int64());else g.int64Data.push(e.int64());break;case 8:g.name=e.string();break;case 12:g.docString=e.string();break;case 9:g.rawData=e.bytes();break;case 13:g.externalData&&g.externalData.length||(g.externalData=[]),g.externalData.push(u.onnx.StringStringEntryProto.decode(e,e.uint32()));break;case 14:g.dataLocation=e.int32();break;case 10:if(g.doubleData&&g.doubleData.length||(g.doubleData=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.doubleData.push(e.double());else g.doubleData.push(e.double());break;case 11:if(g.uint64Data&&g.uint64Data.length||(g.uint64Data=[]),(7&y)==2)for(x=e.uint32()+e.pos;e.pos<x;)g.uint64Data.push(e.uint64());else g.uint64Data.push(e.uint64());break;default:e.skipType(7&y)}}return g},n.decodeDelimited=function(e){return e instanceof m||(e=new m(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 a=0;a<e.dims.length;++a)if(!(f.isInteger(e.dims[a])||e.dims[a]&&f.isInteger(e.dims[a].low)&&f.isInteger(e.dims[a].high)))return"dims: integer|Long[] expected"}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&!f.isInteger(e.dataType))return"dataType: integer expected";if(e.segment!=null&&e.hasOwnProperty("segment")&&(s=u.onnx.TensorProto.Segment.verify(e.segment)))return"segment."+s;if(e.floatData!=null&&e.hasOwnProperty("floatData")){if(!Array.isArray(e.floatData))return"floatData: array expected";for(a=0;a<e.floatData.length;++a)if(typeof e.floatData[a]!="number")return"floatData: number[] expected"}if(e.int32Data!=null&&e.hasOwnProperty("int32Data")){if(!Array.isArray(e.int32Data))return"int32Data: array expected";for(a=0;a<e.int32Data.length;++a)if(!f.isInteger(e.int32Data[a]))return"int32Data: integer[] expected"}if(e.stringData!=null&&e.hasOwnProperty("stringData")){if(!Array.isArray(e.stringData))return"stringData: array expected";for(a=0;a<e.stringData.length;++a)if(!(e.stringData[a]&&typeof e.stringData[a].length=="number"||f.isString(e.stringData[a])))return"stringData: buffer[] expected"}if(e.int64Data!=null&&e.hasOwnProperty("int64Data")){if(!Array.isArray(e.int64Data))return"int64Data: array expected";for(a=0;a<e.int64Data.length;++a)if(!(f.isInteger(e.int64Data[a])||e.int64Data[a]&&f.isInteger(e.int64Data[a].low)&&f.isInteger(e.int64Data[a].high)))return"int64Data: integer|Long[] expected"}if(e.name!=null&&e.hasOwnProperty("name")&&!f.isString(e.name))return"name: string expected";if(e.docString!=null&&e.hasOwnProperty("docString")&&!f.isString(e.docString))return"docString: string expected";if(e.rawData!=null&&e.hasOwnProperty("rawData")&&!(e.rawData&&typeof e.rawData.length=="number"||f.isString(e.rawData)))return"rawData: buffer expected";if(e.externalData!=null&&e.hasOwnProperty("externalData")){if(!Array.isArray(e.externalData))return"externalData: array expected";for(a=0;a<e.externalData.length;++a){var s;if(s=u.onnx.StringStringEntryProto.verify(e.externalData[a]))return"externalData."+s}}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(a=0;a<e.doubleData.length;++a)if(typeof e.doubleData[a]!="number")return"doubleData: number[] expected"}if(e.uint64Data!=null&&e.hasOwnProperty("uint64Data")){if(!Array.isArray(e.uint64Data))return"uint64Data: array expected";for(a=0;a<e.uint64Data.length;++a)if(!(f.isInteger(e.uint64Data[a])||e.uint64Data[a]&&f.isInteger(e.uint64Data[a].low)&&f.isInteger(e.uint64Data[a].high)))return"uint64Data: integer|Long[] expected"}return null},n.fromObject=function(e){if(e instanceof u.onnx.TensorProto)return e;var a=new u.onnx.TensorProto;if(e.dims){if(!Array.isArray(e.dims))throw TypeError(".onnx.TensorProto.dims: array expected");a.dims=[];for(var s=0;s<e.dims.length;++s)f.Long?(a.dims[s]=f.Long.fromValue(e.dims[s])).unsigned=!1:typeof e.dims[s]=="string"?a.dims[s]=parseInt(e.dims[s],10):typeof e.dims[s]=="number"?a.dims[s]=e.dims[s]:typeof e.dims[s]=="object"&&(a.dims[s]=new f.LongBits(e.dims[s].low>>>0,e.dims[s].high>>>0).toNumber())}if(e.dataType!=null&&(a.dataType=0|e.dataType),e.segment!=null){if(typeof e.segment!="object")throw TypeError(".onnx.TensorProto.segment: object expected");a.segment=u.onnx.TensorProto.Segment.fromObject(e.segment)}if(e.floatData){if(!Array.isArray(e.floatData))throw TypeError(".onnx.TensorProto.floatData: array expected");for(a.floatData=[],s=0;s<e.floatData.length;++s)a.floatData[s]=Number(e.floatData[s])}if(e.int32Data){if(!Array.isArray(e.int32Data))throw TypeError(".onnx.TensorProto.int32Data: array expected");for(a.int32Data=[],s=0;s<e.int32Data.length;++s)a.int32Data[s]=0|e.int32Data[s]}if(e.stringData){if(!Array.isArray(e.stringData))throw TypeError(".onnx.TensorProto.stringData: array expected");for(a.stringData=[],s=0;s<e.stringData.length;++s)typeof e.stringData[s]=="string"?f.base64.decode(e.stringData[s],a.stringData[s]=f.newBuffer(f.base64.length(e.stringData[s])),0):e.stringData[s].length&&(a.stringData[s]=e.stringData[s])}if(e.int64Data){if(!Array.isArray(e.int64Data))throw TypeError(".onnx.TensorProto.int64Data: array expected");for(a.int64Data=[],s=0;s<e.int64Data.length;++s)f.Long?(a.int64Data[s]=f.Long.fromValue(e.int64Data[s])).unsigned=!1:typeof e.int64Data[s]=="string"?a.int64Data[s]=parseInt(e.int64Data[s],10):typeof e.int64Data[s]=="number"?a.int64Data[s]=e.int64Data[s]:typeof e.int64Data[s]=="object"&&(a.int64Data[s]=new f.LongBits(e.int64Data[s].low>>>0,e.int64Data[s].high>>>0).toNumber())}if(e.name!=null&&(a.name=String(e.name)),e.docString!=null&&(a.docString=String(e.docString)),e.rawData!=null&&(typeof e.rawData=="string"?f.base64.decode(e.rawData,a.rawData=f.newBuffer(f.base64.length(e.rawData)),0):e.rawData.length&&(a.rawData=e.rawData)),e.externalData){if(!Array.isArray(e.externalData))throw TypeError(".onnx.TensorProto.externalData: array expected");for(a.externalData=[],s=0;s<e.externalData.length;++s){if(typeof e.externalData[s]!="object")throw TypeError(".onnx.TensorProto.externalData: object expected");a.externalData[s]=u.onnx.StringStringEntryProto.fromObject(e.externalData[s])}}switch(e.dataLocation){case"DEFAULT":case 0:a.dataLocation=0;break;case"EXTERNAL":case 1:a.dataLocation=1}if(e.doubleData){if(!Array.isArray(e.doubleData))throw TypeError(".onnx.TensorProto.doubleData: array expected");for(a.doubleData=[],s=0;s<e.doubleData.length;++s)a.doubleData[s]=Number(e.doubleData[s])}if(e.uint64Data){if(!Array.isArray(e.uint64Data))throw TypeError(".onnx.TensorProto.uint64Data: array expected");for(a.uint64Data=[],s=0;s<e.uint64Data.length;++s)f.Long?(a.uint64Data[s]=f.Long.fromValue(e.uint64Data[s])).unsigned=!0:typeof e.uint64Data[s]=="string"?a.uint64Data[s]=parseInt(e.uint64Data[s],10):typeof e.uint64Data[s]=="number"?a.uint64Data[s]=e.uint64Data[s]:typeof e.uint64Data[s]=="object"&&(a.uint64Data[s]=new f.LongBits(e.uint64Data[s].low>>>0,e.uint64Data[s].high>>>0).toNumber(!0))}return a},n.toObject=function(e,a){a||(a={});var s={};if((a.arrays||a.defaults)&&(s.dims=[],s.floatData=[],s.int32Data=[],s.stringData=[],s.int64Data=[],s.doubleData=[],s.uint64Data=[],s.externalData=[]),a.defaults&&(s.dataType=0,s.segment=null,s.name="",a.bytes===String?s.rawData="":(s.rawData=[],a.bytes!==Array&&(s.rawData=f.newBuffer(s.rawData))),s.docString="",s.dataLocation=a.enums===String?"DEFAULT":0),e.dims&&e.dims.length){s.dims=[];for(var g=0;g<e.dims.length;++g)typeof e.dims[g]=="number"?s.dims[g]=a.longs===String?String(e.dims[g]):e.dims[g]:s.dims[g]=a.longs===String?f.Long.prototype.toString.call(e.dims[g]):a.longs===Number?new f.LongBits(e.dims[g].low>>>0,e.dims[g].high>>>0).toNumber():e.dims[g]}if(e.dataType!=null&&e.hasOwnProperty("dataType")&&(s.dataType=e.dataType),e.segment!=null&&e.hasOwnProperty("segment")&&(s.segment=u.onnx.TensorProto.Segment.toObject(e.segment,a)),e.floatData&&e.floatData.length)for(s.floatData=[],g=0;g<e.floatData.length;++g)s.floatData[g]=a.json&&!isFinite(e.floatData[g])?String(e.floatData[g]):e.floatData[g];if(e.int32Data&&e.int32Data.length)for(s.int32Data=[],g=0;g<e.int32Data.length;++g)s.int32Data[g]=e.int32Data[g];if(e.stringData&&e.stringData.length)for(s.stringData=[],g=0;g<e.stringData.length;++g)s.stringData[g]=a.bytes===String?f.base64.encode(e.stringData[g],0,e.stringData[g].length):a.bytes===Array?Array.prototype.slice.call(e.stringData[g]):e.stringData[g];if(e.int64Data&&e.int64Data.length)for(s.int64Data=[],g=0;g<e.int64Data.length;++g)typeof 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f.LongBits(e.uint64Data[g].low>>>0,e.uint64Data[g].high>>>0).toNumber(!0):e.uint64Data[g];if(e.docString!=null&&e.hasOwnProperty("docString")&&(s.docString=e.docString),e.externalData&&e.externalData.length)for(s.externalData=[],g=0;g<e.externalData.length;++g)s.externalData[g]=u.onnx.StringStringEntryProto.toObject(e.externalData[g],a);return e.dataLocation!=null&&e.hasOwnProperty("dataLocation")&&(s.dataLocation=a.enums===String?u.onnx.TensorProto.DataLocation[e.dataLocation]:e.dataLocation),s},n.prototype.toJSON=function(){return this.constructor.toObject(this,c.util.toJSONOptions)},n.DataType=function(){var e={},a=Object.create(e);return 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l.onnx.AttributeProto.AttributeType.FLOATS:return"floats";case l.onnx.AttributeProto.AttributeType.INTS:return"ints";case l.onnx.AttributeProto.AttributeType.STRINGS:return"strings";case l.onnx.AttributeProto.AttributeType.TENSORS:return"tensors";default:throw new Error(`attribute type is not supported yet: ${l.onnx.AttributeProto.AttributeType[n]}`)}}static getValue(u){const n=u instanceof l.onnx.AttributeProto?u.type:u.type();if(n===l.onnx.AttributeProto.AttributeType.GRAPH||n===l.onnx.AttributeProto.AttributeType.GRAPHS)throw new Error("graph attribute is not supported yet");const e=this.getValueNoCheck(u);if(n===l.onnx.AttributeProto.AttributeType.INT&&c.LongUtil.isLong(e))return c.LongUtil.longToNumber(e);if(n===l.onnx.AttributeProto.AttributeType.INTS){const a=e,s=new Array(a.length);for(let g=0;g<a.length;g++){const y=a[g];s[g]=c.LongUtil.longToNumber(y)}return s}if(n===l.onnx.AttributeProto.AttributeType.TENSOR)return u instanceof l.onnx.AttributeProto?b.Tensor.fromProto(e):b.Tensor.fromOrtTensor(e);if(n===l.onnx.AttributeProto.AttributeType.TENSORS){if(u instanceof l.onnx.AttributeProto)return e.map(a=>b.Tensor.fromProto(a));if(u instanceof m.Attribute)return e.map(a=>b.Tensor.fromOrtTensor(a))}if(n===l.onnx.AttributeProto.AttributeType.STRING&&u instanceof l.onnx.AttributeProto){const a=e;return(0,c.decodeUtf8String)(a)}return n===l.onnx.AttributeProto.AttributeType.STRINGS&&u instanceof l.onnx.AttributeProto?e.map(c.decodeUtf8String):e}static getValueNoCheck(u){return u instanceof l.onnx.AttributeProto?this.getValueNoCheckFromOnnxFormat(u):this.getValueNoCheckFromOrtFormat(u)}static getValueNoCheckFromOnnxFormat(u){switch(u.type){case l.onnx.AttributeProto.AttributeType.FLOAT:return u.f;case l.onnx.AttributeProto.AttributeType.INT:return u.i;case l.onnx.AttributeProto.AttributeType.STRING:return u.s;case l.onnx.AttributeProto.AttributeType.TENSOR:return u.t;case l.onnx.AttributeProto.AttributeType.GRAPH:return u.g;case l.onnx.AttributeProto.AttributeType.FLOATS:return u.floats;case l.onnx.AttributeProto.AttributeType.INTS:return u.ints;case l.onnx.AttributeProto.AttributeType.STRINGS:return u.strings;case l.onnx.AttributeProto.AttributeType.TENSORS:return u.tensors;case l.onnx.AttributeProto.AttributeType.GRAPHS:return u.graphs;default:throw new Error(`unsupported attribute type: ${l.onnx.AttributeProto.AttributeType[u.type]}`)}}static getValueNoCheckFromOrtFormat(u){switch(u.type()){case m.AttributeType.FLOAT:return u.f();case m.AttributeType.INT:return u.i();case m.AttributeType.STRING:return u.s();case m.AttributeType.TENSOR:return u.t();case m.AttributeType.GRAPH:return u.g();case m.AttributeType.FLOATS:return u.floatsArray();case m.AttributeType.INTS:{const n=[];for(let e=0;e<u.intsLength();e++)n.push(u.ints(e));return n}case m.AttributeType.STRINGS:{const n=[];for(let e=0;e<u.stringsLength();e++)n.push(u.strings(e));return n}case m.AttributeType.TENSORS:{const n=[];for(let e=0;e<u.tensorsLength();e++)n.push(u.tensors(e));return n}default:throw new Error(`unsupported attribute type: ${m.AttributeType[u.type()]}`)}}}o.Attribute=_},7091:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.resolveBackend=o.backend=void 0;const l=d(5038),p=new Map;async function b(c){const m=o.backend;if(m[c]!==void 0&&function(_){const f=_;return"initialize"in f&&typeof f.initialize=="function"&&"createSessionHandler"in f&&typeof f.createSessionHandler=="function"&&"dispose"in f&&typeof f.dispose=="function"}(m[c])){const _=m[c];let f=_.initialize();if(typeof f=="object"&&"then"in f&&(f=await f),f)return p.set(c,_),_}}o.backend={webgl:new l.WebGLBackend},o.resolveBackend=async function c(m){if(!m)return c(["webgl"]);{const _=typeof m=="string"?[m]:m;for(const f of _){const u=p.get(f);if(u)return u;const n=await b(f);if(n)return n}}throw new Error("no available backend to use")}},5038:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.WebGLBackend=void 0;const l=d(1670),p=d(6231),b=d(6416),c=d(7305);o.WebGLBackend=class{get contextId(){return l.env.webgl.contextId}set contextId(m){l.env.webgl.contextId=m}get matmulMaxBatchSize(){return l.env.webgl.matmulMaxBatchSize}set matmulMaxBatchSize(m){l.env.webgl.matmulMaxBatchSize=m}get textureCacheMode(){return l.env.webgl.textureCacheMode}set textureCacheMode(m){l.env.webgl.textureCacheMode=m}get pack(){return l.env.webgl.pack}set pack(m){l.env.webgl.pack=m}get async(){return l.env.webgl.async}set async(m){l.env.webgl.async=m}initialize(){try{return this.glContext=(0,c.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),p.Logger.setWithEnv(l.env),p.Logger.verbose("WebGLBackend",`Created WebGLContext: ${typeof this.glContext} with matmulMaxBatchSize: ${this.matmulMaxBatchSize}; textureCacheMode: ${this.textureCacheMode}; pack: ${this.pack}; async: ${this.async}.`),!0}catch(m){return p.Logger.warning("WebGLBackend",`Unable to initialize WebGLBackend. ${m}`),!1}}createSessionHandler(m){return new b.WebGLSessionHandler(this,m)}dispose(){this.glContext.dispose()}}},5107:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.CoordsGlslLib=void 0;const l=d(2517),p=d(8520),b=d(5060),c=d(7859),m=d(9390);class _ extends p.GlslLib{constructor(u){super(u)}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 p.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 p.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 u=this.context.outputTextureLayout;return u.isPacked?this.getPackedOutputSamplingSnippet(u):this.getUnpackedOutputSamplingSnippet(u)}getPackedOutputSamplingSnippet(u){const n=u.unpackedShape,e=[u.width,u.height],a={},s="getOutputCoords";switch(n.length){case 0:a[s]=this.getOutputScalarCoords();break;case 1:a[s]=this.getOutputPacked1DCoords(n,e);break;case 2:a[s]=this.getOutputPacked2DCoords(n,e);break;case 3:a[s]=this.getOutputPacked3DCoords(n,e);break;default:a[s]=this.getOutputPackedNDCoords(n,e)}const g=`
+      void setOutput(vec4 val) {
+        ${(0,b.getGlsl)(this.context.glContext.version).output} = val;
+      }
+    `;return a.floatTextureSetRGBA=new p.GlslLibRoutine(g),a}getUnpackedOutputSamplingSnippet(u){const n=u.unpackedShape,e=[u.width,u.height],a={},s="getOutputCoords";switch(n.length){case 0:a[s]=this.getOutputScalarCoords();break;case 1:a[s]=this.getOutputUnpacked1DCoords(n,e);break;case 2:a[s]=this.getOutputUnpacked2DCoords(n,e);break;case 3:a[s]=this.getOutputUnpacked3DCoords(n,e);break;case 4:a[s]=this.getOutputUnpacked4DCoords(n,e);break;case 5:a[s]=this.getOutputUnpacked5DCoords(n,e);break;case 6:a[s]=this.getOutputUnpacked6DCoords(n,e);break;default:throw new Error(`Unsupported output dimensionality: ${n.length}`)}const g=`
+        void setOutput(float val) {
+          ${(0,b.getGlsl)(this.context.glContext.version).output} = vec4(val, 0, 0, 0);
+        }
+    `;return a.floatTextureSetR=new p.GlslLibRoutine(g),a}getOutputScalarCoords(){return new p.GlslLibRoutine(`
+      int getOutputCoords() {
+        return 0;
+      }
+    `)}getOutputPacked1DCoords(u,n){const e=n;let a="";return e[0]===1?(a=`
+          int getOutputCoords() {
+            return 2 * int(TexCoords.y * ${e[1]}.0);
+          }
+        `,new p.GlslLibRoutine(a)):e[1]===1?(a=`
+          int getOutputCoords() {
+            return 2 * int(TexCoords.x * ${e[0]}.0);
+          }
+        `,new p.GlslLibRoutine(a)):(a=`
+        int getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                 vec2(${e[0]}, ${e[1]}));
+          return 2 * (resTexRC.y * ${e[0]} + resTexRC.x);
+        }
+      `,new p.GlslLibRoutine(a))}getOutputPacked2DCoords(u,n){let e="";if(l.ArrayUtil.arraysEqual(u,n))return e=`
+        ivec2 getOutputCoords() {
+          return 2 * ivec2(TexCoords.xy * vec2(${n[0]}, ${n[1]}));
+        }
+      `,new p.GlslLibRoutine(e);const a=n,s=Math.ceil(u[1]/2);return e=`
+        ivec2 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${a[0]}, ${a[1]}));
+
+          int index = resTexRC.y * ${a[0]} + resTexRC.x;
+
+          // reverse r and c order for packed texture
+          int r = imod(index, ${s}) * 2;
+          int c = 2 * (index / ${s});
+
+          return ivec2(r, c);
+        }
+      `,new p.GlslLibRoutine(e)}getOutputPacked3DCoords(u,n){const e=[n[0],n[1]],a=Math.ceil(u[2]/2),s=a*Math.ceil(u[1]/2),g=`
+        ivec3 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${e[0]}, ${e[1]}));
+          int index = resTexRC.y * ${e[0]} + resTexRC.x;
+
+          int b = index / ${s};
+          index -= b * ${s};
+
+          // reverse r and c order for packed texture
+          int r = imod(index, ${a}) * 2;
+          int c = 2 * (index / ${a});
+
+          return ivec3(b, r, c);
+        }
+      `;return new p.GlslLibRoutine(g)}getOutputPackedNDCoords(u,n){const e=[n[0],n[1]],a=Math.ceil(u[u.length-1]/2),s=a*Math.ceil(u[u.length-2]/2);let g=s,y="",x="b, r, c";for(let S=2;S<u.length-1;S++)g*=u[u.length-S-1],y=`
+      int b${S} = index / ${g};
+      index -= b${S} * ${g};
+    `+y,x=`b${S}, `+x;const E=`
+      ivec${u.length} getOutputCoords() {
+        ivec2 resTexRC = ivec2(TexCoords.xy *
+                              vec2(${e[0]}, ${e[1]}));
+        int index = resTexRC.y * ${e[0]} + resTexRC.x;
+
+        ${y}
+
+        int b = index / ${s};
+        index -= b * ${s};
+
+        // reverse r and c order for packed texture
+        int r = imod(index, ${a}) * 2;
+        int c = 2 * (index / ${a});
+
+        return ivec${u.length}(${x});
+      }
+    `;return new p.GlslLibRoutine(E)}getOutputUnpacked1DCoords(u,n){const e=`
+        int getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${n[0]}, ${n[1]}));
+          return resTexRC.y * ${n[0]} + resTexRC.x;
+        }
+      `;return new p.GlslLibRoutine(e)}getOutputUnpacked2DCoords(u,n){const e=`
+        ivec2 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${n[0]}, ${n[1]}));
+          int index = resTexRC.y * ${n[0]} + resTexRC.x;
+          int r = index / ${u[1]};
+          int c = index - r * ${u[1]};
+          return ivec2(r, c);
+        }
+      `;return new p.GlslLibRoutine(e)}getOutputUnpacked3DCoords(u,n){let e="";const a=u.length;let s=null;a<2&&(s=[]),s=new Array(a-1),s[a-2]=u[a-1];for(let x=a-3;x>=0;--x)s[x]=s[x+1]*u[x+1];const g=["r","c","d"],y=s.map((x,E)=>`int ${g[E]} = index / ${x}; ${E===s.length-1?`int ${g[E+1]} = index - ${g[E]} * ${x}`:`index -= ${g[E]} * ${x}`};`).join("");return e=`
+        ivec3 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${n[0]}, ${n[1]}));
+          int index = resTexRC.y * ${n[0]} + resTexRC.x;
+          ${y}
+          return ivec3(r, c, d);
+        }
+      `,new p.GlslLibRoutine(e)}getOutputUnpacked4DCoords(u,n){let e="";const a=u.length;let s=null;a<2&&(s=[]),s=new Array(a-1),s[a-2]=u[a-1];for(let x=a-3;x>=0;--x)s[x]=s[x+1]*u[x+1];const g=["r","c","d","d2"],y=s.map((x,E)=>`int ${g[E]} = index / ${x}; ${E===s.length-1?`int ${g[E+1]} = index - ${g[E]} * ${x}`:`index -= ${g[E]} * ${x}`};`).join("");return e=`
+      ivec4 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${n[0]}, ${n[1]}));
+          int index = resTexRC.y * ${n[0]} + resTexRC.x;
+          ${y}
+          return ivec4(r, c, d, d2);
+        }
+      `,new p.GlslLibRoutine(e)}getOutputUnpacked5DCoords(u,n){let e="";const a=u.length;let s=null;a<2&&(s=[]),s=new Array(a-1),s[a-2]=u[a-1];for(let x=a-3;x>=0;--x)s[x]=s[x+1]*u[x+1];const g=["r","c","d","d2","d3"],y=s.map((x,E)=>`int ${g[E]} = index / ${x}; ${E===s.length-1?`int ${g[E+1]} = index - ${g[E]} * ${x}`:`index -= ${g[E]} * ${x}`};`).join("");return e=`
+      ivec5 getOutputCoords() {
+          ivec2 resTexRC = ivec2(TexCoords.xy *
+                                vec2(${n[0]}, ${n[1]}));
+          int index = resTexRC.y * ${n[0]} + resTexRC.x;
+          ${y}
+          return ivec5(r, c, d, d2, d3);
+        }
+      `,new p.GlslLibRoutine(e)}getOutputUnpacked6DCoords(u,n){let e="";const a=u.length;let s=null;a<2&&(s=[]),s=new Array(a-1),s[a-2]=u[a-1];for(let x=a-3;x>=0;--x)s[x]=s[x+1]*u[x+1];const g=["r","c","d","d2","d3","d4"],y=s.map((x,E)=>`int ${g[E]} = index / ${x}; ${E===s.length-1?`int ${g[E+1]} = index - ${g[E]} * ${x}`:`index -= ${g[E]} * ${x}`};`).join("");return e=`
+     ivec6 getOutputCoords() {
+         ivec2 resTexRC = ivec2(TexCoords.xy *
+                               vec2(${n[0]}, ${n[1]}));
+         int index = resTexRC.y * ${n[0]} + resTexRC.x;
+         ${y}
+         return ivec6(r, c, d, d2, d3, d4);
+       }
+     `,new p.GlslLibRoutine(e)}getCommonUtilFuncs(){const u={};let n="uvFromFlat";u[n]=new p.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",u[n]=new p.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",u[n]=new p.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",u[n]=new p.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,b.getGlsl)(this.context.glContext.version);return u[n]=new p.GlslLibRoutine(`
+        float sampleTexture(sampler2D textureSampler, vec2 uv) {
+            return ${e.texture2D}(textureSampler, uv).r;
+        }`),u}getInputsSamplingSnippets(){const u={},n=this.context.outputTextureLayout;return this.context.programInfo.inputNames.forEach((e,a)=>{const s=this.context.inputTextureLayouts[a],g=(0,m.generateShaderFuncNameFromInputSamplerName)(e);s.isPacked?u[g]=this.getPackedSamplerFromInput(g,e,s):u[g]=this.getUnpackedSamplerFromInput(g,e,s);const y=(0,m.generateShaderFuncNameFromInputSamplerNameAtOutCoords)(e);s.unpackedShape.length<=n.unpackedShape.length&&(s.isPacked?u[y]=this.getPackedSamplerAtOutputCoords(y,s,n,e):u[y]=this.getUnpackedSamplerAtOutputCoords(y,s,n,e))}),u}getPackedSamplerAtOutputCoords(u,n,e,a){const s=n.unpackedShape,g=e.unpackedShape,y=a,x=(0,m.generateShaderFuncNameFromInputSamplerName)(y),E=s.length,S=g.length,P=l.BroadcastUtil.getBroadcastDims(s,g),O=(0,m.getCoordsDataType)(S),k=S-E;let D;const C=(0,m.getGlChannels)();D=E===0?"":S<2&&P.length>=1?"coords = 0;":P.map(q=>`coords.${C[q+k]} = 0;`).join(`
+`);let A="";A=S<2&&E>0?"coords":s.map((q,se)=>`coords.${C[se+k]}`).join(", ");let $="return outputValue;";const W=l.ShapeUtil.size(s)===1,K=l.ShapeUtil.size(g)===1;if(E!==1||W||K){if(W&&!K)$=S===1?`
+          return vec4(outputValue.x, outputValue.x, 0., 0.);
+        `:`
+          return vec4(outputValue.x);
+        `;else if(P.length){const q=E-2,se=E-1;P.indexOf(q)>-1&&P.indexOf(se)>-1?$="return vec4(outputValue.x);":P.indexOf(q)>-1?$="return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);":P.indexOf(se)>-1&&($="return vec4(outputValue.xx, outputValue.zz);")}}else $=`
+        return vec4(outputValue.xy, outputValue.xy);
+      `;const Y=`
+      vec4 ${u}() {
+        ${O} coords = getOutputCoords();
+        
+        int lastDim = coords.${C[S-1]};
+        coords.${C[S-1]} = coords.${C[S-2]};
+        coords.${C[S-2]} = lastDim;
+      
+        ${D}
+        vec4 outputValue = ${x}(${A});
+        ${$}
+      }
+    `;return new p.GlslLibRoutine(Y,["coordinates.getOutputCoords"])}getUnpackedSamplerAtOutputCoords(u,n,e,a){const s=[e.width,e.height],g=[n.width,n.height],y=n.unpackedShape.length,x=e.unpackedShape.length,E=n.unpackedShape,S=e.unpackedShape,P=(0,m.generateShaderFuncNameFromInputSamplerName)(a);if(y===x&&l.ArrayUtil.arraysEqual(g,s)){const K=`
+          float ${u}() {
+            return sampleTexture(${a}, TexCoords);
+          }
+        `;return new p.GlslLibRoutine(K,["coordinates.sampleTexture"])}const O=(0,m.getCoordsDataType)(x),k=l.BroadcastUtil.getBroadcastDims(E,S),D=x-y;let C;const A=(0,m.getGlChannels)();C=y===0?"":x<2&&k.length>=1?"coords = 0;":k.map(K=>`coords.${A[K+D]} = 0;`).join(`
+`);let $="";$=x<2&&y>0?"coords":n.unpackedShape.map((K,Y)=>`coords.${A[Y+D]}`).join(", ");const W=`
+        float ${u}() {
+          ${O} coords = getOutputCoords();
+          ${C}
+          return ${P}(${$});
+        }
+      `;return new p.GlslLibRoutine(W,["coordinates.getOutputCoords"])}getPackedSamplerFromInput(u,n,e){switch(e.unpackedShape.length){case 0:return this.getPackedSamplerScalar(u,n);case 1:return this.getPackedSampler1D(u,n,e);case 2:return this.getPackedSampler2D(u,n,e);case 3:return this.getPackedSampler3D(u,n,e);default:return this.getPackedSamplerND(u,n,e)}}getUnpackedSamplerFromInput(u,n,e){const a=e.unpackedShape;switch(a.length){case 0:return this.getUnpackedSamplerScalar(u,n,e);case 1:return this.getUnpackedSampler1D(u,n,e);case 2:return this.getUnpackedSampler2D(u,n,e);case 3:return this.getUnpackedSampler3D(u,n,e);case 4:return this.getUnpackedSampler4D(u,n,e);case 5:return this.getUnpackedSampler5D(u,n,e);case 6:return this.getUnpackedSampler6D(u,n,e);default:throw new Error(`Unsupported dimension ${a.length}-D`)}}getPackedSamplerScalar(u,n){const e=`
+          vec4 ${u}() {
+            return ${(0,b.getGlsl)(this.context.glContext.version).texture2D}(${n}, halfCR);
+          }
+        `;return new p.GlslLibRoutine(e)}getPackedSampler1D(u,n,e){const a=[e.width,e.height],s=[a[1],a[0]],g=(0,b.getGlsl)(this.context.glContext.version),y=`vec4 ${u}(int index) {
+      vec2 uv = packedUVfrom1D(
+      ${s[0]}, ${s[1]}, index);
+      return ${g.texture2D}(${n}, uv);
+    }`;return new p.GlslLibRoutine(y,["coordinates.packedUVfrom1D"])}getPackedSampler2D(u,n,e){const a=e.unpackedShape,s=[e.width,e.height],g=(0,b.getGlsl)(this.context.glContext.version),y=s[0],x=s[1];if(s!=null&&l.ArrayUtil.arraysEqual(a,s)){const O=`vec4 ${u}(int row, int col) {
+        vec2 uv = (vec2(col, row) + halfCR) / vec2(${x}.0, ${y}.0);
+        return ${g.texture2D}(${n}, uv);
+      }`;return new p.GlslLibRoutine(O)}const E=s,S=Math.ceil(a[1]/2),P=`vec4 ${u}(int row, int col) {
+      vec2 uv = packedUVfrom2D(${E[1]}, ${E[0]}, ${S}, row, col);
+      return ${g.texture2D}(${n}, uv);
+    }`;return new p.GlslLibRoutine(P,["coordinates.packedUVfrom2D"])}getPackedSampler3D(u,n,e){const a=e.unpackedShape,s=[e.width,e.height],g=[s[0],s[1]],y=(0,b.getGlsl)(this.context.glContext.version);if(a[0]===1){const O=a.slice(1),k=[1,2],D=(0,m.squeezeInputShape)(a,O),C=["b","row","col"],A=JSON.parse(JSON.stringify(e));A.unpackedShape=D;const $=this.getPackedSamplerFromInput(u,n,A),W=`${$.routineBody}
+      vec4 ${u}(int b, int row, int col) {
+        return ${u}(${(0,m.getSqueezedParams)(C,k)});
+      } `;return new p.GlslLibRoutine(W,$.dependencies)}const x=g[0],E=g[1],S=Math.ceil(a[2]/2),P=`vec4 ${u}(int b, int row, int col) {
+      vec2 uv = packedUVfrom3D(
+        ${E}, ${x}, ${S*Math.ceil(a[1]/2)}, ${S}, b, row, col);
+      return ${y.texture2D}(${n}, uv);}`;return new p.GlslLibRoutine(P,["coordinates.packedUVfrom3D"])}getPackedSamplerND(u,n,e){const a=e.unpackedShape,s=a.length,g=[e.width,e.height],y=(0,b.getGlsl)(this.context.glContext.version),x=[g[0],g[1]],E=x[1],S=x[0],P=Math.ceil(a[s-1]/2);let O=P*Math.ceil(a[s-2]/2),k="int b, int row, int col",D=`b * ${O} + (row / 2) * ${P} + (col / 2)`;for(let A=2;A<s-1;A++)k=`int b${A}, `+k,O*=a[s-A-1],D=`b${A} * ${O} + `+D;const C=`vec4 ${u}(${k}) {
+      int index = ${D};
+      int texR = index / ${S};
+      int texC = index - texR * ${S};
+      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${S}, ${E});
+      return ${y.texture2D}(${n}, uv);
+    }`;return new p.GlslLibRoutine(C)}getUnpackedSamplerScalar(u,n,e){const[a,s]=[e.width,e.height];if(a===1&&s===1){const y=`
+          float ${u}() {
+            return sampleTexture(${n}, halfCR);
+          }
+        `;return new p.GlslLibRoutine(y,["coordinates.sampleTexture"])}const g=`
+        float ${u}() {
+          int offset_${n} = coordsToOffset(TexCoords, ${a}, ${s});
+          vec2 uv = uvFromFlat(${a}, ${s}, offset_${n});
+          return sampleTexture(${n}, uv);
+        }
+      `;return new p.GlslLibRoutine(g,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler1D(u,n,e){const a=e.width,s=e.height;if(s===1&&a===1){const y=`
+        float ${u}(int index) {
+          return sampleTexture(${n}, halfCR);
+        }
+      `;return new p.GlslLibRoutine(y,["coordinates.sampleTexture"])}if(s===1){const y=`
+          float ${u}(int index) {
+            vec2 uv = vec2((float(index) + 0.5) / ${a}.0, 0.5);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(y,["coordinates.sampleTexture"])}if(a===1){const y=`
+          float ${u}(int index) {
+            vec2 uv = vec2(0.5, (float(index) + 0.5) / ${s}.0);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(y,["coordinates.sampleTexture"])}const g=`
+        float ${u}(int index) {
+          vec2 uv = uvFromFlat(${a}, ${s}, index);
+          return sampleTexture(${n}, uv);
+        }
+      `;return new p.GlslLibRoutine(g,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler2D(u,n,e){const a=e.unpackedShape,s=[e.height,e.width];if(s!=null&&l.ArrayUtil.arraysEqual(a,s)){const O=`
+          float ${u}(int row, int col) {
+            vec2 uv = (vec2(row, col) + halfCR) / vec2(${s[1]}.0, ${s[0]}.0);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(O,["coordinates.sampleTexture"])}const{newShape:g,keptDims:y}=(0,c.squeezeShape)(a),x=g;if(x.length<a.length){const O=(0,m.squeezeInputShape)(a,x),k=JSON.parse(JSON.stringify(e));k.unpackedShape=O;const D=["col","row"],C=`
+          ${this.getUnpackedSamplerFromInput(u,n,k).routineBody}
+          float ${u}(int row, int col) {
+            return ${u}(${(0,m.getSqueezedParams)(D,y)});
+          }
+        `;return new p.GlslLibRoutine(C,["coordinates.sampleTexture"])}const E=s[1],S=s[0];if(S===1){const O=`
+          float ${u}(int row, int col) {
+            int offset_${n} = coordsToOffset(TexCoords, ${E}, ${S});
+            float index = dot(vec3(row, col, offset_${n}), vec3(${a[1]}, 1, 1));
+            vec2 uv = vec2(0.5, (index + 0.5) / ${E}.0);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(O,["coordinates.sampleTexture","coordinates.coordsToOffset"])}if(E===1){const O=`
+          float ${u}(int row, int col) {
+            int offset_${n} = coordsToOffset(TexCoords, ${E}, ${S});
+            float index = dot(vec3(row, col, offset_${n}), vec3(${a[1]}, 1, 1));
+            vec2 uv = vec2((index + 0.5) / ${S}.0, 0.5);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(O,["coordinates.sampleTexture","coordinates.coordsToOffset"])}const P=`
+        float ${u}(int row, int col) {
+          int index = col * ${a[1]} + row;
+          vec2 uv = uvFromFlat(${E}, ${S}, index);
+          return sampleTexture(${n}, uv);
+        }
+      `;return new p.GlslLibRoutine(P,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler3D(u,n,e){const a=e.unpackedShape,s=a[1]*a[2],g=a[2],{newShape:y,keptDims:x}=(0,c.squeezeShape)(a),E=y;if(E.length<a.length){const P=(0,m.squeezeInputShape)(a,E),O=["batch","col","row"],k=JSON.parse(JSON.stringify(e));k.unpackedShape=P;const D=this.getUnpackedSamplerFromInput(u,n,k),C=x.reverse(),A=`
+          ${D.routineBody}
+          float ${u}(int batch, int row, int col) {
+            return ${u}(${(0,m.getSqueezedParams)(O,C)});
+          }
+        `;return new p.GlslLibRoutine(A,D.dependencies)}const S=`
+          float ${u}(int depth, int row, int col) {
+            // Explicitly use integer operations as dot() only works on floats.
+            int index = depth * ${s} + col * ${g} + row;
+            vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
+            return sampleTexture(${n}, uv);
+          }
+      `;return new p.GlslLibRoutine(S,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}getUnpackedSampler4D(u,n,e){const a=e.unpackedShape,s=a[3],g=a[2]*s,y=`
+        float ${u}(int row, int col, int depth, int depth2) {
+          int index = row * ${a[1]*g} + col * ${g} +
+              depth2 * ${s} + depth;
+          vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
+          return sampleTexture(${n}, uv);
+        }
+      `;return new p.GlslLibRoutine(y,["coordinates.uvFromFlat","coordinates.sampleTexture"])}getUnpackedSampler5D(u,n,e){const a=e.unpackedShape,s=a[4],g=a[3]*s,y=a[2]*g,x=a[1]*y,{newShape:E,keptDims:S}=(0,c.squeezeShape)(a);if(E.length<a.length){const O=(0,m.squeezeInputShape)(a,E),k=["row","col","depth","depth2","depth3"],D=JSON.parse(JSON.stringify(e));D.unpackedShape=O;const C=`
+          ${this.getUnpackedSamplerFromInput(u,n,D).routineBody}
+          float ${u}(int row, int col, int depth, int depth2, int depth3) {
+            return ${u}(${(0,m.getSqueezedParams)(k,S)});
+          }
+        `;return new p.GlslLibRoutine(C,["coordinates.sampleTexture","coordinates.uvFromFlat"])}const P=`
+        float ${u}(int row, int col, int depth, int depth2, int depth3) {
+          int index = row * ${x} + col * ${y} + depth * ${g} +
+          depth3 * ${s} + depth2;
+          vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
+          return sampleTexture(${n}, uv);
+        }
+      `;return new p.GlslLibRoutine(P,["coordinates.sampleTexture","coordinates.uvFromFlat"])}getUnpackedSampler6D(u,n,e){const a=e.unpackedShape,s=a[5],g=a[4]*s,y=a[3]*g,x=a[2]*y,E=a[1]*x,{newShape:S,keptDims:P}=(0,c.squeezeShape)(a);if(S.length<a.length){const k=(0,m.squeezeInputShape)(a,S),D=["row","col","depth","depth2","depth3","depth4"],C=JSON.parse(JSON.stringify(e));C.unpackedShape=k;const A=`
+            ${this.getUnpackedSamplerFromInput(u,n,C).routineBody}
+            float ${u}(int row, int col, int depth,
+              int depth2, int depth3, int depth4) {
+              return ${u}(${(0,m.getSqueezedParams)(D,P)});
+            }
+          `;return new p.GlslLibRoutine(A,["coordinates.sampleTexture","coordinates.uvFromFlat"])}const O=`
+          float ${u}(int row, int col, int depth,
+            int depth2, int depth3, int depth4) {
+            int index = row * ${E} + col * ${x} + depth * ${y} +
+            depth2 * ${g} + depth3 * ${s} + depth4;
+            vec2 uv = uvFromFlat(${e.width}, ${e.height}, index);
+            return sampleTexture(${n}, uv);
+          }
+        `;return new p.GlslLibRoutine(O,["coordinates.uvFromFlat","coordinates.sampleTexture","coordinates.coordsToOffset"])}toVec(){const u=this.context.outputTextureLayout,n=u.shape.length,e=u.strides,a=u.width,s=u.height,g=[];for(let x=0;x<n-1;++x)g.push(`
+        c[${x}] = offset / ${e[x]};`),g.push(`
+        offset -= c[${x}] * ${e[x]};`);g.push(`
+        c[${n-1}] = offset;`);const y=`
+      void toVec(vec2 texCoords, out int c[${n}]) {
+        int offset = coordsToOffset(texCoords, ${a}, ${s});
+        ${g.join("")}
+      }
+      void toVec(int offset, out int c[${n}]) {
+        ${g.join("")}
+      }
+    `;return{toVec:new p.GlslLibRoutine(y,["coordinates.coordsToOffset"])}}valueFrom(){const u={};return this.context.programInfo.inputNames.forEach((n,e)=>{const a=this.context.inputTextureLayouts[e],s=(a.unpackedShape.length>0?a.unpackedShape:a.shape).length;let g=`_${n}`;u[g]=new p.GlslLibRoutine(this.getValueFromSingle(n,s,a.width,a.height,!1),[`shapeUtils.indicesToOffset${g}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"]),g+="_T",u[g]=new p.GlslLibRoutine(this.getValueFromSingle(n,s,a.width,a.height,!0),[`shapeUtils.indicesToOffset${g}`,"coordinates.offsetToCoords","fragcolor.getColorAsFloat"])}),u}getValueFromSingle(u,n,e,a,s){let g=`_${u}`;return s&&(g+="_T"),`
+        float ${g}(int m[${n}]) {
+          int offset = indicesToOffset${g}(m);
+          vec2 coords = offsetToCoords(offset, ${e}, ${a});
+          float value = getColorAsFloat(${(0,b.getGlsl)(this.context.glContext.version).texture2D}(${u}, coords));
+          return value;
+        }
+        `}getPackedValueFrom(u,n,e,a,s){let g=`_${u}_Pack`;return s&&(g+="_T"),`
+        vec4 ${g}(int m[${n}]) {
+          int offset = indicesToOffset_${u}(m);
+          vec2 coords = offsetToCoords(offset, ${e}, ${a});
+          return ${(0,b.getGlsl)(this.context.glContext.version).texture2D}(${u}, coords);
+        }
+        `}}o.CoordsGlslLib=_},8520:(v,o)=>{var d;Object.defineProperty(o,"__esModule",{value:!0}),o.TopologicalSortGlslRoutines=o.GlslLibRoutineNode=o.GlslLibRoutine=o.GlslLib=o.GlslContext=o.FunctionType=void 0,(d=o.FunctionType||(o.FunctionType={}))[d.ValueBased=0]="ValueBased",d[d.Positional=1]="Positional",o.GlslContext=class{constructor(l,p,b,c){this.glContext=l,this.programInfo=p,this.inputTextureLayouts=b,this.outputTextureLayout=c}},o.GlslLib=class{constructor(l){this.context=l}},o.GlslLibRoutine=class{constructor(l,p){this.routineBody=l,this.dependencies=p}},o.GlslLibRoutineNode=class{constructor(l,p,b){this.name=l,this.dependencies=b||[],p&&(this.routineBody=p)}addDependency(l){l&&this.dependencies.push(l)}},o.TopologicalSortGlslRoutines=class{static returnOrderedNodes(l){if(!l||l.length===0)return[];if(l.length===1)return l;const p=new Set,b=new Set,c=new Array;return this.createOrderedNodes(l,p,b,c),c}static createOrderedNodes(l,p,b,c){for(let m=0;m<l.length;++m)this.dfsTraverse(l[m],p,b,c)}static dfsTraverse(l,p,b,c){if(!l||b.has(l.name))return;if(p.has(l.name))throw new Error("Cyclic dependency detected. Can't topologically sort routines needed for shader.");p.add(l.name);const m=l.dependencies;if(m&&m.length>0)for(let _=0;_<m.length;++_)this.dfsTraverse(m[_],p,b,c);c.push(l),b.add(l.name),p.delete(l.name)}}},7341:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.EncodingGlslLib=void 0;const l=d(8520);class p extends l.GlslLib{constructor(c){super(c)}getFunctions(){return Object.assign(Object.assign({},this.encodeFloat32()),this.decodeFloat32())}getCustomTypes(){return{}}encodeFloat32(){return{encode:new l.GlslLibRoutine(`highp vec4 encode(highp float f) {
+        return vec4(f, 0.0, 0.0, 0.0);
+      }
+        `)}}decodeFloat32(){return{decode:new l.GlslLibRoutine(`highp float decode(highp vec4 rgba) {
+        return rgba.r;
+      }
+        `)}}encodeUint8(){const c=p.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{encode:new l.GlslLibRoutine(`
+      highp vec4 encode(highp float f) {
+        highp float F = abs(f);
+        highp float Sign = step(0.0,-f);
+        highp float Exponent = floor(log2(F));
+        highp float Mantissa = (exp2(- Exponent) * F);
+        Exponent = floor(log2(F) + 127.0) + floor(log2(Mantissa));
+        highp vec4 rgba;
+        rgba[0] = 128.0 * Sign  + floor(Exponent*exp2(-1.0));
+        rgba[1] = 128.0 * mod(Exponent,2.0) + mod(floor(Mantissa*128.0),128.0);
+        rgba[2] = floor(mod(floor(Mantissa*exp2(23.0 -8.0)),exp2(8.0)));
+        rgba[3] = floor(exp2(23.0)*mod(Mantissa,exp2(-15.0)));
+        ${c}
+        rgba = rgba / 255.0; // values need to be normalized to [0,1]
+        return rgba;
+    }
+        `)}}decodeUint8(){const c=p.isLittleEndian()?"rgba.rgba=rgba.abgr;":"";return{decode:new l.GlslLibRoutine(`
+        highp float decode(highp vec4 rgba) {
+          rgba = rgba * 255.0; // values need to be de-normalized from [0,1] to [0,255]
+          ${c}
+          highp float Sign = 1.0 - step(128.0,rgba[0])*2.0;
+          highp float Exponent = 2.0 * mod(rgba[0],128.0) + step(128.0,rgba[1]) - 127.0;
+          highp float Mantissa = mod(rgba[1],128.0)*65536.0 + rgba[2]*256.0 +rgba[3] + float(0x800000);
+          highp float Result =  Sign * exp2(Exponent) * (Mantissa * exp2(-23.0 ));
+          return Result;
+      }
+        `)}}static isLittleEndian(){const c=new ArrayBuffer(4),m=new Uint32Array(c),_=new Uint8Array(c);if(m[0]=3735928559,_[0]===239)return!0;if(_[0]===222)return!1;throw new Error("unknown endianness")}}o.EncodingGlslLib=p},9894:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.FragColorGlslLib=void 0;const l=d(8520),p=d(5060);class b extends l.GlslLib{constructor(m){super(m)}getFunctions(){return Object.assign(Object.assign({},this.setFragColor()),this.getColorAsFloat())}getCustomTypes(){return{}}setFragColor(){const m=(0,p.getGlsl)(this.context.glContext.version);return{setFragColor:new l.GlslLibRoutine(`
+        void setFragColor(float value) {
+            ${m.output} = encode(value);
+        }
+        `,["encoding.encode"])}}getColorAsFloat(){return{getColorAsFloat:new l.GlslLibRoutine(`
+        float getColorAsFloat(vec4 color) {
+            return decode(color);
+        }
+        `,["encoding.decode"])}}}o.FragColorGlslLib=b},2848:(v,o)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.replaceInlines=void 0;const d=/@inline[\s\n\r]+(\w+)[\s\n\r]+([0-9a-zA-Z_]+)\s*\(([^)]*)\)\s*{(([^}]|[\n\r])*)}/gm;o.replaceInlines=function(l){const p={};let b;for(;(b=d.exec(l))!==null;){const c=b[3].split(",").map(m=>{const _=m.trim().split(" ");return _&&_.length===2?{type:_[0],name:_[1]}:null}).filter(m=>m!==null);p[b[2]]={params:c,body:b[4]}}for(const c in p){const m="(\\w+)?\\s+([_0-9a-zA-Z]+)\\s+=\\s+__FUNC__\\((.*)\\)\\s*;".replace("__FUNC__",c),_=new RegExp(m,"gm");for(;(b=_.exec(l))!==null;){const f=b[1],u=b[2],n=b[3].split(","),e=f?`${f} ${u};`:"";let a=p[c].body,s="";p[c].params.forEach((y,x)=>{y&&(s+=`${y.type} ${y.name} = ${n[x]};
+`)}),a=`${s}
+ ${a}`,a=a.replace("return",`${u} = `);const g=`
+      ${e}
+      {
+        ${a}
+      }
+      `;l=l.replace(b[0],g)}}return l.replace(d,"")}},8879:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.GlslPreprocessor=void 0;const l=d(8520),p=d(2848),b=d(5483),c=d(5060);o.GlslPreprocessor=class{constructor(m,_,f,u){this.libs={},this.glslLibRoutineDependencyGraph={},this.context=new l.GlslContext(m,_,f,u),Object.keys(b.glslRegistry).forEach(e=>{const a=new b.glslRegistry[e](this.context);this.libs[e]=a});const n=this.glslLibRoutineDependencyGraph;for(const e in this.libs){const a=this.libs[e].getFunctions();for(const s in a){const g=e+"."+s;let y;n[g]?(y=n[g],y.routineBody=a[s].routineBody):(y=new l.GlslLibRoutineNode(g,a[s].routineBody),n[g]=y);const x=a[s].dependencies;if(x)for(let E=0;E<x.length;++E)if(n[x[E]])y.addDependency(n[x[E]]);else{const S=new l.GlslLibRoutineNode(x[E]);n[x[E]]=S,y.addDependency(S)}}}}preprocess(){const m=this.context.programInfo;let _=m.shaderSource;return this.context.programInfo.hasMain||(_=`${_}
+      ${(0,c.getDefaultFragShaderMain)(this.context.glContext.version,this.context.outputTextureLayout.shape.length)}`),_=(0,p.replaceInlines)(_),`${(0,c.getFragShaderPreamble)(this.context.glContext.version)}
+    ${this.getUniforms(m.inputNames,m.variables)}
+    ${this.getImports(_)}
+    ${_}`}getImports(m){const _=this.selectGlslLibRoutinesToBeIncluded(m);if(_.length===0)return"";let f="";for(let u=0;u<_.length;++u){if(!_[u].routineBody)throw new Error(`Missing body for the Glsl Library routine: ${_[u].name}`);f+=_[u].routineBody+`
+`}return f}selectGlslLibRoutinesToBeIncluded(m){const _=[];return Object.keys(this.glslLibRoutineDependencyGraph).forEach(f=>{const u=f.split(".")[1];m.indexOf(u)!==-1&&_.push(this.glslLibRoutineDependencyGraph[f])}),l.TopologicalSortGlslRoutines.returnOrderedNodes(_)}getUniforms(m,_){const f=[];if(m)for(const u of m)f.push(`uniform sampler2D ${u};`);if(_)for(const u of _)f.push(`uniform ${u.type} ${u.name}${u.arrayLength?`[${u.arrayLength}]`:""};`);return f.join(`
+`)}}},5483:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.glslRegistry=void 0;const l=d(5107),p=d(7341),b=d(9894),c=d(2655),m=d(3891);o.glslRegistry={encoding:p.EncodingGlslLib,fragcolor:b.FragColorGlslLib,vec:m.VecGlslLib,shapeUtils:c.ShapeUtilsGlslLib,coordinates:l.CoordsGlslLib}},2655:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.ShapeUtilsGlslLib=void 0;const l=d(8520);class p extends l.GlslLib{constructor(c){super(c)}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign(Object.assign({},this.bcastIndex()),this.bcastMatmulIndex()),this.offsetToIndices()),this.indicesToOffset()),this.incrementIndices())}getCustomTypes(){return{}}bcastIndex(){const c=this.context.outputTextureLayout.shape.length,m={};return this.context.programInfo.inputNames.forEach((_,f)=>{const u=this.context.inputTextureLayouts[f].unpackedShape;if(u.length<=c){const n=u.length,e=c-n,a=`bcastIndices_${_}`;let s="";for(let y=0;y<n;++y)s+=`
+          realIndices[${y}] = int( mod(float(bcastedIndices[${e+y}]), ${u[y]}.0) );
+          `;const g=`
+        void ${a} (int bcastedIndices[${c}], out int realIndices[${n}]) {
+          ${s}
+        }
+        `;m[a]=new l.GlslLibRoutine(g)}}),m}bcastMatmulIndex(){const c=this.context.outputTextureLayout.shape.length,m={};return this.context.programInfo.inputNames.forEach((_,f)=>{const u=this.context.inputTextureLayouts[f].shape;if(!(u.length<2||u.length>c)){const n=u.length,e=c-n,a=`bcastMatmulIndices_${_}`;let s="";for(let y=0;y<n-2;++y)s+=`
+          realIndices[${y}] = int( mod(float(bcastedIndices[${e+y}]), ${u[y]}.0) );
+          `;const g=`
+        void ${a}(int bcastedIndices[${c}], out int realIndices[${n}]) {
+          ${s}
+          realIndices[${n-1}] = bcastedIndices[${c-1}];
+          realIndices[${n-2}] = bcastedIndices[${c-2}];
+        }
+        `;m[a]=new l.GlslLibRoutine(g)}}),m}indicesToOffset(){const c={};return this.context.programInfo.inputNames.forEach((m,_)=>{const f=this.context.inputTextureLayouts[_].shape,u=this.context.inputTextureLayouts[_].strides,n=f.length;let e=`indicesToOffset_${m}`;c[e]=new l.GlslLibRoutine(p.indexToOffsetSingle(e,n,u)),e=`indicesToOffset_${m}_T`,c[e]=new l.GlslLibRoutine(p.indexToOffsetSingle(e,n,u.slice().reverse()))}),c}static indexToOffsetSingle(c,m,_){let f="";for(let u=m-1;u>=0;--u)f+=`
+        offset += indices[${u}] * ${_[u]};
+        `;return`
+      int ${c}(int indices[${m}]) {
+        int offset = 0;
+        ${f}
+        return offset;
+      }
+      `}offsetToIndices(){const c={};return this.context.programInfo.inputNames.forEach((m,_)=>{const f=this.context.inputTextureLayouts[_].shape,u=this.context.inputTextureLayouts[_].strides,n=f.length;let e=`offsetToIndices_${m}`;c[e]=new l.GlslLibRoutine(p.offsetToIndicesSingle(e,n,u)),e=`offsetToIndices_${m}_T`,c[e]=new l.GlslLibRoutine(p.offsetToIndicesSingle(e,n,u.slice().reverse()))}),c}static offsetToIndicesSingle(c,m,_){const f=[];for(let u=0;u<m-1;++u)f.push(`
+      indices[${u}] = offset / ${_[u]};`),f.push(`
+        offset -= indices[${u}] * ${_[u]};`);return f.push(`
+      indices[${m-1}] = offset;`),`
+      void ${c}(int offset, out int indices[${m}]) {
+        ${f.join("")}
+      }
+      `}incrementIndices(){const c={};return this.context.programInfo.inputNames.forEach((m,_)=>{const f=this.context.inputTextureLayouts[_].shape,u=f.length,n=`incrementIndices_${m}`;let e="";for(let s=0;s<u;++s)e+=`
+        shape[${s}] = ${f[s]};`;const a=`
+        void ${n}(int axis, out int indices[${u}]) {
+          int shape[${u}];
+          ${e};
+          for(int i = ${u} -1 ; i >= 0; --i) {
+            if(i > axis) continue;
+            indices[i] += 1;
+            if(indices[i] < shape[i]) {
+              break;
+            }
+            indices[i] = 0;
+          }
+        }
+        `;c[n]=new l.GlslLibRoutine(a)}),c}}o.ShapeUtilsGlslLib=p},5060:(v,o)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.getDefaultFragShaderMain=o.getFragShaderPreamble=o.getVertexShaderSource=o.getGlsl=void 0;const d={version:"",attribute:"attribute",varyingVertex:"varying",varyingFrag:"varying",texture2D:"texture2D",output:"gl_FragColor",outputDeclaration:""},l={version:"#version 300 es",attribute:"in",varyingVertex:"out",varyingFrag:"in",texture2D:"texture",output:"outputColor",outputDeclaration:"out vec4 outputColor;"};function p(b){return b===1?d:l}o.getGlsl=p,o.getVertexShaderSource=function(b){const c=p(b);return`${c.version}
+      precision highp float;
+      ${c.attribute} vec3 position;
+      ${c.attribute} vec2 textureCoord;
+
+      ${c.varyingVertex} vec2 TexCoords;
+
+      void main()
+      {
+          gl_Position = vec4(position, 1.0);
+          TexCoords = textureCoord;
+      }`},o.getFragShaderPreamble=function(b){const c=p(b);return`${c.version}
+    precision highp float;
+    precision highp int;
+    precision highp sampler2D;
+    ${c.varyingFrag} vec2 TexCoords;
+    ${c.outputDeclaration}
+    const vec2 halfCR = vec2(0.5, 0.5);
+
+    // Custom vector types to handle higher dimenalities.
+    struct ivec5
+    {
+      int x;
+      int y;
+      int z;
+      int w;
+      int u;
+    };
+
+    struct ivec6
+    {
+      int x;
+      int y;
+      int z;
+      int w;
+      int u;
+      int v;
+    };
+
+    int imod(int x, int y) {
+      return x - y * (x / y);
+    }
+
+    `},o.getDefaultFragShaderMain=function(b,c){return`
+  void main() {
+    int indices[${c}];
+    toVec(TexCoords, indices);
+    vec4 result = vec4(process(indices));
+    ${p(b).output} = result;
+  }
+  `}},3891:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.VecGlslLib=void 0;const l=d(8520);class p extends l.GlslLib{constructor(c){super(c)}getCustomTypes(){return{}}getFunctions(){return Object.assign(Object.assign(Object.assign(Object.assign({},this.binaryVecFunctions()),this.copyVec()),this.setVecItem()),this.getVecItem())}binaryVecFunctions(){const c=this.context.outputTextureLayout.shape.length,m={add:"+=",sub:"-=",mul:"*=",div:"/="},_={};for(const f in m){const u=`${f}Vec`;let n="";for(let a=0;a<c;++a)n+=`
+          dest[${a}] ${m[f]} src[${a}];
+          `;const e=`
+        void ${u}(int src[${c}], out int dest[${c}]) {
+          ${n}
+        }
+        `;_[u]=new l.GlslLibRoutine(e)}return _}copyVec(){const c=this.context.outputTextureLayout.shape.length;let m="";for(let f=0;f<c;++f)m+=`
+        dest[${f}] = src[${f}];
+        `;const _=`
+      void copyVec(int src[${c}], out int dest[${c}]) {
+        ${m}
+      }
+      `;return{copyVec:new l.GlslLibRoutine(_)}}setVecItem(){const c=this.context.outputTextureLayout.shape.length;let m=`
+        if(index < 0)
+            index =${c} + index;
+        if (index == 0)
+            m[0] = value;
+        `;for(let f=1;f<c-1;++f)m+=`
+        else if (index == ${f})
+            m[${f}] = value;
+            `;m+=`
+        else
+            m[${c-1}] = value;
+        `;const _=`
+      void setVecItem(out int m[${c}], int index, int value) {
+        ${m}
+      }
+        `;return{setVecItem:new l.GlslLibRoutine(_)}}getVecItem(){const c=this.context.outputTextureLayout.shape.length;let m=`
+        if(index < 0)
+            index = ${c} + index;
+        if (index == 0)
+            return m[0];
+      `;for(let f=1;f<c-1;++f)m+=`
+        else if (index == ${f})
+            return m[${f}];
+      `;m+=`
+        else
+            return m[${c-1}];
+        `;const _=`
+      int getVecItem(int m[${c}], int index) {
+        ${m}
+      }
+    `;return{getVecItem:new l.GlslLibRoutine(_)}}}o.VecGlslLib=p},8316:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.WebGLInferenceHandler=void 0;const l=d(6231),p=d(9162),b=d(2517),c=d(2403),m=d(7019),_=d(8710),f=d(5611),u=d(4057),n=d(2039);o.WebGLInferenceHandler=class{constructor(e){this.session=e,this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map}calculateTextureWidthAndHeight(e,a){return(0,u.calculateTextureWidthAndHeight)(this.session.layoutStrategy,e,a)}executeProgram(e,a){if(a.length<e.inputNames.length)throw new Error(`Input size mustn't be less than ${e.inputNames.length}.`);if(e.inputNames.length!==e.inputTypes.length)throw new Error("input names size does not match input types");const s=[];for(let P=0;P<e.inputNames.length;++P)s[P]=this.getOrCreateTextureData(a[P],e.inputTypes[P]);const g=((P,O)=>{const k=O.map(C=>`${C.unpackedShape.join(",")};${C.width}x${C.height}`).join("_");let D=P.name;return 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this.createTextureData(e,a,s,g,1)}createTextureData(e,a,s,g,y){l.Logger.verbose("InferenceHandler",`Creating TextureData: layout:[${JSON.stringify(e)}]`);const x=this.session.textureManager.createTextureFromLayout(a,e,s,y);return this.createTextureDataFromTexture(e,a,x,g)}reshapeUnpacked(e,a){const s=this.getOrCreateTextureData(e,n.TextureType.unpacked),g={channels:s.channels,height:s.height,width:s.width,shape:a.length!==0?a:[1],strides:b.ShapeUtil.computeStrides(a),unpackedShape:a};return this.createTextureDataFromTexture(g,e.type,s.texture).tensor}reshapePacked(e,a){const s=this.getOrCreateTextureData(e,n.TextureType.packed);if((0,m.isReshapeCheap)(e.dims,a)){const S={channels:s.channels,height:s.height,width:s.width,shape:a.length!==0?a:[1],strides:b.ShapeUtil.computeStrides(a),unpackedShape:a,isPacked:!0};return this.createTextureDataFromTexture(S,e.type,s.texture).tensor}const g=(0,m.processDims3D)(e.dims),y=(0,m.processDims3D)(a),x=this.reshapePacked(e,g),E=this.run((0,m.createPackedReshape3DProgramInfoLoader)(this,x,y),[x]);return this.reshapePacked(E,a)}cast(e,a){const s=this.getOrCreateTextureData(e,n.TextureType.unpacked);return this.createTextureDataFromTexture(s,a,s.texture).tensor}createTextureDataFromTexture(e,a,s,g,y){const x=Object.assign(Object.assign({},e),{tensor:g||new p.Tensor(e.unpackedShape,a,E=>this.readTexture(x),async E=>this.readTextureAsync(x),void 0,y),texture:s});return this.setTextureData(x.tensor.dataId,x,e.isPacked),x}getTextureData(e,a=!1){return this.session.isInitializer(e)?this.session.getTextureData(e,a):a?this.packedTextureDataCache.get(e):this.unpackedTextureDataCache.get(e)}setTextureData(e,a,s=!1){this.session.isInitializer(e)?this.session.setTextureData(e,a,s):(s?this.packedTextureDataCache:this.unpackedTextureDataCache).set(e,a)}isTextureLayoutCached(e,a=!1){return!!this.getTextureData(e.dataId,a)}dispose(){this.session.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach(e=>this.session.textureManager.releaseTexture(e)),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache.forEach(e=>this.session.textureManager.releaseTexture(e)),this.unpackedTextureDataCache=new Map}readTexture(e){return e.isPacked?this.readTexture(this.unpack(e)):this.session.backend.glContext.isFloat32DownloadSupported?this.session.textureManager.readTexture(e,e.tensor.type,e.channels):this.session.textureManager.readUint8TextureAsFloat((0,_.encodeAsUint8)(this,e))}async readTextureAsync(e){return e.isPacked?this.readTextureAsync(this.unpack(e)):this.session.backend.glContext.isFloat32DownloadSupported?this.session.textureManager.readTextureAsync(e,e.tensor.type,e.channels):this.session.textureManager.readUint8TextureAsFloat((0,_.encodeAsUint8)(this,e))}pack(e){return this.executeProgram((0,c.createPackProgramInfoLoader)(this,e.tensor),[e.tensor])}unpack(e){return this.executeProgram((0,f.createUnpackProgramInfoLoader)(this,e.tensor),[e.tensor])}}},1640:function(v,o,d){var l=this&&this.__createBinding||(Object.create?function(ne,z,Q,re){re===void 0&&(re=Q);var ue=Object.getOwnPropertyDescriptor(z,Q);ue&&!("get"in ue?!z.__esModule:ue.writable||ue.configurable)||(ue={enumerable:!0,get:function(){return z[Q]}}),Object.defineProperty(ne,re,ue)}:function(ne,z,Q,re){re===void 0&&(re=Q),ne[re]=z[Q]}),p=this&&this.__setModuleDefault||(Object.create?function(ne,z){Object.defineProperty(ne,"default",{enumerable:!0,value:z})}:function(ne,z){ne.default=z}),b=this&&this.__importStar||function(ne){if(ne&&ne.__esModule)return ne;var z={};if(ne!=null)for(var Q in ne)Q!=="default"&&Object.prototype.hasOwnProperty.call(ne,Q)&&l(z,ne,Q);return p(z,ne),z};Object.defineProperty(o,"__esModule",{value:!0}),o.WEBGL_OP_RESOLVE_RULES=void 0;const c=d(2898),m=b(d(7839)),_=d(4196),f=d(2069),u=d(8138),n=d(9663),e=d(5193),a=d(7992),s=d(1253),g=d(4776),y=d(6572),x=d(3346),E=d(5623),S=d(2870),P=d(2143),O=d(4939),k=d(718),D=d(2268),C=d(8117),A=d(2278),$=d(5524),W=d(5975),K=d(3933),Y=d(6558),q=d(5723),se=d(3738),F=b(d(4909)),B=d(8428),fe=d(9793);o.WEBGL_OP_RESOLVE_RULES=[["Abs","","6+",F.abs],["Acos","","7+",F.acos],["Add","","7+",m.add],["And","","7+",m.and],["Asin","","7+",F.asin],["Atan","","7+",F.atan],["AveragePool","","7+",P.averagePool,P.parseAveragePoolAttributes],["BatchNormalization","","7+",c.batchNormalization,c.parseBatchNormalizationAttributes],["Cast","","6+",_.cast,_.parseCastAttributes],["Ceil","","6+",F.ceil],["Clip","","6-10",F.clip,F.parseClipAttributes],["Clip","","11+",F.clipV11],["Concat","","4+",f.concat,f.parseConcatAttributes],["Conv","","1+",u.conv,u.parseConvAttributes],["ConvTranspose","","1+",n.convTranspose,n.parseConvTransposeAttributes],["Cos","","7+",F.cos],["Div","","7+",m.div],["Dropout","","7+",F.identity],["DepthToSpace","","1+",e.depthToSpace,e.parseDepthToSpaceAttributes],["Equal","","7+",m.equal],["Elu","","6+",F.elu,F.parseEluAttributes],["Exp","","6+",F.exp],["Flatten","","1+",a.flatten,a.parseFlattenAttributes],["Floor","","6+",F.floor],["FusedConv","com.microsoft","1+",u.conv,u.parseConvAttributes],["Gather","","1+",s.gather,s.parseGatherAttributes],["Gemm","","7-10",g.gemm,g.parseGemmAttributesV7],["Gemm","","11+",g.gemm,g.parseGemmAttributesV11],["GlobalAveragePool","","1+",P.globalAveragePool,P.parseGlobalAveragePoolAttributes],["GlobalMaxPool","","1+",P.globalMaxPool],["Greater","","7+",m.greater],["Identity","","1+",F.identity],["ImageScaler","","1+",y.imageScaler,y.parseImageScalerAttributes],["InstanceNormalization","","6+",x.instanceNormalization,x.parseInstanceNormalizationAttributes],["LeakyRelu","","6+",F.leakyRelu,F.parseLeakyReluAttributes],["Less","","7+",m.less],["Log","","6+",F.log],["MatMul","","1+",E.matMul,E.parseMatMulAttributes],["MaxPool","","1+",P.maxPool,P.parseMaxPoolAttributes],["Mul","","7+",m.mul],["Neg","","6+",F.neg],["Not","","1+",F.not],["Or","","7+",m.or],["Pad","","2-10",S.padV2,S.parsePadAttributesV2],["Pad","","11+",S.padV11,S.parsePadAttributesV11],["Pow","","7+",m.pow],["PRelu","","7+",m.pRelu],["ReduceLogSum","","1+",O.reduceLogSum,O.parseReduceAttributes],["ReduceMax","","1+",O.reduceMax,O.parseReduceAttributes],["ReduceMean","","1+",O.reduceMean,O.parseReduceAttributes],["ReduceMin","","1+",O.reduceMin,O.parseReduceAttributes],["ReduceProd","","1+",O.reduceProd,O.parseReduceAttributes],["ReduceSum","","1-12",O.reduceSum,O.parseReduceAttributes],["ReduceSumSquare","","1+",O.reduceLogSumSquare,O.parseReduceAttributes],["Relu","","6+",F.relu],["Reshape","","5+",k.reshape],["Resize","","10",D.resize,D.parseResizeAttributesV10],["Resize","","11+",D.resize,D.parseResizeAttributesV11],["Shape","","1+",C.shape],["Sigmoid","","6+",F.sigmoid],["Sin","","7+",F.sin],["Slice","","10+",A.sliceV10],["Slice","","1-9",A.slice,A.parseSliceAttributes],["Softmax","","1-12",$.softmax,$.parseSoftmaxAttributes],["Softmax","","13+",$.softmaxV13,$.parseSoftmaxAttributesV13],["Split","","2-12",W.split,W.parseSplitAttributes],["Sqrt","","6+",F.sqrt],["Squeeze","","1-12",K.squeeze,K.parseSqueezeAttributes],["Squeeze","","13+",K.squeezeV13],["Sub","","7+",m.sub],["Sum","","6+",Y.sum],["Tan","","7+",F.tan],["Tanh","","6+",F.tanh],["Tile","","6+",q.tile],["Transpose","","1+",se.transpose,se.parseTransposeAttributes],["Upsample","","7-8",fe.upsample,fe.parseUpsampleAttributesV7],["Upsample","","9",fe.upsample,fe.parseUpsampleAttributesV9],["Unsqueeze","","1-12",B.unsqueeze,B.parseUnsqueezeAttributes],["Unsqueeze","","13+",B.unsqueezeV13],["Xor","","7+",m.xor]]},2898:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseBatchNormalizationAttributes=o.batchNormalization=void 0;const l=d(246),p=d(5060),b=d(2039),c={name:"BatchNormalization",inputNames:["A","Scale","B","Mean","Variance"],inputTypes:[b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked]};o.batchNormalization=(f,u,n)=>(_(u),[f.run(Object.assign(Object.assign({},c),{cacheHint:n.cacheKey,get:()=>m(f,u,n)}),u)]),o.parseBatchNormalizationAttributes=f=>{const u=f.attributes.getFloat("epsilon",1e-5),n=f.attributes.getFloat("momentum",.9),e=f.attributes.getInt("spatial",1);return(0,l.createAttributeWithCacheKey)({epsilon:u,momentum:n,spatial:e})};const m=(f,u,n)=>{const e=(0,p.getGlsl)(f.session.backend.glContext.version),a=u[0].dims.length,[s,g]=f.calculateTextureWidthAndHeight(u[1].dims,b.TextureType.unpacked),y=`
+  float process(int[${a}] indices) {
+    vec2 position = offsetToCoords(indices[1], ${s}, ${g});
+    float scale = getColorAsFloat(${e.texture2D}(Scale, position));
+    float mean = getColorAsFloat(${e.texture2D}(Mean, position));
+    float variance = getColorAsFloat(${e.texture2D}(Variance, position));
+    float b = getColorAsFloat(${e.texture2D}(B, position));
+
+    return scale * ( (_A(indices) - mean) / sqrt(variance + float(${n.epsilon})) ) + b;
+  }`;return Object.assign(Object.assign({},c),{output:{dims:u[0].dims,type:u[0].type,textureType:b.TextureType.unpacked},shaderSource:y})},_=f=>{if(!f||f.length!==5)throw new Error("BatchNormalization requires 5 inputs.");const u=f[0],n=f[1],e=f[2],a=f[3],s=f[4];if(u.dims.length<3||n.dims.length!==1||e.dims.length!==1||a.dims.length!==1||s.dims.length!==1)throw new Error("invalid input shape.");if(n.dims[0]!==u.dims[1]||e.dims[0]!==u.dims[1]||a.dims[0]!==u.dims[1]||s.dims[0]!==u.dims[1])throw new Error("invalid input shape.");if(u.type!=="float32"&&u.type!=="float64"||n.type!=="float32"&&n.type!=="float64"||e.type!=="float32"&&e.type!=="float64"||a.type!=="float32"&&a.type!=="float64"||s.type!=="float32"&&s.type!=="float64")throw new Error("invalid input tensor types.")}},7839:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.xor=o.sub=o.pRelu=o.pow=o.or=o.mul=o.less=o.greater=o.equal=o.div=o.and=o.add=o.glslPRelu=o.glslPow=o.glslXor=o.glslOr=o.glslAnd=o.glslLess=o.glslGreater=o.glslEqual=o.glslSub=o.glslMul=o.glslDiv=o.glslAdd=void 0;const l=d(2517),p=d(8520),b=d(5060),c=d(2039);function m(){const O="add_";return{body:`
+  float ${O}(float a, float b) {
+    return a + b;
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return v1 + v2;
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function _(){const O="div_";return{body:`
+  float ${O}(float a, float b) {
+    return a / b;
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return v1 / v2;
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function f(){const O="mul_";return{body:`
+  float ${O}(float a, float b) {
+    return a * b;
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return v1 * v2;
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function u(){const O="sub_";return{body:`
+  float ${O}(float a, float b) {
+    return a - b;
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return v1 - v2;
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function n(){const O="equal_";return{body:`
+  float ${O}(float a, float b) {
+    return float(a == b);
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return vec4(equal(v1, v2));
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function e(){const O="greater_";return{body:`
+  float ${O}(float a, float b) {
+    return float(a > b);
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return vec4( v1.r > v2.r ,
+      v1.g > v2.g,
+      v1.b > v2.b,
+      v1.a > v2.a );
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function a(){const O="less_";return{body:`
+  float ${O}(float a, float b) {
+    return float(a < b);
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    return vec4( v1.r < v2.r ,
+                v1.g < v2.g,
+                v1.b < v2.b,
+                v1.a < v2.a );
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function s(){const O="and_";return{body:`
+  float ${O}(float a, float b) {
+    return float( bool(a) && bool(b) );
+  }
+  vec4 ${O}(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:O,type:p.FunctionType.ValueBased}}function g(){const O="or_";return{body:`
+  float ${O}(float a, float b) {
+    return float( bool(a) || bool(b) );
+  }
+  vec4 ${O}(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:O,type:p.FunctionType.ValueBased}}function y(){const O="xor_";return{body:`
+  float ${O}(float a, float b) {
+    return float( bool(a) ^^ bool(b) );
+  }
+  vec4 ${O}(vec4 v1, vec4 v2) {
+    bvec4 b1 = bvec4(v1);
+    bvec4 b2 = bvec4(v2);
+    return vec4( b1.r ^^ b2.r ,
+                b1.g ^^ b2.g,
+                b1.b ^^ b2.b,
+                b1.a ^^ b2.a );
+  }
+  `,name:O,type:p.FunctionType.ValueBased}}function x(){return function(O){const k=`${O}_`;return{body:`
+  float ${k}(float a, float b) {
+    return ${O}(a, b);
+  }
+  vec4 ${k}(vec4 v1, vec4 v2) {
+    return ${O}(v1, v2);
+  }
+  `,name:k,type:p.FunctionType.ValueBased}}("pow")}function E(){const O="prelu_";return{body:`
+  float ${O}(float a, float b) {
+    return a < 0.0 ? a * b: a;
+  }
+  vec4 ${O}(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:O,type:p.FunctionType.ValueBased}}o.glslAdd=m,o.glslDiv=_,o.glslMul=f,o.glslSub=u,o.glslEqual=n,o.glslGreater=e,o.glslLess=a,o.glslAnd=s,o.glslOr=g,o.glslXor=y,o.glslPow=x,o.glslPRelu=E;const S=(O,k,D,C=k[0].type,A)=>{const $=O.session.pack?c.TextureType.packed:c.TextureType.unpacked;return{name:D.name,inputNames:["A","B"],inputTypes:[$,$],cacheHint:A,get:()=>P(O,k,D,C)}},P=(O,k,D,C=k[0].type)=>{const A=O.session.pack?c.TextureType.packed:c.TextureType.unpacked,$=!l.ShapeUtil.areEqual(k[0].dims,k[1].dims);let W=k[0].dims;const K=O.session.pack;if($){const se=l.BroadcastUtil.calcShape(k[0].dims,k[1].dims,!1);if(!se)throw new Error("Can't perform binary op on the given tensors");W=se;const F=W.length,B=k[0].dims.length!==0?k[0].dims.length:1,fe=k[1].dims.length!==0?k[1].dims.length:1,ne=k[0].dims.length!==0?"bcastIndices_A(indices, aindices);":"aindices[0] = 0;",z=k[1].dims.length!==0?"bcastIndices_B(indices, bindices);":"bindices[0] = 0;",Q=(0,b.getGlsl)(O.session.backend.glContext.version),re=K?`
+      ${D.body}
+      void main() {
+        vec4 a = getAAtOutCoords();
+        vec4 b = getBAtOutCoords();
+        vec4 result = ${D.name}(a, b);
+        ${Q.output} = result;
+      }`:`
+      ${D.body}
+      float process(int indices[${F}]) {
+        int aindices[${B}];
+        int bindices[${fe}];
+        ${ne}
+        ${z}
+        return ${D.name}(_A(aindices), _B(bindices));
+      }`;return{name:D.name,inputNames:["A","B"],inputTypes:[A,A],output:{dims:W,type:C,textureType:A},shaderSource:re,hasMain:K}}const Y=(0,b.getGlsl)(O.session.backend.glContext.version),q=`
+    ${D.body}
+    void main() {
+      vec4 v1 = ${Y.texture2D}(A, TexCoords);
+      vec4 v2 = ${Y.texture2D}(B, TexCoords);
+      vec4 result = ${D.name}(v1, v2);
+      ${Y.output} = result;
+    }
+    `;return{name:D.name,inputNames:["A","B"],inputTypes:[A,A],output:{dims:k[0].dims,type:C,textureType:A},shaderSource:q,hasMain:!0}};o.add=(O,k)=>[O.run(S(O,k,m()),k)],o.and=(O,k)=>[O.run(S(O,k,s(),"bool"),k)],o.div=(O,k)=>[O.run(S(O,k,_()),k)],o.equal=(O,k)=>[O.run(S(O,k,n(),"bool"),k)],o.greater=(O,k)=>[O.run(S(O,k,e(),"bool"),k)],o.less=(O,k)=>[O.run(S(O,k,a(),"bool"),k)],o.mul=(O,k)=>[O.run(S(O,k,f()),k)],o.or=(O,k)=>[O.run(S(O,k,g(),"bool"),k)],o.pow=(O,k)=>[O.run(S(O,k,x()),k)],o.pRelu=(O,k)=>[O.run(S(O,k,E()),k)],o.sub=(O,k)=>[O.run(S(O,k,u()),k)],o.xor=(O,k)=>[O.run(S(O,k,y(),"bool"),k)]},4196:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseCastAttributes=o.cast=void 0;const l=d(2517);o.cast=(b,c,m)=>(p(c),[b.cast(c[0],m)]),o.parseCastAttributes=b=>l.ProtoUtil.tensorDataTypeFromProto(b.attributes.getInt("to"));const p=b=>{if(!b||b.length!==1)throw new Error("Cast requires 1 input.");if(b[0].type==="string")throw new Error("Invalid input type.")}},1163:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createPackedConcatProgramInfoLoader=void 0;const l=d(5060),p=d(2039),b=d(9390),c=d(2827);o.createPackedConcatProgramInfoLoader=(_,f,u)=>{const n=(e=f.length,a=u.cacheKey,{name:"Concat (packed)",inputNames:Array.from({length:e},(s,g)=>`X${g}`),inputTypes:Array(e).fill(p.TextureType.packed),cacheHint:a});var e,a;return Object.assign(Object.assign({},n),{get:()=>((s,g,y,x)=>{const E=y[0].dims.slice();if(x>=E.length||x<-1*E.length)throw new Error("axis specified for concat doesn't match input dimensionality");x<0&&(x=E.length+x);const S=E.slice(0);for(let ne=1;ne<y.length;ne++){const z=y[ne].dims.slice();for(let Q=0;Q<E.length;Q++)if(Q===x)S[x]+=z[Q];else if(E[Q]!==z[Q])throw new Error("non concat dimensions must match")}const P=S.length,O=(0,c.getChannels)("coords",P),k=(0,b.getCoordsDataType)(P),D=(0,c.unpackFromChannel)(),C=y.map(ne=>ne.dims),A=(0,b.getGlChannels)(P),$=new Array(C.length-1);$[0]=C[0][x];for(let ne=1;ne<$.length;ne++)$[ne]=$[ne-1]+C[ne][x];const W=A[x],K=A.slice(-2),Y=A.join();let q=`if (${W} < ${$[0]}) {
+        return getChannel(
+            getX0(${Y}), vec2(${K.join()}));
+        }`;for(let ne=1;ne<$.length;ne++){const z=$[ne-1];q+=`
+            if (${W} < ${$[ne]}  && ${W} >= ${$[ne-1]}) {
+              return getChannel(
+                getX${ne}(${m(A,W,z)}),
+                vec2(${m(K,W,z)}));
+            }`}const se=$.length,F=$[$.length-1];q+=`
+            return getChannel(
+              getX${se}(${m(A,W,F)}),
+              vec2(${m(K,W,F)}));`;const B=(0,l.getGlsl)(s.session.backend.glContext.version),fe=`
+          ${D}
+          float getValue(${A.map(ne=>"int "+ne)}) {
+            ${q}
+          }
+
+          void main() {
+            ${k} coords = getOutputCoords();
+            int lastDim = coords.${A[P-1]};
+            coords.${A[P-1]} = coords.${A[P-2]};
+            coords.${A[P-2]} = lastDim;
+
+            vec4 result = vec4(getValue(${O}), 0., 0., 0.);
+
+            ${O[P-1]} = ${O[P-1]} + 1;
+            if (${O[P-1]} < ${S[P-1]}) {
+              result.g = getValue(${O});
+            }
+
+            ${O[P-2]} = ${O[P-2]} + 1;
+            if (${O[P-2]} < ${S[P-2]}) {
+              result.a = getValue(${O});
+            }
+
+            ${O[P-1]} = ${O[P-1]} - 1;
+            if (${O[P-2]} < ${S[P-2]} &&
+                ${O[P-1]} < ${S[P-1]}) {
+              result.b = getValue(${O});
+            }
+            ${B.output} = result;
+          }
+        `;return Object.assign(Object.assign({},g),{output:{dims:S,type:y[0].type,textureType:p.TextureType.packed},shaderSource:fe,hasMain:!0})})(_,n,f,u.axis)})};const m=(_,f,u)=>{const n=_.indexOf(f);return _.map((e,a)=>a===n?`${e} - ${u}`:e).join()}},2069:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseConcatAttributes=o.concat=void 0;const l=d(246),p=d(2039),b=d(1163);o.concat=(e,a,s)=>(n(a),e.session.pack&&a[0].dims.length>1?[e.run((0,b.createPackedConcatProgramInfoLoader)(e,a,s),a)]:[e.run(c(e,a,s),a)]);const c=(e,a,s)=>{const g=(y=a.length,x=s.cacheKey,{name:"Concat",inputNames:Array.from({length:y},(E,S)=>`X${S}`),inputTypes:Array(y).fill(p.TextureType.unpacked),cacheHint:x});var y,x;return Object.assign(Object.assign({},g),{get:()=>((E,S,P,O)=>{const k=P[0].dims.slice();if(O>=k.length||O<-1*k.length)throw new Error("axis specified for concat doesn't match input dimensionality");O<0&&(O=k.length+O);const D=k.slice(0);for(let Y=1;Y<P.length;Y++){const q=P[Y].dims.slice();for(let se=0;se<k.length;se++)if(se===O)D[O]+=q[se];else if(k[se]!==q[se])throw new Error("non concat dimensions must match")}const C=D.length,A=new Array(P.length);let $=0;for(let Y=0;Y<A.length;++Y)$+=P[Y].dims[O],A[Y]=$;let W="";W=P.length<5?m(A):_(A);const K=`
+        ${f(P.length,C)}
+        ${u(A)}
+        ${W}
+        float process(int indices[${C}]) {
+          int textureIndex = getTextureWhereDataResides (indices[${O}]);
+
+          if(textureIndex != 0) {
+            indices[${O}] = indices[${O}] - int(getSizeInConcatAxisValueFromIndex(textureIndex-int(1)));
+          }
+
+          return fetchDataFromCorrectTexture(textureIndex, indices);
+        }`;return Object.assign(Object.assign({},S),{output:{dims:D,type:P[0].type,textureType:p.TextureType.unpacked},shaderSource:K})})(0,g,a,s.axis)})},m=e=>`int getTextureWhereDataResides(int index) {
+      ${e.map((a,s)=>`if(index<${a}) {return ${s};}
+`).join("")}
+    }`,_=e=>m(e),f=(e,a)=>{const s=[`float fetchDataFromCorrectTexture(int textureIndex, int indices[${a}]) {`];for(let g=0;g<e;++g)g===0?s.push(`	if (textureIndex == ${g}) { return _X${g}(indices); }`):g===e-1?s.push(`	else { return _X${g}(indices); }`):s.push(`	else if (textureIndex == ${g}) { return _X${g}(indices); }`);return s.push("	}"),s.join(`
+`)},u=e=>{const a=["int getSizeInConcatAxisValueFromIndex(int index) {"];for(let s=0;s<e.length;++s)s===0?a.push(`	if (index == ${s}) { return ${e[s]}; }`):s===e.length-1?a.push(`	else { return ${e[s]}; }`):a.push(`	else if (index == ${s}) { return ${e[s]}; }`);return a.push("	}"),a.join(`
+`)};o.parseConcatAttributes=e=>(0,l.createAttributeWithCacheKey)({axis:e.attributes.getInt("axis")});const n=e=>{if(!e||e.length<1)throw new Error("too few inputs");const a=e[0].type,s=e[0].dims.length;if(a==="string")throw new Error("string tensor is not supported yet");for(const g of e){if(g.type!==a)throw new Error("input tensors should be one type");if(g.dims.length!==s)throw new Error("input tensors should have the same shape")}}},4770:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createUnpackedGroupedConvProgramInfoLoader=void 0;const l=d(6231),p=d(5060),b=d(2039),c=d(8138),m=d(2823);o.createUnpackedGroupedConvProgramInfoLoader=(_,f,u)=>{const n=(e=f.length>2,a=u.cacheKey,{name:"GroupedConv",inputNames:e?["X","W","Bias"]:["X","W"],inputTypes:e?[b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked]:[b.TextureType.unpacked,b.TextureType.unpacked],cacheHint:a});var e,a;return Object.assign(Object.assign({},n),{get:()=>((s,g,y,x)=>{const E=g.length>2?"value += getBias(output_channel);":"",S=g[0].dims.slice(),P=g[1].dims.slice(),O=P[0]/x.group;l.Logger.verbose("GroupedConv",`autpPad:${x.autoPad}, dilations:${x.dilations}, group:${x.group}, kernelShape:${x.kernelShape}, pads:${x.pads}, strides:${x.strides}`);const k=(0,c.calculateOutputShape)(S,P,x.dilations,x.pads,x.strides),D=(0,p.getGlsl)(s.session.backend.glContext.version),{activationFunction:C,applyActivation:A}=(0,m.getActivationSnippet)(x),$=`
+  const ivec2 strides = ivec2(${x.strides[0]}, ${x.strides[1]});
+  const ivec2 pads = ivec2(${x.pads[0]}, ${x.pads[1]});
+  ${C}
+  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 / ${O};
+
+    float value = 0.0;
+    for (int wInChannel = 0; wInChannel < ${P[1]}; wInChannel++) {
+      int input_channel = group_id * ${P[1]} + wInChannel;
+      for (int wHeight = 0; wHeight < ${P[2]}; wHeight++) {
+        int xHeight = xRCCorner.x + wHeight * ${x.dilations[0]};
+
+        if (xHeight < 0 || xHeight >= ${S[2]}) {
+          continue;
+        }
+
+        for (int wWidth = 0; wWidth < ${P[3]}; wWidth++) {
+          int xWidth = xRCCorner.y + wWidth * ${x.dilations[1]};
+          if (xWidth < 0 || xWidth >= ${S[3]}) {
+            continue;
+          }
+
+          float xVal = getX(batch, input_channel, xWidth, xHeight);
+          float wVal = getW(output_channel, wInChannel, wWidth, wHeight);
+          value += xVal*wVal;
+        }
+      }
+    }
+    ${E}
+    ${A}
+    ${D.output} = vec4(value, .0, .0, .0);
+  }
+`;return Object.assign(Object.assign({},y),{output:{dims:k,type:g[0].type,textureType:b.TextureType.unpacked},shaderSource:$,hasMain:!0})})(_,f,n,u)})}},1386:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.conv2DPacked=o.conv2DPackedPointwise=void 0;const l=d(8138),p=d(8555),b=d(708);o.conv2DPackedPointwise=(c,m,_)=>{const f=m[0].dims,u=m[1].dims,n=(0,l.calculateOutputShape)(f,u,_.dilations,_.pads,_.strides),e=c.reshapePacked(m[0],[f[1],f[2]*f[3]]),a=c.reshapePacked(m[1],[u[0],u[1]]),s=m.length>2?[a,e,m[2]]:[a,e],g=c.run((0,b.createPackedMatmulProgramInfoLoader)(c,s,_),s);return c.reshapePacked(g,n)},o.conv2DPacked=(c,m,_)=>{const f=m[0].dims,u=m[1].dims,n=(0,l.calculateOutputShape)(f,u,_.dilations,_.pads,_.strides),e=c.run((0,p.createPackedIm2ColProgramInfoLoader)(c,m[0],m[1],n,_),[m[0]]),a=c.reshapePacked(m[1],[u[0],u[1]*u[2]*u[3]]),s=m.length===3?[a,e,m[2]]:[a,e],g=c.run((0,b.createPackedMatmulProgramInfoLoader)(c,s,_),s);return c.reshapePacked(g,n)}},9663:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseConvTransposeAttributes=o.convTranspose=void 0;const l=d(246),p=d(5060),b=d(2039),c=d(2823),m=(a,s,g,y,x,E)=>(a-1)*s+g+(y-1)*x+1-E,_=(a,s,g,y,x)=>{const E=Math.floor(a/2);s==="SAME_UPPER"?(g[y]=E,g[x]=a-E):s==="SAME_LOWER"&&(g[y]=a-E,g[x]=E)};o.convTranspose=(a,s,g)=>(e(s,g),f(a,s,g));const f=(a,s,g)=>{const y=n(g,s);return[u(a,s,y)]},u=(a,s,g)=>a.run(((y,x,E)=>{const S=(P=x.length>2,O=E.cacheKey,{name:"ConvTranspose",inputNames:P?["X","W","B"]:["X","W"],inputTypes:P?[b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked]:[b.TextureType.unpacked,b.TextureType.unpacked],cacheHint:O});var P,O;return Object.assign(Object.assign({},S),{get:()=>((k,D,C,A)=>{const $=D.length>2?"getB(output_channel)":"0.0",W=D[0].dims,K=D[1].dims,Y=K[1],q=K[0]/A.group,se=[D[0].dims[0],D[1].dims[1]*A.group,...A.outputShape],F=(0,p.getGlsl)(k.session.backend.glContext.version),{activationFunction:B,applyActivation:fe}=(0,c.getActivationSnippet)(A),ne=`
+  const ivec2 strides = ivec2(${A.strides[0]}, ${A.strides[1]});
+  const ivec2 pads = ivec2(${A.pads[0]}, ${A.pads[1]});
+  ${B}
+  void main() {
+    ivec4 coords = getOutputCoords();
+    int batch = coords.x;
+    int output_channel = coords.y;
+
+    ivec2 loc = coords.zw + pads;
+
+    int group_id = output_channel / ${Y};
+    int wOutChannel = output_channel - group_id * ${Y};
+
+    float value = ${$};
+    for (int inChannelOffset = 0; inChannelOffset < ${q}; inChannelOffset++) {
+      int input_channel = group_id * ${q} + inChannelOffset;
+      for (int wWOff = 0; wWOff < ${K[2]}; wWOff++) {
+        for (int wHOff = 0; wHOff < ${K[3]}; wHOff++) {
+          ivec2 wOff = ivec2(wWOff * ${A.dilations[0]}, wHOff * ${A.dilations[1]});
+          ivec2 wLoc = loc - wOff;
+          ivec2 wLocIn = wLoc / strides;
+          if (
+            wLocIn * strides == wLoc &&
+            wLocIn.x >= 0 && wLocIn.x < ${W[2]} &&
+            wLocIn.y >= 0 && wLocIn.y < ${W[3]}
+          ) {
+            float xVal = getX(batch, input_channel, wLocIn.y, wLocIn.x);
+            float wVal = getW(input_channel, wOutChannel, wHOff, wWOff);
+            value += xVal * wVal;
+          }
+        }
+      }
+    }
+    ${fe}
+    ${F.output} = vec4(value, .0, .0, .0);
+  }
+`;return Object.assign(Object.assign({},C),{output:{dims:se,type:D[0].type,textureType:b.TextureType.unpacked},shaderSource:ne,hasMain:!0})})(y,x,S,E)})})(a,s,g),s),n=(a,s)=>{const g=a.kernelShape.slice();if(a.kernelShape.length===0)for(let S=2;S<s[1].dims.length;++S)g.push(s[1].dims[S]);const y=a.pads.slice(),x=a.outputShape.slice();((S,P,O,k,D,C,A,$)=>{const W=S.length-2,K=$.length===0;for(let Y=0;Y<W;++Y){const q=K?S[Y+2]*C[Y]:$[Y],se=m(S[Y+2],C[Y],D[Y],P[Y],O[Y],q);_(se,k,D,Y,Y+W),K&&$.push(C[Y]*(S[Y+2]-1)+A[Y]+(P[Y]-1)*O[Y]+1-D[Y]-D[Y+W])}})(s[0].dims,g,a.dilations,a.autoPad,y,a.strides,a.outputPadding,x);const E=Object.assign({},a);return Object.assign(E,{kernelShape:g,pads:y,outputShape:x,cacheKey:a.cacheKey}),E};o.parseConvTransposeAttributes=a=>{const s=a.attributes,g=(0,c.parseInternalActivationAttributes)(s),y=s.getString("auto_pad","NOTSET"),x=s.getInts("dilations",[1,1]),E=s.getInt("group",1),S=s.getInts("kernel_shape",[]),P=s.getInts("output_padding",[0,0]),O=s.getInts("output_shape",[]),k=s.getInts("pads",[0,0,0,0]),D=s.getInts("strides",[1,1]);return(0,l.createAttributeWithCacheKey)(Object.assign({autoPad:y,dilations:x,group:E,kernelShape:S,outputPadding:P,outputShape:O,pads:k,strides:D},g))};const e=(a,s)=>{if(!a||a.length!==2&&a.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(a[0].dims.length!==4||a[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(a[0].dims[1]!==a[1].dims[0])throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");const g=a[1].dims[1]*s.group;if(a.length===3&&(a[2].dims.length!==1||a[2].dims[0]!==g))throw new Error("invalid bias");const y=a[0].dims.length-2;if(s.dilations.length!==y)throw new Error(`dilations should be ${y}D`);if(s.strides.length!==y)throw new Error(`strides should be ${y}D`);if(s.pads.length!==2*y)throw new Error(`pads should be ${2*y}D`);if(s.outputPadding.length!==y)throw new Error(`output_padding should be ${y}D`);if(s.kernelShape.length!==0&&s.kernelShape.length!==a[1].dims.length-2)throw new Error("invalid kernel shape");if(s.outputShape.length!==0&&s.outputShape.length!==a[0].dims.length-2)throw new Error("invalid output shape");if(a[0].type!=="float32"||a[1].type!=="float32")throw new Error("ConvTranspose input(X,W) should be float tensor");if(a.length===3&&a[2].type!=="float32")throw new Error("ConvTranspose input(bias) should be float tensor")}},8138:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseConvAttributes=o.conv=o.calculateOutputShape=void 0;const l=d(246),p=d(2517),b=d(4770),c=d(1386),m=d(9828),_=d(2823),f=d(3248),u=d(5623);o.calculateOutputShape=(y,x,E,S,P)=>{const O=y[0],k=y.slice(2),D=k.length,C=x[0],A=x.slice(2).map((W,K)=>W+(W-1)*(E[K]-1)),$=k.map((W,K)=>W+S[K]+S[K+D]).map((W,K)=>Math.floor((W-A[K]+P[K])/P[K]));return[O,C].concat(...$)},o.conv=(y,x,E)=>(g(x,E),n(y,x,E));const n=(y,x,E)=>{const S=s(E,x),P=y.session.pack,O=S.kernelShape[0]===1&&S.kernelShape[1]===1;return S.group>1?[y.run((0,b.createUnpackedGroupedConvProgramInfoLoader)(y,x,S),x)]:O&&P?[e(y,x,S)]:P&&x[0].dims.length===4&&x[0].dims[0]===1&&!O?[(0,c.conv2DPacked)(y,x,S)]:[a(y,x,S)]},e=(y,x,E)=>{const S=x[0].dims,P=x[1].dims,O=(0,o.calculateOutputShape)(S,P,E.dilations,E.pads,E.strides),k=y.reshapeUnpacked(x[0],[S[1],S[2]*S[3]]),D=y.reshapeUnpacked(x[1],[P[0],P[1]]),C=x.length>2?[D,k,x[2]]:[D,k],A=y.run((0,u.createMatmulProgramInfoLoader)(C,E),C);return y.reshapeUnpacked(A,O)},a=(y,x,E)=>{const S=x[0].dims,P=x[1].dims,O=(0,o.calculateOutputShape)(S,P,E.dilations,E.pads,E.strides),k=y.run((0,f.createIm2ColProgramInfoLoader)(y,x[0],x[1],O,E),[x[0]]),D=x.length===3?[k,x[1],x[2]]:[k,x[1]];return y.run((0,m.createDotProductProgramInfoLoader)(y,x,O,E),D)},s=(y,x)=>{const E=y.kernelShape.slice();if(y.kernelShape.length===0)for(let O=2;O<x[1].dims.length;++O)E.push(x[1].dims[O]);const S=y.pads.slice();p.PoolConvUtil.adjustPadsBasedOnAutoPad(x[0].dims,y.strides,y.dilations,E,S,y.autoPad);const P=Object.assign({},y);return Object.assign(P,{kernelShape:E,pads:S,cacheKey:y.cacheKey}),P};o.parseConvAttributes=y=>{const x=y.attributes,E=(0,_.parseInternalActivationAttributes)(x),S=x.getString("auto_pad","NOTSET"),P=x.getInts("dilations",[1,1]),O=x.getInt("group",1),k=x.getInts("kernel_shape",[]),D=x.getInts("pads",[0,0,0,0]),C=x.getInts("strides",[1,1]);return(0,l.createAttributeWithCacheKey)(Object.assign({autoPad:S,dilations:P,group:O,kernelShape:k,pads:D,strides:C},E))};const g=(y,x)=>{if(!y||y.length!==2&&y.length!==3)throw new Error("Conv requires 2 or 3 inputs");if(y[0].dims.length!==4||y[1].dims.length!==4)throw new Error("currently only support 2-dimensional conv");if(y[0].dims[1]!==y[1].dims[1]*x.group)throw new Error("FILTER_IN_CHANNEL should be equal to DATA_CHANNEL");if(y.length===3&&(y[2].dims.length!==1||y[1].dims[0]!==y[2].dims[0]))throw new Error("invalid bias");const E=y[0].dims.length-2;if(x.dilations.length!==E)throw new Error(`dilations should be ${E}D`);if(x.strides.length!==E)throw new Error(`strides should be ${E}D`);if(x.pads.length!==2*E)throw new Error(`pads should be ${2*E}D`);if(x.kernelShape.length!==0&&x.kernelShape.length!==y[1].dims.length-2)throw new Error("invalid kernel shape");if(y[0].type!=="float32"||y[1].type!=="float32")throw new Error("Conv input(X,W) should be float tensor");if(y.length===3&&y[2].type!=="float32")throw new Error("Conv input(bias) should be float tensor")}},5193:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseDepthToSpaceAttributes=o.depthToSpace=void 0;const l=d(3738);o.depthToSpace=(b,c,m)=>{p(c);const _=m.blocksize,f=_*_,u=m.mode==="DCR"?[0,3,4,1,5,2]:[0,1,4,2,5,3],n=m.mode==="DCR"?[c[0].dims[0],_,_,c[0].dims[1]/f,c[0].dims[2],c[0].dims[3]]:[c[0].dims[0],c[0].dims[1]/f,_,_,c[0].dims[2],c[0].dims[3]],e=b.reshapeUnpacked(c[0],n),a={perm:u,cacheKey:`${u}`},[s]=(0,l.transpose)(b,[e],a),g=[c[0].dims[0],c[0].dims[1]/f,c[0].dims[2]*_,c[0].dims[3]*_];return[b.reshapeUnpacked(s,g)]},o.parseDepthToSpaceAttributes=b=>{const c=b.attributes.getInt("blocksize");if(c<1)throw new Error(`blocksize must be >= 1, but got : ${c} for DepthToSpace`);const m=b.attributes.getString("mode","DCR");if(m!=="DCR"&&m!=="CRD")throw new Error(`unrecognized mode: ${m} for DepthToSpace`);return{mode:m,blocksize:c}};const p=b=>{if(b.length!==1)throw new Error(`DepthToSpace expect 1 inputs, but got ${b.length}`);if(b[0].type==="string"||b[0].dims.length!==4)throw new TypeError("DepthToSpace input should be a 4-D numeric tensor")}},9828:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createDotProductProgramInfoLoader=void 0;const l=d(2517),p=d(5060),b=d(2039),c=d(2823),m=d(3248);o.createDotProductProgramInfoLoader=(_,f,u,n)=>{const e=((a,s)=>({name:"ConvDotProduct",inputNames:a?["Im2Col","K","B"]:["Im2Col","K"],inputTypes:a?[b.TextureType.unpacked,b.TextureType.packedLastDimension,b.TextureType.unpacked]:[b.TextureType.unpacked,b.TextureType.packedLastDimension],cacheKey:s.activationCacheKey}))(f.length>2,n);return Object.assign(Object.assign({},e),{get:()=>((a,s,g,y,x)=>{const E=g[0].dims,S=g[1].dims,P=[S[0],Math.ceil(E[1]*S[2]*S[3]/4)],O=(0,m.calculateIm2ColDims)(E,S,y),[k,D]=a.calculateTextureWidthAndHeight(P,b.TextureType.packedLastDimension),C=l.ShapeUtil.computeStrides(O),[A,$]=a.calculateTextureWidthAndHeight(O,b.TextureType.packedLastDimension),W=y.length,K=g.length<3?"0.0":"_B(b)",Y=Math.ceil(E[1]*S[2]*S[3]/4),{activationFunction:q,applyActivation:se}=(0,c.getActivationSnippet)(x),F=(0,p.getGlsl)(a.session.backend.glContext.version),B=`
+${q}
+float process(int indices[${W}]) {
+  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] * ${C[0]} + im2col[1] * ${C[1]} + im2col[2] * ${C[2]};
+  int kernelOffset = indices[1] * ${P[1]};
+  float value = ${K};
+  for (int i = 0; i < ${Y}; ++i) {
+    vec2 im2colCoords = offsetToCoords(im2colOffset, ${A}, ${$});
+    vec2 kernelCoords = offsetToCoords(kernelOffset, ${k}, ${D});
+    value += dot(${F.texture2D}(Im2Col, im2colCoords), ${F.texture2D}(K, kernelCoords));
+    ++im2colOffset;
+    ++kernelOffset;
+  }
+  ${se}
+  return value;
+}`;return Object.assign(Object.assign({},s),{output:{dims:y,type:g[0].type,textureType:b.TextureType.unpacked},shaderSource:B})})(_,e,f,u,n)})}},7992:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseFlattenAttributes=o.flatten=void 0;const l=d(2517);o.flatten=(b,c,m)=>{p(c,m);const _=l.ShapeUtil.flattenShape(c[0].dims,m);return[b.reshapeUnpacked(c[0],_)]},o.parseFlattenAttributes=b=>b.attributes.getInt("axis",1);const p=(b,c)=>{if(!b||b.length!==1)throw new Error("Flatten requires 1 input.");const m=b[0].dims.length;if(m===0)throw new Error("scalar tensor is not supported.");if(c<-m||c>m)throw new Error("Invalid axis");if(b[0].type==="string")throw new Error("string tensor is not supported.")}},2823:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseInternalActivationAttributes=o.getActivationSnippet=void 0;const l=d(2517),p=d(4909);o.getActivationSnippet=function(b){let c;switch(b.activation){case"Relu":c=(0,p.glslRelu)();break;case"Sigmoid":c=(0,p.glslSigmoid)();break;case"Clip":c=(0,p.glslClip)(b.clipMin,b.clipMax);break;default:return{activationFunction:"",applyActivation:""}}const m=c.name;return{activationFunction:c.body,applyActivation:`value = ${m}_(value);`}},o.parseInternalActivationAttributes=b=>{const c=b.getString("activation","");if(c==="Clip"){const[m,_]=b.getFloats("activation_params",[l.MIN_CLIP,l.MAX_CLIP]);return{activation:c,clipMax:_,clipMin:m,activationCacheKey:`${c}:${m},${_}`}}return{activation:c,activationCacheKey:c}}},1253:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseGatherAttributes=o.gather=void 0;const l=d(246),p=d(782),b=d(2517),c=d(2039);o.gather=(u,n,e)=>(f(n,e.axis),[u.run(_(u,n,e),n)]),o.parseGatherAttributes=u=>(0,l.createAttributeWithCacheKey)({axis:u.attributes.getInt("axis",0)});const m={name:"Gather",inputNames:["A","B"],inputTypes:[c.TextureType.unpacked,c.TextureType.unpacked]},_=(u,n,e)=>{const a=Object.assign(Object.assign({},m),{cacheHint:e.cacheKey});return Object.assign(Object.assign({},a),{get:()=>((s,g,y,x)=>{const E=y[0].dims.slice(),S=y[1].dims.slice(),P=new Array(E.length+S.length-1);x=b.ShapeUtil.normalizeAxis(x,E.length);const O=[];for(let D=0;D<P.length;D++)D<x?(P[D]=E[D],O.push(`inputIdx[${D}] = outputIdx[${D}];`)):D<x+S.length?(P[D]=S[D-x],O.push(`indexDataIdx[${D-x}] = outputIdx[${D}];`)):(P[D]=E[D-S.length+1],O.push(`inputIdx[${D-S.length+1}] = outputIdx[${D}];`));const k=`
+      float process(int outputIdx[${P.length||1}]) {
+        int inputIdx[${E.length}];
+        int indexDataIdx[${S.length||1}];
+        indexDataIdx[0] = 0;
+        ${O.join(`
+        `)}
+        int idx = int(_B(indexDataIdx));
+        inputIdx[${x}] = idx < 0 ? idx + ${E[x]} : idx;
+        return _A(inputIdx);
+      }`;return Object.assign(Object.assign({},g),{output:{dims:P,type:y[0].type,textureType:c.TextureType.unpacked},shaderSource:k})})(0,a,n,e.axis)})},f=(u,n)=>{if(!u||u.length!==2)throw new Error("Gather requires 2 inputs.");const e=u[0].dims.length;if(e<1)throw new Error("Invalid input shape.");if(n<-e||n>e-1)throw new Error("Invalid axis.");if(p.NUMBER_TYPES.indexOf(u[0].type)===-1)throw new Error("Invaid input type.");if(u[1].type!=="int32"&&u[1].type!=="int16")throw new Error("Invaid input type.")}},4776:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseGemmAttributesV11=o.parseGemmAttributesV7=o.gemm=void 0;const l=d(246),p=d(2517),b=d(2039);o.gemm=(u,n,e)=>(f(n,e),[u.run(m(n,e),n)]);const c=(u,n)=>{const e=u.attributes.getInt("transA",0)!==0,a=u.attributes.getInt("transB",0)!==0,s=u.attributes.getFloat("alpha",1),g=u.attributes.getFloat("beta",1);return(0,l.createAttributeWithCacheKey)({transA:e,transB:a,alpha:s,beta:g,isOptionalC:n})};o.parseGemmAttributesV7=u=>c(u,!1),o.parseGemmAttributesV11=u=>c(u,!0);const m=(u,n)=>{const e={name:"Gemm",inputNames:u.length===3?["A","B","C"]:["A","B"],inputTypes:u.length===3?[b.TextureType.unpacked,b.TextureType.unpacked,b.TextureType.unpacked]:[b.TextureType.unpacked,b.TextureType.unpacked],key:n.cacheKey};return Object.assign(Object.assign({},e),{get:()=>_(e,u,n)})},_=(u,n,e)=>{const a=n[0].dims.slice(),s=n[1].dims.slice(),[g,y]=p.GemmUtil.getShapeOfGemmResult(a,e.transA,s,e.transB,n.length===3?n[2].dims:void 0),x=[g,y];if(!x)throw new Error("Can't use gemm on the given tensors");let E=a[a.length-1],S="";e.transA&&(E=a[0]),e.transA&&e.transB?S="value += _A_T(a) * _B_T(b);":e.transA&&!e.transB?S="value += _A_T(a) * _B(b);":!e.transA&&e.transB?S="value += _A(a) * _B_T(b);":e.transA||e.transB||(S="value += _A(a) * _B(b);");const P=x.length,O=`
+      float process(int indices[${P}]) {
+          int a[${P}];
+          int b[${P}];
+          ${n.length===3?`int c[${n[2].dims.length}];`:""}
+
+          copyVec(indices, a);
+          copyVec(indices, b);
+          ${n.length===3?"bcastIndices_C(indices, c);":""}
+
+          float value = 0.0;
+          for (int k=0; k<${E}; ++k) {
+              a[${P-1}] = k;
+              b[${P-2}] = k;
+              ${S}
+          }
+
+          value = value * alpha;
+          ${n.length===3?"value += beta * _C(c);":""}
+          return value;
+      }`;return Object.assign(Object.assign({},u),{output:{dims:x,type:n[0].type,textureType:b.TextureType.unpacked},variables:[{name:"alpha",type:"float",data:e.alpha},{name:"beta",type:"float",data:e.beta}],shaderSource:O})},f=(u,n)=>{if(!u)throw new Error("Input is missing");if(n.isOptionalC&&(u.length<2||u.length>3))throw new Error("Invaid input shape.");if(!n.isOptionalC&&u.length!==3)throw new Error("Gemm requires 3 inputs");if(u.length===3&&u[2].dims.length!==1&&u[2].dims.length!==2)throw new Error("Invalid input shape of C");if(u[0].type!=="float32"&&u[0].type!=="float64"||u[1].type!=="float32"&&u[1].type!=="float64"||u.length===3&&u[2].type!=="float32"&&u[2].type!=="float64")throw new Error("Invalid input type.");if(u[0].type!==u[1].type||u.length===3&&u[0].type!==u[2].type)throw new Error("Input types are mismatched")}},8555:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createPackedIm2ColProgramInfoLoader=void 0;const l=d(5060),p=d(2039),b=d(2827);o.createPackedIm2ColProgramInfoLoader=(c,m,_,f,u)=>{const n=(e=u.cacheKey,{name:"Im2Col (packed)",inputNames:["A"],inputTypes:[p.TextureType.packed],cacheHint:e});var e;return Object.assign(Object.assign({},n),{get:()=>((a,s,g,y,x,E)=>{const S=g.dims,P=y.dims,O=x.length,k=[P[1]*P[2]*P[3],x[2]*x[3]],D=P[2]*P[3],C=(0,b.unpackFromChannel)(),A=(0,l.getGlsl)(a.session.backend.glContext.version);let $="";for(let K=0;K<=1;K++)for(let Y=0;Y<=1;Y++)$+=`
+            blockIndex = rc.x + ${Y};
+            pos = rc.y + ${K};
+
+            if(blockIndex < ${k[1]} && pos < ${k[0]}) {
+              offsetY = int(blockIndex / (${x[O-1]})) * ${E.strides[0]} -
+                ${E.pads[0]};
+              d0 = offsetY + ${E.dilations[0]} * (imod(pos, ${D}) / ${P[2]});
+
+              if(d0 < ${S[2]} && d0 >= 0) {
+                offsetX = imod(blockIndex, ${x[O-1]}) * ${E.strides[1]} -
+                  ${E.pads[1]};
+                d1 = offsetX + ${E.dilations[1]} * imod(imod(pos, ${D}), ${P[2]});
+
+                if(d1 < ${S[3]} && d1 >= 0) {
+
+                  ch = int(float(pos)/ ${D}.);
+                    innerDims = vec2(d0, d1);
+                    result[${2*K+Y}] = getChannel(
+                      getA(0, ch, int(innerDims.x),
+                      int(innerDims.y)), innerDims);
+                }
+              }
+            }
+
+          `;const W=`
+      ${C}
+
+      void main() {
+        ivec2 rc = getOutputCoords();
+          vec4 result = vec4(0.0);
+          int blockIndex, pos, offsetY, d0, offsetX, d1, ch;
+          vec2 innerDims;
+          ${$}
+          ${A.output} = result;
+      }
+            `;return Object.assign(Object.assign({},s),{output:{dims:k,type:g.type,textureType:p.TextureType.packed},shaderSource:W,hasMain:!0})})(c,n,m,_,f,u)})}},3248:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.calculateIm2ColDims=o.createIm2ColProgramInfoLoader=void 0;const l=d(2039);o.createIm2ColProgramInfoLoader=(p,b,c,m,_)=>{const f=(u=_.cacheKey,{name:"Im2Col",inputNames:["X"],inputTypes:[l.TextureType.unpacked],cacheHint:u});var u;return Object.assign(Object.assign({},f),{get:()=>((n,e,a,s,g,y)=>{const x=a.dims,E=s.dims,S=g.length,P=(0,o.calculateIm2ColDims)(x,E,g,4),O=`
+        const int XC = ${x[1]};
+        const int XH = ${x[2]};
+        const int XW = ${x[3]};
+        const int KH = ${y.kernelShape[0]};
+        const int KW = ${y.kernelShape[1]};
+        const int dilationH = ${y.dilations[0]};
+        const int dilationW = ${y.dilations[1]};
+        const int strideH = ${y.strides[0]};
+        const int strideW = ${y.strides[1]};
+        const int padH = ${y.pads[0]};
+        const int padW = ${y.pads[1]};
+        const int KHKW = KH*KW;
+        const int XCKHKW = XC * KHKW;
+        const int outputChannels = 4;
+        vec4 process(int indices[${S}]) {
+          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[${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:P,type:a.type,textureType:l.TextureType.packedLastDimension},shaderSource:O})})(0,f,b,c,m,_)})},o.calculateIm2ColDims=(p,b,c,m=4)=>[c[0],c[2],c[3],Math.ceil(p[1]*b[2]*b[3]/m)]},6572:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseImageScalerAttributes=o.imageScaler=void 0;const l=d(246),p=d(2039);o.imageScaler=(f,u,n)=>(_(u),[f.run(c(f,u,n),u)]),o.parseImageScalerAttributes=f=>{const u=f.attributes.getFloat("scale"),n=f.attributes.getFloats("bias");return(0,l.createAttributeWithCacheKey)({scale:u,bias:n})};const b={name:"ImageScaler",inputNames:["X"],inputTypes:[p.TextureType.unpacked]},c=(f,u,n)=>{const e=Object.assign(Object.assign({},b),{cacheHint:n.cacheKey});return Object.assign(Object.assign({},e),{get:()=>((a,s,g,y)=>{const x=g[0].dims.slice(),E=x.length,S=`
+      ${m(y.bias.length)}
+      float process(int indices[${E}]) {
+        return _X(indices) * scale + getBias(bias, indices[1]);
+      }`;return Object.assign(Object.assign({},s),{output:{dims:x,type:g[0].type,textureType:p.TextureType.unpacked},variables:[{name:"bias",type:"float",arrayLength:y.bias.length,data:y.bias},{name:"scale",type:"float",data:y.scale}],shaderSource:S})})(0,e,u,n)})},m=f=>{const u=[`float getBias(float bias[${f}], int channel) {`];for(let n=0;n<f;++n)n===0?u.push(`	if (channel == ${n}) { return bias[${n}]; }`):n===f-1?u.push(`	else { return bias[${n}]; }`):u.push(`	else if (channel == ${n}) { return bias[${n}]; }`);return u.push("	}"),u.join(`
+`)},_=f=>{if(!f||f.length!==1)throw new Error("ImageScaler requires 1 input.");if(f[0].dims.length!==4)throw new Error("Invalid input shape.");if(f[0].type!=="float32"&&f[0].type!=="float64")throw new Error("Invalid input type.")}},3346:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseInstanceNormalizationAttributes=o.instanceNormalization=void 0;const l=d(5060),p=d(2039);o.instanceNormalization=(u,n,e)=>{f(n);const a=u.run(c(n[0]),n);return[u.run(_(u,n[0],e,a.dims),[n[0],a,n[1],n[2]])]},o.parseInstanceNormalizationAttributes=u=>u.attributes.getFloat("epsilon",1e-5);const b={name:"InstanceNormalization_MeanAndVariance",inputNames:["X"],inputTypes:[p.TextureType.unpacked]},c=u=>Object.assign(Object.assign({},b),{get:()=>((n,e)=>{const a=e.dims.slice(),s=a[1],g=a[2]*a[3],y=[a[0],s],x=`
+      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<${a[2]}; a2++) {
+          a[2] = a2;
+          for(int a3=0; a3<${a[3]}; a3++) {
+            a[3] = a3;
+            float x = _X(a);
+            temp += x;
+          }
+        }
+        float mean = temp / float(${g});
+        temp = 0.0;
+        for(int a2=0; a2<${a[2]}; a2++) {
+          a[2] = a2;
+          for(int a3=0; a3<${a[3]}; a3++) {
+            a[3] = a3;
+            float x = _X(a);
+            temp += (x - mean) * (x - mean);
+          }
+        }
+        v.r = mean;
+        v.g = temp / float(${g});
+
+        return v;
+      }`;return Object.assign(Object.assign({},n),{output:{dims:y,type:e.type,textureType:p.TextureType.packedLastDimension},shaderSource:x})})(b,u)}),m={name:"InstanceNormalization_ComputeOutput",inputNames:["X","MeanAndVariance","Scale","B"],inputTypes:[p.TextureType.unpacked,p.TextureType.packedLastDimension,p.TextureType.unpacked,p.TextureType.unpacked]},_=(u,n,e,a)=>{const s=Object.assign(Object.assign({},m),{cacheHint:`${e}`});return Object.assign(Object.assign({},s),{get:()=>((g,y,x,E,S)=>{const P=(0,l.getGlsl)(g.session.backend.glContext.version),[O,k]=g.calculateTextureWidthAndHeight(S,p.TextureType.packedLastDimension),[D,C]=[O/4,k],A=`
+      vec4 get_MeanAndVariance(int[2] mv) {
+        int offset = indicesToOffset_MeanAndVariance(mv);
+        vec2 coords = offsetToCoords(offset, ${D}, ${C});
+        return ${P.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({},y),{output:{dims:x.dims,type:x.type,textureType:p.TextureType.unpacked},variables:[{name:"epsilon",type:"float",data:E}],shaderSource:A})})(u,s,n,e,a)})},f=u=>{if(!u||u.length!==3)throw new Error("InstanceNormalization requires 3 inputs.");const n=u[0],e=u[1],a=u[2];if(n.dims.length<3||e.dims.length!==1||a.dims.length!==1)throw new Error("Invalid input shape.");if(e.dims[0]!==n.dims[1]||a.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"||a.type!=="float32"&&a.type!=="float64")throw new Error("Invalid input type.");if(u[0].dims.length!==4)throw new Error("Only support 4-D input shape.")}},708:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createPackedMatmulProgramInfoLoader=void 0;const l=d(2517),p=d(5060),b=d(2039),c=d(9390),m=d(2823),_=d(5623);o.createPackedMatmulProgramInfoLoader=(f,u,n)=>{const e=(a=u.length>2,s=n.activationCacheKey,{name:"MatMul (packed)",inputNames:a?["A","B","Bias"]:["A","B"],inputTypes:a?[b.TextureType.packed,b.TextureType.packed,b.TextureType.packed]:[b.TextureType.packed,b.TextureType.packed],cacheHint:s});var a,s;return Object.assign(Object.assign({},e),{get:()=>((g,y,x,E)=>{const S=x.length>2,P=S?"value += getBiasForMatmul();":"",O=x[0].dims,k=x[1].dims,D=l.BroadcastUtil.calcShape(O,k,!0),C=!l.ShapeUtil.areEqual(x[0].dims,x[1].dims);if(!D)throw new Error("Can't use matmul on the given tensors");const A=O[O.length-1],$=Math.ceil(A/2),W=O.length,K=k.length,Y=(0,p.getGlsl)(g.session.backend.glContext.version),q=(0,c.getCoordsDataType)(D.length),se=D.length,F=(0,c.getGlChannels)(),{activationFunction:B,applyActivation:fe}=(0,m.getActivationSnippet)(E),ne=S?`${(0,_.getBiasForMatmul)(q,F,x[2].dims,D,!0)}`:"",z=C?`${function(_e,ve,we,Ae){let Me=[],tt=[];const Ze=we[0].dims,ot=we[1].dims,Ue=Ze.length,Qe=ot.length,nt=Ae.length,Lt=nt-Ue,Bt=nt-Qe;Me=Ze.map((pt,Ut)=>`coords.${ve[Ut+Lt]}`),Me[Ue-1]="i*2",Me.join(", "),tt=ot.map((pt,Ut)=>`coords.${ve[Ut+Bt]}`),tt[Qe-2]="i*2",tt.join(", ");const yt=l.BroadcastUtil.getBroadcastDims(Ze,Ae),bn=l.BroadcastUtil.getBroadcastDims(ot,Ae),_n=yt.map(pt=>`coords.${ve[pt+Lt]} = 0;`).join(`
+`),Jt=bn.map(pt=>`coords.${ve[pt+Bt]} = 0;`).join(`
+`),Rt=`int lastDim = coords.${ve[nt-1]};
+  coords.${ve[nt-1]} = coords.${ve[nt-2]};
+  coords.${ve[nt-2]} = lastDim;`;return`
+vec4 getAAtOutCoordsMatmul(int i) {
+  ${_e} coords = getOutputCoords();
+  ${Rt}
+  ${_n}
+  vec4 outputValue = getA(${Me});
+  return outputValue;
+}
+
+vec4 getBAtOutCoordsMatmul(int i) {
+  ${_e} coords = getOutputCoords();
+  ${Rt}
+  ${Jt}
+  vec4 outputValue = getB(${tt});
+  return outputValue;
+}`}(q,F,x,D)}`:"",Q=C?"getAAtOutCoordsMatmul(i)":`getA(${function(_e,ve){let we="";for(let Ae=0;Ae<ve-2;Ae++)we+=`rc.${_e[Ae]}, `;return we+=`rc.${_e[ve-2]}, i*2`,we}(F,W)})`,re=C?"getBAtOutCoordsMatmul(i)":`getB(${function(_e,ve){let we="";for(let Ae=0;Ae<ve-2;Ae++)we+=`rc.${_e[Ae]}, `;return we+=`i*2, rc.${_e[ve-1]}`,we}(F,K)})`,ue=`
+            ${z}
+            ${ne}
+            ${B}
+            void main() {
+              ${C?"":`${q} rc =
+          getOutputCoords(); int lastDim = rc.${F[se-1]}; rc.${F[se-1]} =
+          rc.${F[se-2]}; rc.${F[se-2]} = lastDim;
+      `}
+
+              vec4 value = vec4(0);
+              for (int i = 0; i < ${$}; i++) {
+                vec4 a = ${Q};
+                vec4 b = ${re};
+
+                value += (a.rrbb * b.rgrg);
+                value += (a.ggaa * b.baba);
+              }
+              ${P}
+              ${fe}
+              ${Y.output} = value;
+            }`;return Object.assign(Object.assign({},y),{output:{dims:D,type:x[0].type,textureType:b.TextureType.packed},shaderSource:ue,hasMain:!0})})(f,e,u,n)})}},5623:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.getBiasForMatmul=o.createMatmulProgramInfoLoader=o.parseMatMulAttributes=o.matMul=void 0;const l=d(2517),p=d(2039),b=d(9390),c=d(2823),m=d(708);function _(n,e){const a=(s=n.length>2,g=e.activationCacheKey,{name:"MatMul",inputNames:s?["A","B","Bias"]:["A","B"],inputTypes:s?[p.TextureType.unpacked,p.TextureType.unpacked,p.TextureType.unpacked]:[p.TextureType.unpacked,p.TextureType.unpacked],cacheHint:g});var s,g;return Object.assign(Object.assign({},a),{get:()=>function(y,x,E){const S=x[0].dims,P=x[1].dims,O=l.BroadcastUtil.calcShape(S,P,!0);if(!O)throw new Error("Can't use matmul on the given tensors");const k=(0,b.getCoordsDataType)(O.length),D=(0,b.getGlChannels)(),{activationFunction:C,applyActivation:A}=(0,c.getActivationSnippet)(E),$=x.length>2,W=$?"value += getBiasForMatmul();":"",K=$?`${u(k,D,x[2].dims,O,!1)}`:"",Y=O.length,q=S.length,se=P.length,F=`
+    ${C}
+    ${K}
+    float process(int indices[${Y}]) {
+        int a[${q}];
+        int b[${se}];
+        bcastMatmulIndices_A(indices, a);
+        bcastMatmulIndices_B(indices, b);
+
+        float value;
+        for (int k=0; k<${S[S.length-1]}; ++k) {
+            a[${q-1}] = k;
+            b[${se-2}] = k;
+            value += _A(a) * _B(b);
+        }
+        ${W}
+        ${A}
+        return value;
+    }`;return Object.assign(Object.assign({},y),{output:{dims:O,type:x[0].type,textureType:p.TextureType.unpacked},shaderSource:F})}(a,n,e)})}o.matMul=(n,e,a)=>(f(e),n.session.pack?[n.run((0,m.createPackedMatmulProgramInfoLoader)(n,e,a),e)]:[n.run(_(e,a),e)]),o.parseMatMulAttributes=n=>(0,c.parseInternalActivationAttributes)(n.attributes),o.createMatmulProgramInfoLoader=_;const f=n=>{if(!n||n.length!==2)throw new Error("MatMul requires 2 inputs.");if(n[0].dims[n[0].dims.length-1]!==n[1].dims[n[1].dims.length-2])throw new Error("shared dimension does not match.");if(n[0].type!=="float32"&&n[0].type!=="float64"||n[1].type!=="float32"&&n[1].type!=="float64")throw new Error("inputs should be float type");if(n[0].type!==n[1].type)throw new Error("inputs types should match")};function u(n,e,a,s,g){let y="";const x=a.length,E=s.length,S=E-x;y=E<2&&x>0?"coords":a.map((k,D)=>`coords.${e[D+S]}`).join(", ");const P=l.BroadcastUtil.getBroadcastDims(a,s).map(k=>`coords.${e[k+S]} = 0;`).join(`
+`);let O="vec4(outputValue.xx, outputValue.yy)";return l.ShapeUtil.size(a)===1&&(O="vec4(outputValue.x)"),g?`
+vec4 getBiasForMatmul() {
+  ${n} coords = getOutputCoords();
+  ${P}
+  vec4 outputValue = getBias(${y});
+  return ${O};
+}`:`
+float getBiasForMatmul() {
+  ${n} coords = getOutputCoords();
+  ${P}
+  return getBias(coords.x);
+}`}o.getBiasForMatmul=u},2403:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createPackProgramInfoLoader=void 0;const l=d(5060),p=d(2039),b=d(9390),c=d(2827),m={name:"pack",inputNames:["A"],inputTypes:[p.TextureType.unpackedReversed]};o.createPackProgramInfoLoader=(_,f)=>Object.assign(Object.assign({},m),{get:()=>((u,n)=>{const e=(0,l.getGlsl)(u.session.backend.glContext.version),a=n.dims,s=a.length,g=n.dims.length,y=(0,b.getCoordsDataType)(g),x=(0,c.getChannels)("rc",g),E=(S=g,P=x,O=a[a.length-2],k=a[a.length-1],S===0||S===1?"":`
+    int r = ${P[S-2]};
+    int c = ${P[S-1]};
+    int rp1 = ${P[S-2]} + 1;
+    int cp1 = ${P[S-1]} + 1;
+    bool rEdge = rp1 >= ${k};
+    bool cEdge = cp1 >= ${O};
+    `);var S,P,O,k;let D;D=s===0?[1,1]:s===1?[a[0],1]:[a[g-1],a[g-2]];const C=function(W,K,Y){if(W===0)return"false";if(W===1)return`rc > ${K[0]}`;let q="";for(let se=W-2;se<W;se++)q+=`${Y[se]} >= ${K[se-W+2]}`,se<W-1&&(q+="||");return q}(g,D,x),A=function(W,K){const Y=W.length;if(Y===0)return"getA(), 0, 0, 0";if(Y===1)return`getA(rc),
+            rc + 1 >= ${W[0]} ? 0. : getA(rc + 1),
+            0, 0`;let q="";if(Y>2)for(let se=0;se<Y-2;++se)q+=`${K[se]},`;return`getA(${q}r, c),
+          rEdge ? 0. : getA(${q}rp1, c),
+          cEdge ? 0. : getA(${q}r, cp1),
+          rEdge || cEdge ? 0. : getA(${q}rp1, cp1)`}(a,x),$=`
+        void main() {
+          ${y} rc = getOutputCoords();
+
+          if(${C}) {
+            ${e.output} = vec4(0);
+          } else {
+            ${E}
+
+            ${e.output} = vec4(${A});
+          }
+        }
+      `;return Object.assign(Object.assign({},m),{hasMain:!0,output:{dims:n.dims,type:n.type,textureType:p.TextureType.packed},shaderSource:$})})(_,f)})},2827:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.unpackFromChannel=o.getChannels=o.getVecChannels=void 0;const l=d(9390);function p(b,c){return(0,l.getGlChannels)(c).map(m=>`${b}.${m}`)}o.getVecChannels=p,o.getChannels=function(b,c){return c===1?[b]:p(b,c)},o.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:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parsePadAttributesV11=o.padV11=o.parsePadAttributesV2=o.padV2=void 0;const l=d(246),p=d(2517),b=d(5060),c=d(2039),m={name:"Pad",inputNames:["A"],inputTypes:[c.TextureType.unpacked]};o.padV2=(y,x,E)=>(u(x),[y.run(Object.assign(Object.assign({},m),{cacheHint:E.cacheKey,get:()=>f(y,x[0],E)}),x)]),o.parsePadAttributesV2=y=>{const x=y.attributes.getString("mode","constant"),E=y.attributes.getFloat("value",0),S=y.attributes.getInts("pads");return(0,l.createAttributeWithCacheKey)({mode:x,value:E,pads:S})},o.padV11=(y,x,E)=>{n(x);const S=_(y,x,E);return(0,o.padV2)(y,[x[0]],S)},o.parsePadAttributesV11=y=>y.attributes.getString("mode","constant");const _=(y,x,E)=>{if(!y.session.isInitializer(x[1].dataId)||x.length>=3&&!y.session.isInitializer(x[2].dataId))throw new Error("dynamic pad attributes are not allowed");const S=Array.from(x[1].integerData),P=x.length>=3?x[2].floatData[0]:0;return(0,l.createAttributeWithCacheKey)({mode:E,pads:S,value:P})},f=(y,x,E)=>{const S=p.ShapeUtil.padShape(x.dims.slice(),E.pads),P=S.length,O=`
+      ${e(y,x,E)}
+      float process(int[${P}] indices) {
+          return padA(indices);
+      }`;return{name:"Pad",inputNames:["A"],inputTypes:[c.TextureType.unpacked],output:{dims:S,type:x.type,textureType:c.TextureType.unpacked},shaderSource:O}},u=y=>{if(!y||y.length!==1)throw new Error("Pad requires 1 input");if(y[0].type!=="float32"&&y[0].type!=="float64")throw new Error("Invalid input type.")},n=y=>{if(!y||y.length!==2&&y.length!==3)throw new Error("Pad requires 2 or 3 inputs");if(y[1].type!=="int32")throw new Error("Invalid input type.");if(y.length>=3&&y[2].type==="string")throw new Error("Invalid input type.")},e=(y,x,E)=>{const S=(0,b.getGlsl)(y.session.backend.glContext.version),[P,O]=y.calculateTextureWidthAndHeight(x.dims,c.TextureType.unpacked),k=p.ShapeUtil.computeStrides(x.dims);switch(E.mode){case"constant":return a(S,x.dims,k,P,O,E.pads,E.value);case"reflect":return s(S,x.dims,k,P,O,E.pads);case"edge":return g(S,x.dims,k,P,O,E.pads);default:throw new Error("Invalid mode")}},a=(y,x,E,S,P,O,k)=>{const D=x.length;let C="";for(let A=D-1;A>=0;--A)C+=`
+        k = m[${A}] - ${O[A]};
+        if (k < 0)  return constant;
+        if (k >= ${x[A]}) return constant;
+        offset += k * ${E[A]};
+        `;return`
+      float padA(int m[${D}]) {
+        const float constant = float(${k});
+        int offset = 0;
+        int k = 0;
+        ${C}
+        vec2 coords = offsetToCoords(offset, ${S}, ${P});
+        float value = getColorAsFloat(${y.texture2D}(A, coords));
+        return value;
+      }
+      `},s=(y,x,E,S,P,O)=>{const k=x.length;let D="";for(let C=k-1;C>=0;--C)D+=`
+        k = m[${C}] - ${O[C]};
+        if (k < 0) { k = -k; }
+        {
+          const int _2n_1 = ${2*(x[C]-1)};
+          k = int( mod( float(k), float(_2n_1) ) ) ;
+          if(k >= ${x[C]}) { k = _2n_1 - k; }
+        }
+        offset += k * ${E[C]};
+        `;return`
+      float padA(int m[${k}]) {
+        int offset = 0;
+        int k = 0;
+        ${D}
+        vec2 coords = offsetToCoords(offset, ${S}, ${P});
+        float value = getColorAsFloat(${y.texture2D}(A, coords));
+        return value;
+      }
+      `},g=(y,x,E,S,P,O)=>{const k=x.length;let D="";for(let C=k-1;C>=0;--C)D+=`
+        k = m[${C}] - ${O[C]};
+        if (k < 0)  k = 0;
+        if (k >= ${x[C]}) k = ${x[C]-1};
+        offset += k * ${E[C]};
+      `;return`
+      float padA(int m[${k}]) {
+        int offset = 0;
+        int k = 0;
+        ${D}
+        vec2 coords = offsetToCoords(offset, ${S}, ${P});
+        float value = getColorAsFloat(${y.texture2D}(A, coords));
+        return value;
+      }
+      `}},2143:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.globalMaxPool=o.parseMaxPoolAttributes=o.maxPool=o.parseGlobalAveragePoolAttributes=o.globalAveragePool=o.parseAveragePoolAttributes=o.averagePool=void 0;const l=d(246),p=d(2517),b=d(2039);o.averagePool=(g,y,x)=>{n(y);const E={name:"AveragePool",inputNames:["X"],inputTypes:[b.TextureType.unpacked],cacheHint:x.cacheKey};return[g.run(Object.assign(Object.assign({},E),{get:()=>c(y,E,!1,x)}),y)]},o.parseAveragePoolAttributes=g=>{const y=g.attributes.getString("auto_pad","NOTSET"),x=g.attributes.getInt("ceil_mode",0),E=g.attributes.getInt("count_include_pad",0)!==0,S=g.attributes.getInts("kernel_shape"),P=g.attributes.getInts("strides",[]),O=g.attributes.getInts("pads",[]);if(x!==0)throw new Error("using ceil() in shape computation is not yet supported for AveragePool");return(0,l.createAttributeWithCacheKey)({autoPad:y,ceilMode:x,countIncludePad:E,kernelShape:S,strides:P,pads:O})};const c=(g,y,x,E)=>{const[S,P]=_(g,E,x),O=p.ShapeUtil.size(S.kernelShape);let k="";S.countIncludePad?k+=`value /= float(${O});`:k+=`value /= float(${O} - pad);`;const D=`
+        ${e(g[0].dims,S,"value += _X(x);",k,"0.0")}
+      `;return Object.assign(Object.assign({},y),{output:{dims:P,type:g[0].type,textureType:b.TextureType.unpacked},shaderSource:D})};o.globalAveragePool=(g,y,x)=>{n(y);const E={name:"GlobalAveragePool",inputNames:["X"],inputTypes:[b.TextureType.unpacked],cacheHint:`${x.countIncludePad}`};return[g.run(Object.assign(Object.assign({},E),{get:()=>c(y,E,!0,x)}),y)]},o.parseGlobalAveragePoolAttributes=g=>{const y=g.attributes.getInt("count_include_pad",0)!==0;return(0,l.createAttributeWithCacheKey)({autoPad:"",ceilMode:0,countIncludePad:y,kernelShape:[],strides:[],pads:[]})},o.maxPool=(g,y,x)=>{n(y);const E={name:"MaxPool",inputNames:["X"],inputTypes:[b.TextureType.unpacked],cacheHint:x.cacheKey};return[g.run(Object.assign(Object.assign({},E),{get:()=>m(y,E,!1,x)}),y)]},o.parseMaxPoolAttributes=g=>{const y=g.attributes.getString("auto_pad","NOTSET"),x=g.attributes.getInt("ceil_mode",0),E=g.attributes.getInts("kernel_shape"),S=g.attributes.getInts("strides",[]),P=g.attributes.getInts("pads",[]),O=g.attributes.getInt("storage_order",0),k=g.attributes.getInts("dilations",[]);if(O!==0)throw new Error("column major storage order is not yet supported for MaxPool");if(x!==0)throw new Error("using ceil() in shape computation is not yet supported for MaxPool");return(0,l.createAttributeWithCacheKey)({autoPad:y,ceilMode:x,countIncludePad:!1,kernelShape:E,strides:S,pads:P,storageOrder:O,dilations:k})};const m=(g,y,x,E)=>{const[S,P]=_(g,E,x),O=`
+      ${e(g[0].dims,S,`
+      value = max(_X(x), value);
+    `,"","-1e5")}
+    `;return Object.assign(Object.assign({},y),{output:{dims:P,type:g[0].type,textureType:b.TextureType.unpacked},shaderSource:O})},_=(g,y,x)=>{const E=g[0].dims.slice(),S=Object.hasOwnProperty.call(y,"dilations"),P=y.kernelShape.slice(),O=y.strides.slice(),k=S?y.dilations.slice():[],D=y.pads.slice();p.PoolConvUtil.adjustPoolAttributes(x,E,P,O,k,D);const C=p.PoolConvUtil.computePoolOutputShape(x,E,O,k,P,D,y.autoPad),A=Object.assign({},y);return S?Object.assign(A,{kernelShape:P,strides:O,pads:D,dilations:k,cacheKey:y.cacheKey}):Object.assign(A,{kernelShape:P,strides:O,pads:D,cacheKey:y.cacheKey}),[A,C]},f={autoPad:"",ceilMode:0,countIncludePad:!1,kernelShape:[],strides:[],pads:[],storageOrder:0,dilations:[],cacheKey:""},u={name:"GlobalMaxPool",inputNames:["X"],inputTypes:[b.TextureType.unpacked]};o.globalMaxPool=(g,y)=>(n(y),[g.run(Object.assign(Object.assign({},u),{get:()=>m(y,u,!0,f)}),y)]);const n=g=>{if(!g||g.length!==1)throw new Error("Pool ops requires 1 input.");if(g[0].type!=="float32"&&g[0].type!=="float64")throw new Error("Invalid input type.")},e=(g,y,x,E,S)=>{const P=g.length;if(y.kernelShape.length<=2){const O=y.kernelShape[y.kernelShape.length-1],k=y.strides[y.strides.length-1],D=y.pads[y.pads.length/2-1],C=y.pads[y.pads.length-1],A=g[P-1];let $="",W="",K="";if($=D+C!==0?`
+          for (int i = 0; i < ${O}; i++) {
+            x[${P} - 1] = indices[${P} - 1] * ${k} - ${D} + i;
+            if (x[${P} - 1] < 0 || x[${P} - 1] >= ${A}) {
+              pad++;
+              continue;
+            }
+            ${x}
+          }`:`
+          for (int i = 0; i < ${O}; i++) {
+            x[${P} - 1] = indices[${P} - 1] * ${k} - ${D} + i;
+            ${x}
+          }`,y.kernelShape.length===2){const Y=y.kernelShape[y.kernelShape.length-2],q=y.strides[y.strides.length-2],se=y.pads[y.pads.length/2-2],F=y.pads[y.pads.length-2],B=g[P-2];W=se+F!==0?`
+            for (int j = 0; j < ${Y}; j++) {
+              x[${P} - 2] = indices[${P} - 2] * ${q} - ${se} + j;
+              if (x[${P} - 2] < 0 || x[${P} - 2] >= ${B}) {
+                pad+= ${O};
+                continue;
+              }
+          `:`
+            for (int j = 0; j < ${Y}; j++) {
+              x[${P} - 2] = indices[${P} - 2] * ${q} - ${se} + j;
+            `,K=`
+          }
+        `}return`
+        float process(int indices[${P}]) {
+          int x[${P}];
+          copyVec(indices, x);
+
+          float value = ${S};
+          int pad = 0;
+          ${W}
+          ${$}
+          ${K}
+          ${E}
+          return value;
+        }
+      `}{const O=p.ShapeUtil.size(y.kernelShape),k=p.ShapeUtil.computeStrides(y.kernelShape),D=k.length,C=y.pads.length,A=s(D),$=a(g,"inputDims"),W=a(y.pads,"pads"),K=a(k,"kernelStrides"),Y=a(y.strides,"strides");let q="";return q=y.pads.reduce((se,F)=>se+F)?`
+            if (x[j] >= inputDims[j] || x[j] < 0) {
+              pad++;
+              isPad = true;
+              break;
+            }
+          }
+          if (!isPad) {
+            ${x}
+          }`:`
+          }
+          ${x}
+        `,`
+        ${A}
+        float process(int indices[${P}]) {
+          int x[${P}];
+          copyVec(indices, x);
+          int offset[${D}];
+          int pads[${C}];
+          int inputDims[${P}];
+          int kernelStrides[${D}];
+          int strides[${D}];
+          ${W}
+          ${$}
+          ${Y}
+          ${K}
+
+          float value = ${S};
+          int pad = 0;
+          bool isPad = false;
+          for (int i = 0; i < ${O}; i++) {
+            offsetToIndices(i, kernelStrides, offset);
+            isPad = false;
+            for (int j = ${P} - ${D}; j < ${P}; j++) {
+              x[j] = indices[j] * strides[j - ${P} + ${D}]
+                + offset[j - ${P} + ${D}] - pads[j - 2];
+              ${q}
+          }
+          ${E}
+
+          return value;
+        }
+      `}},a=(g,y)=>{let x="";for(let E=0;E<g.length;E++)x+=`
+      ${y}[${E}] = ${g[E]};
+    `;return x},s=g=>`
+  void offsetToIndices(int offset, int[${g}] strides, out int[${g}] indices) {
+    if (${g} == 0) {
+      return;
+    }
+    for (int i = 0; i < ${g} - 1; ++i) {
+      indices[i] = offset / strides[i];
+      offset -= indices[i] * strides[i];
+    }
+    indices[${g} - 1] = offset;
+  }`},4939:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.reduceLogSumSquare=o.reduceLogSum=o.reduceProd=o.reduceMin=o.reduceMax=o.reduceMean=o.reduceSum=o.parseReduceAttributes=void 0;const l=d(246),p=d(782),b=d(2517),c=d(2039),m=(u,n,e,a,s)=>{f(n);const g={name:a,inputNames:["A"],inputTypes:[c.TextureType.unpacked]};return[u.run(Object.assign(Object.assign({},g),{cacheHint:e.cacheKey,get:()=>_(u,n,e,a,s,g)}),n)]};o.parseReduceAttributes=u=>{const n=u.attributes.getInts("axes",[]),e=u.attributes.getInt("keepdims",1)===1;return(0,l.createAttributeWithCacheKey)({axes:n,keepDims:e})};const _=(u,n,e,a,s,g)=>{const y=[],x=n[0].dims.length||1,E=[],S=b.ShapeUtil.normalizeAxes(e.axes,n[0].dims.length),P=s(n,S);let O=P[1];for(let D=0;D<n[0].dims.length;D++)S.indexOf(D)>=0||S.length===0?(e.keepDims&&y.push(1),O=`
+          for(int j${D} = 0; j${D} < ${n[0].dims[D]}; j${D}++) {
+            inputIdx[${D}] = j${D};
+            ${O}
+          }`):(E.push(`inputIdx[${D}] = outputIdx[${y.length}];`),y.push(n[0].dims[D]));const k=`
+      float process(int outputIdx[${y.length||1}]) {
+        float value;                 // final result
+        int inputIdx[${x}];      // addressing input data
+        ${E.join(`
+`)}
+        ${P[0]}       // init ops for reduce max/min
+        ${O}
+        ${P[2]}       // final computation for reduce mean
+        return value;
+      }`;return Object.assign(Object.assign({},g),{output:{dims:y,type:n[0].type,textureType:c.TextureType.unpacked},shaderSource:k})},f=u=>{if(!u||u.length!==1)throw new Error("Reduce op requires 1 input.");if(p.NUMBER_TYPES.indexOf(u[0].type)===-1)throw new Error("Invalid input type.")};o.reduceSum=(u,n,e)=>m(u,n,e,"ReduceSum",()=>["value = 0.0;","value += _A(inputIdx);",""]),o.reduceMean=(u,n,e)=>m(u,n,e,"ReduceMean",(a,s)=>{let g=1;for(let y=0;y<a[0].dims.length;y++)(s.indexOf(y)>=0||s.length===0)&&(g*=a[0].dims[y]);return["value = 0.0;","value += _A(inputIdx);",`value /= ${g}.;`]}),o.reduceMax=(u,n,e)=>m(u,n,e,"ReduceMax",(a,s)=>{const g=[];for(let y=0;y<a[0].dims.length;y++)(s.indexOf(y)>=0||s.length===0)&&g.push(`inputIdx[${y}] = 0;`);return[`${g.join(`
+`)}
+value = _A(inputIdx);`,"value = max(value, _A(inputIdx));",""]}),o.reduceMin=(u,n,e)=>m(u,n,e,"ReduceMin",(a,s)=>{const g=[];for(let y=0;y<a[0].dims.length;y++)(s.indexOf(y)>=0||s.length===0)&&g.push(`inputIdx[${y}] = 0;`);return[`${g.join(`
+`)}
+value = _A(inputIdx);`,"value = min(value, _A(inputIdx));",""]}),o.reduceProd=(u,n,e)=>m(u,n,e,"ReduceProd",()=>["value = 1.0;","value *= _A(inputIdx);",""]),o.reduceLogSum=(u,n,e)=>m(u,n,e,"ReduceLogSum",()=>["value = 0.0;","value += _A(inputIdx);","value = log(value);"]),o.reduceLogSumSquare=(u,n,e)=>m(u,n,e,"ReduceLogSumSquare",()=>["float t; value = 0.0;","t = _A(inputIdx); value += t * t;",""])},7019:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.isReshapeCheap=o.processDims3D=o.createPackedReshape3DProgramInfoLoader=void 0;const l=d(2517),p=d(5060),b=d(2039),c=d(2827);o.createPackedReshape3DProgramInfoLoader=(m,_,f)=>{const u=(n=>({name:"Reshape (packed)",inputTypes:[b.TextureType.packed],inputNames:["A"],cacheHint:`${n}`}))(f);return Object.assign(Object.assign({},u),{get:()=>((n,e,a,s)=>{const g=e.dims,y=s;let x="";for(let P=0;P<4;P++){let O="";switch(P){case 0:O="outputCoords = rc;";break;case 1:O="outputCoords = ivec3(rc.x, rc.y+1, rc.z);";break;case 2:O="outputCoords = ivec3(rc.x, rc.y, rc.z+1);";break;case 3:O="outputCoords = ivec3(rc.x, rc.y+1, rc.z+1);";break;default:throw new Error}x+=`
+        ${O}
+        ${P>0?"if(outputCoords.y < rows && outputCoords.z < cols){":""}
+          int flattenedIndex = getFlattenedIndex(outputCoords);
+
+          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flattenedIndex);
+          vec2 innerDims = vec2(float(inputRC.y),float(inputRC.z));
+
+          result[${P}] = getChannel(getA(inputRC.x, inputRC.y, inputRC.z), innerDims);
+
+        ${P>0?"}":""}
+      `}const E=(0,p.getGlsl)(n.session.backend.glContext.version),S=`
+      ${function(P){const O=l.ShapeUtil.computeStrides(P),k=["b","r","c"],D="index";return`
+    ivec3 inputCoordsFromReshapedOutCoords(int index) {
+      ${O.map((C,A)=>`int ${k[A]} = ${D} / ${C}; ${A===O.length-1?`int ${k[A+1]} = ${D} - ${k[A]} * ${C}`:`index -= ${k[A]} * ${C}`};`).join("")}
+      return ivec3(b, r, c);
+    }
+  `}(g)}
+      ${function(P){const O=l.ShapeUtil.computeStrides(P);return`
+  int getFlattenedIndex(ivec3 coords) {
+    // reverse y, z order
+    return coords.x * ${O[0]} + coords.z * ${O[1]} + coords.y;
+  }
+`}(y)}
+      ${(0,c.unpackFromChannel)()}
+
+      void main() {
+        ivec3 rc = getOutputCoords();
+
+        vec4 result = vec4(0.0);
+
+        ivec3 outputCoords;
+        int rows = ${y[2]};
+        int cols = ${y[1]};
+
+        ${x}
+        ${E.output} = result;
+      }
+    `;return Object.assign(Object.assign({},a),{output:{dims:y,type:e.type,textureType:b.TextureType.packed},shaderSource:S,hasMain:!0})})(m,_,u,f)})},o.processDims3D=function(m){if(m.length===0)return[1,1,1];let _=1;for(let f=0;f<m.length-2;++f)_*=m[f];return[_,m.length>1?m[m.length-2]:1,m[m.length-1]]},o.isReshapeCheap=function(m,_){let f=!1;return f=m.length===0||_.length===0||(m.length<2||_.length<2?m[m.length-1]===_[_.length-1]:m[m.length-1]===_[_.length-1]&&m[m.length-2]===_[_.length-2]),f}},718:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.reshape=void 0;const l=d(2517);o.reshape=(p,b)=>{const c=l.ShapeUtil.calculateReshapedDims(b[0].dims,b[1].integerData);return p.session.pack?[p.reshapePacked(b[0],c)]:[p.reshapeUnpacked(b[0],c)]}},2268:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseResizeAttributesV11=o.parseResizeAttributesV10=o.resize=void 0;const l=d(5060),p=d(2039),b=d(9390),c=d(2827),m=d(9793),_={name:"Resize",inputNames:["A"],inputTypes:[p.TextureType.packed]};o.resize=(a,s,g)=>((0,m.validateInputs)(s,g),[a.run(Object.assign(Object.assign({},_),{cacheHint:g.cacheKey,get:()=>f(a,s,g)}),s)]),o.parseResizeAttributesV10=a=>(0,m.parseUpsampleAttributes)(a,10),o.parseResizeAttributesV11=a=>(0,m.parseUpsampleAttributes)(a,11);const f=(a,s,g)=>{const y=(0,l.getGlsl)(a.session.backend.glContext.version),[x,E]=u(s,g);if(x.every(q=>q===1)&&g.coordinateTransformMode!=="tf_crop_and_resize")return Object.assign(Object.assign({},_),{output:{dims:E,type:s[0].type,textureType:p.TextureType.packed},hasMain:!0,shaderSource:`void main() {
+                    vec4 v = ${y.texture2D}(X, TexCoords);
+                    ${y.output} = v;
+                }`});const S=E.length;if(S<2)throw new Error(`output dimension should be at least 2, but got ${S}`);const P=E[S-2],O=E[S-1],k=s[0].dims;if(S!==k.length)throw new Error(`output dimension should match input ${k.length}, but got ${S}`);const D=k[S-2],C=k[S-1],A=x[S-2],$=x[S-1];let W="";if(g.mode!=="linear")throw new Error(`resize (packed) does not support mode: '${g.mode}'`);switch(g.coordinateTransformMode){case"asymmetric":W=`
+                    vec4 getSourceFracIndex(ivec4 coords) {
+                        return vec4(coords) / scaleWHWH;
+                    }
+                `;break;case"half_pixel":W=`
+                    vec4 getSourceFracIndex(ivec4 coords) {
+                        return (vec4(coords) + 0.5) / scaleWHWH - 0.5;
+                    }
+                `;break;case"pytorch_half_pixel":W=`
+                    vec4 getSourceFracIndex(ivec4 coords) {
+                        vec4 fcoords = vec4(coords);
+                        return vec4(
+                            ${O}.0 > 1.0 ? (fcoords.x + 0.5) / scaleWHWH.x - 0.5 : 0.0,
+                            ${P}.0 > 1.0 ? (fcoords.y + 0.5) / scaleWHWH.y - 0.5 : 0.0,
+                            ${O}.0 > 1.0 ? (fcoords.z + 0.5) / scaleWHWH.z - 0.5 : 0.0,
+                            ${P}.0 > 1.0 ? (fcoords.w + 0.5) / scaleWHWH.w - 0.5 : 0.0
+                          );
+                    }
+                `;break;case"align_corners":W=`
+                    vec4 getSourceFracIndex(ivec4 coords) {
+                        vec4 resized = vec4(${O}.0 - 1.0, ${P}.0 - 1.0, ${O}.0 - 1.0,
+                            ${P}.0 - 1.0);
+                        vec4 original = vec4(${C}.0 - 1.0, ${D}.0 - 1.0, ${C}.0 - 1.0,
+                            ${D}.0 - 1.0);
+                        vec4 new_scale = original / resized;
+                        return vec4(coords) * new_scale;
+                    }
+                `;break;default:throw new Error(`resize (packed) does not support coordinateTransformMode:                                 '${g.coordinateTransformMode}'`)}const K=(0,b.getCoordsDataType)(S),Y=`
+            const vec2 inputWH = vec2(${D}.0, ${C}.0);
+            const vec4 scaleWHWH = vec4(float(${A}), float(${$}), float(${A}), float(${$}));
+            ${(0,c.unpackFromChannel)()}
+            ${W}
+            float getAValue(int x10, int r, int c, int d) {
+                return getChannel(getA(x10, r, c, d), vec2(c, d));
+            }
+            void main() {
+                ${K} 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 < ${P-1};
+                bool hasNextCol = rc.z < ${O-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);
+
+                ${y.output} = vec4(newValue);
+            }
+        `;return Object.assign(Object.assign({},_),{output:{dims:E,type:s[0].type,textureType:p.TextureType.packed},hasMain:!0,shaderSource:Y})},u=(a,s)=>{const g=a[0].dims;let y,x=s.scales;if(x.length===0){const S=a[s.scalesInputIdx];if(S&&S.size!==0){if(a[s.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");x=n(S,s.mode,s.isResize)}else{const P=a[s.sizesInputIdx];if(!P||P.size===0)throw new Error("Either scales or sizes MUST be provided as input.");y=Array.from(P.integerData),x=e(y,g,s.mode,s.isResize)}}else if(a[s.sizesInputIdx])throw new Error("Only one of scales or sizes must be provided as input.");const E=y||g.map((S,P)=>Math.floor(S*x[P]));return[x,E]},n=(a,s,g)=>{const y=Array.from(a.floatData);return(0,m.scalesValidation)(y,s,g),y},e=(a,s,g,y)=>{const x=s.length,E=new Array(x);for(let S=0,P=x;S<P;S++)if(s[S]===0){if(a[S]!==0)throw new Error("Input dim is zero but required output dim is non-zero.");E[S]=1}else E[S]=a[S]/s[S];return(0,m.scalesValidation)(E,g,y),E}},8117:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.shape=void 0;const l=d(9162);o.shape=(b,c)=>(p(c),[new l.Tensor([c[0].dims.length],"int32",void 0,void 0,new Int32Array(c[0].dims))]);const p=b=>{if(!b||b.length!==1)throw new Error("Shape requires 1 input.")}},2278:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.sliceV10=o.parseSliceAttributes=o.slice=void 0;const l=d(246),p=d(782),b=d(2517),c=d(2039),m={name:"Slice",inputNames:["A"],inputTypes:[c.TextureType.unpacked]};o.slice=(e,a,s)=>(f(a),[e.run(Object.assign(Object.assign({},m),{cacheHint:s.cacheKey,get:()=>_(e,a[0],s)}),a)]),o.parseSliceAttributes=e=>{const a=e.attributes.getInts("starts"),s=e.attributes.getInts("ends"),g=e.attributes.getInts("axes",[]);return(0,l.createAttributeWithCacheKey)({starts:a,ends:s,axes:g})};const _=(e,a,s)=>{const g=s.axes.length===0?a.dims.slice(0).map((k,D)=>D):s.axes,y=b.ShapeUtil.normalizeAxes(g,a.dims.length),x=s.starts.map((k,D)=>k>a.dims[y[D]]-1?a.dims[y[D]]:b.ShapeUtil.normalizeAxis(k,a.dims[y[D]])),E=s.ends.map((k,D)=>k>a.dims[y[D]]-1?a.dims[y[D]]:b.ShapeUtil.normalizeAxis(k,a.dims[y[D]])),S=a.dims.slice(),P=[];for(let k=0;k<y.length;k++)S[y[k]]=E[k]-x[k],x[k]>0&&P.push(`outputIdx[${y[k]}] += ${x[k]};`);const O=`
+      float process(int outputIdx[${S.length}]) {
+        ${P.join(`
+      `)}
+        return _A(outputIdx);
+      }`;return Object.assign(Object.assign({},m),{output:{dims:S,type:a.type,textureType:c.TextureType.unpacked},shaderSource:O})},f=e=>{if(!e||e.length!==1)throw new Error("Slice requires 1 input.");if(p.NUMBER_TYPES.indexOf(e[0].type)===-1)throw new Error("Invalid input type.")};o.sliceV10=(e,a)=>{n(a);const s=u(e,a);return[e.run(Object.assign(Object.assign({},m),{cacheHint:s.cacheKey,get:()=>_(e,a[0],s)}),[a[0]])]};const u=(e,a)=>{if(!e.session.isInitializer(a[1].dataId)||!e.session.isInitializer(a[2].dataId)||a.length>=4&&!e.session.isInitializer(a[3].dataId)||a.length>=5&&!e.session.isInitializer(a[4].dataId))throw new Error("dynamic slice attributes are not allowed");if(a.length>=5&&a[4].integerData.some(x=>x!==1))throw new Error("currently non-1 steps is not supported for Slice");const s=Array.from(a[1].integerData),g=Array.from(a[2].integerData),y=a.length>=4?Array.from(a[3].integerData):[];return{starts:s,ends:g,axes:y,cacheKey:`${y};${s};${g}`}},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:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.softmaxV13=o.parseSoftmaxAttributesV13=o.parseSoftmaxAttributes=o.softmax=void 0;const l=d(246),p=d(2517),b=d(5060),c=d(2039),m=d(3738),_={name:"SoftmaxComputeMax",inputNames:["A"],inputTypes:[c.TextureType.unpacked]},f={name:"SoftmaxComputeScale",inputNames:["A","Max"],inputTypes:[c.TextureType.unpacked,c.TextureType.unpacked]},u={name:"SoftMax",inputNames:["A","Max","Norm"],inputTypes:[c.TextureType.unpacked,c.TextureType.unpacked,c.TextureType.unpacked]};o.softmax=(y,x,E)=>{g(x);const S=x[0].dims.slice(),P=p.ShapeUtil.normalizeAxis(E.axis,S.length),O=p.ShapeUtil.sizeToDimension(S,P),k=p.ShapeUtil.sizeFromDimension(S,P);return n(y,x,E,O,k)},o.parseSoftmaxAttributes=y=>(0,l.createAttributeWithCacheKey)({axis:y.attributes.getInt("axis",1)}),o.parseSoftmaxAttributesV13=y=>(0,l.createAttributeWithCacheKey)({axis:y.attributes.getInt("axis",-1)}),o.softmaxV13=(y,x,E)=>{g(x);const S=x[0].dims.slice(),P=p.ShapeUtil.normalizeAxis(E.axis,S.length),O=S.length,k=P!==O-1,D=[];let C,A=[],$=[];k&&(A=Array.from({length:O}).map((q,se)=>se),A[P]=O-1,A[O-1]=P,A.map(q=>D.push(S[q])),C=(0,l.createAttributeWithCacheKey)({perm:A}),$=(0,m.transpose)(y,x,C));const W=k?p.ShapeUtil.sizeToDimension(D,O-1):p.ShapeUtil.sizeToDimension(S,O-1),K=k?p.ShapeUtil.sizeFromDimension(D,O-1):p.ShapeUtil.sizeFromDimension(S,O-1),Y=n(y,k?$:x,E,W,K);return k?(0,m.transpose)(y,Y,C):Y};const n=(y,x,E,S,P)=>{const O=e(y,x[0],S,P,[S]),k=y.run(Object.assign(Object.assign({},_),{cacheHint:E.cacheKey,get:()=>O}),x),D=a(y,x[0],S,P,O.output.dims,[S]),C=y.run(Object.assign(Object.assign({},f),{cacheHint:E.cacheKey,get:()=>D}),[x[0],k]),A=s(y,x[0],S,P,O.output.dims,D.output.dims);return[y.run(Object.assign(Object.assign({},u),{cacheHint:E.cacheKey,get:()=>A}),[x[0],k,C])]},e=(y,x,E,S,P)=>{const[O,k]=y.calculateTextureWidthAndHeight(x.dims,c.TextureType.unpacked),D=P.length;if(E<1||S<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(P.length!==1)throw new Error("Dimensionality of the output should be 1");if(P[0]!==E)throw new Error("Shape of the output should be equal to logical row count");const C=(0,b.getGlsl)(y.session.backend.glContext.version),A=`
+      float process(int[${D}] indices) {
+        int logical_row_start_offset = indices[0] * ${S};
+
+        float max = getColorAsFloat(${C.texture2D}(A, offsetToCoords(logical_row_start_offset, ${O},
+        ${k} )));
+        for(int i=1; i<${S}; ++i)
+        {
+          float current = getColorAsFloat(${C.texture2D}(A, offsetToCoords(logical_row_start_offset + i,
+            ${O}, ${k})));
+          if(current > max)
+          max = current;
+        }
+
+        return max;
+      }`;return Object.assign(Object.assign({},_),{output:{dims:P,type:x.type,textureType:c.TextureType.unpacked},shaderSource:A})},a=(y,x,E,S,P,O)=>{const[k,D]=y.calculateTextureWidthAndHeight(x.dims,c.TextureType.unpacked),C=O.length;if(E<1||S<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(O.length!==1)throw new Error("Dimensionality of the output should be 1");if(O[0]!==E)throw new Error("Shape of the output should be equal to logical row count");if(P.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(P[0]!==E)throw new Error("Shape of the intermediate results should be equal to logical row count");const A=`
+      float process(int[${C}] indices) {
+        int logical_row_start_offset = indices[0] * ${S};
+
+        float norm_factor = 0.0;
+        float max = _Max(indices);
+        for(int i=0; i<${S}; ++i)
+        {
+          norm_factor += exp(getColorAsFloat(${(0,b.getGlsl)(y.session.backend.glContext.version).texture2D}(A, offsetToCoords(logical_row_start_offset + i,
+            ${k}, ${D}))) - max);
+        }
+
+        return norm_factor;
+      }`;return Object.assign(Object.assign({},f),{output:{dims:O,type:x.type,textureType:c.TextureType.unpacked},shaderSource:A})},s=(y,x,E,S,P,O)=>{const[k,D]=y.calculateTextureWidthAndHeight(x.dims,c.TextureType.unpacked),C=x.dims.length;if(E<1||S<1)throw new Error("Logical row count N and feature count D must be greater than or equal to 1");if(P.length!==1||O.length!==1)throw new Error("Dimensionality of the intermediate results should be 1");if(P[0]!==E||O[0]!==E)throw new Error("Shape of the intermediate results should be equal to logical row count");const A=`
+      float process(int[${C}] indices) {
+
+      // get offset of current logical tensor index from the 2-D texture coordinates (TexCoords)
+      int offset = coordsToOffset(TexCoords, ${k}, ${D});
+
+      //determine the logical row for this index
+      int logical_row_index[1];
+      logical_row_index[0] = offset / ${S};
+
+      float norm_factor = _Norm(logical_row_index);
+
+      // avoid possible division by 0
+      // if norm_facor is 0, all elements are zero
+      // if so, return 0
+      if(norm_factor == 0.0)
+        return 0.0;
+
+      return exp(_A(indices) - _Max(logical_row_index)) / norm_factor;
+    }`;return Object.assign(Object.assign({},u),{output:{dims:x.dims,type:x.type,textureType:c.TextureType.unpacked},shaderSource:A})},g=y=>{if(!y||y.length!==1)throw new Error("Softmax requires 1 input.");if(y[0].type!=="float32"&&y[0].type!=="float64")throw new Error("Invalid input type")}},5975:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseSplitAttributes=o.split=void 0;const l=d(246),p=d(2517),b=d(2039),c={name:"Split",inputNames:["A"],inputTypes:[b.TextureType.unpacked]};o.split=(u,n,e)=>{f(n);const a=p.ShapeUtil.normalizeAxis(e.axis,n[0].dims.length),s=m(u,n,a,e),g=[];for(let y=0;y<s;++y)g.push(u.run(Object.assign(Object.assign({},c),{cacheHint:`${e.cacheKey};${y}`,get:()=>_(u,n[0],e,a,y)}),n));return g},o.parseSplitAttributes=u=>{const n=u.attributes.getInt("axis",0),e=u.attributes.getInts("split",[]),a=u.outputs.length;return(0,l.createAttributeWithCacheKey)({axis:n,split:e,numOutputs:a})};const m=(u,n,e,a)=>{const[,s]=p.SplitUtil.splitShape(n[0].dims,e,a.split,a.numOutputs);return s.length},_=(u,n,e,a,s)=>{const[g,y]=p.SplitUtil.splitShape(n.dims,a,e.split,e.numOutputs),x=y[s],E=g[s],S=`
+      float process(int indices[${E.length}]) {
+        indices[${a}] += ${x};
+        return _A(indices);
+      }
+    `;return Object.assign(Object.assign({},c),{cacheHint:`${e.cacheKey}:${s}`,output:{dims:E,type:n.type,textureType:b.TextureType.unpacked},shaderSource:S})},f=u=>{if(!u||u.length!==1)throw new Error("Split requires one input.");if(u[0].type!=="int8"&&u[0].type!=="uint8"&&u[0].type!=="int16"&&u[0].type!=="uint16"&&u[0].type!=="int32"&&u[0].type!=="uint32"&&u[0].type!=="float32"&&u[0].type!=="float64"&&u[0].type!=="bool")throw new Error("Invalid input type.")}},3933:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseSqueezeAttributes=o.squeezeV13=o.squeeze=void 0;const l=d(2517);o.squeeze=(c,m,_)=>{p(m);const f=l.ShapeUtil.squeezeShape(m[0].dims,_);return[c.reshapeUnpacked(m[0],f)]},o.squeezeV13=(c,m)=>(b(m),(0,o.squeeze)(c,[m[0]],Array.from(m[1].integerData))),o.parseSqueezeAttributes=c=>c.attributes.getInts("axes");const p=c=>{if(!c||c.length!==1)throw new Error("Squeeze requires 1 input.");if(c[0].type==="string")throw new Error("invalid input tensor types.")},b=c=>{if(!c||c.length!==2)throw new Error("Squeeze requires 2 inputs.");if(c[1].type!=="int32")throw new Error("Invalid input type.")}},6558:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.sum=void 0;const l=d(5060),p=d(2039);o.sum=(m,_)=>{c(_);const f={name:"Sum",inputNames:_.map((u,n)=>`X${n}`),inputTypes:new Array(_.length).fill(p.TextureType.unpacked)};return[m.run(Object.assign(Object.assign({},f),{get:()=>b(m,_,f)}),_)]};const b=(m,_,f)=>{const u=(0,l.getGlsl)(m.session.backend.glContext.version),n=_[0].dims.slice(),e=`
+      void main() {
+        vec4 result = ${_.map((a,s)=>`${u.texture2D}(X${s},TexCoords)`).join(" + ")};
+        ${u.output} = result;
+      }
+    `;return Object.assign(Object.assign({},f),{output:{dims:n,type:_[0].type,textureType:p.TextureType.unpacked},hasMain:!0,shaderSource:e})},c=m=>{if(!m||m.length===0)throw new Error("Sum requires inputs.");const _=m[0].dims.length;for(let f=1;f<m.length;f++){if(_!==m[f].dims.length)throw new Error("Input shapes are mismatched.");for(let u=0;u<_;u++)if(m[0].dims[u]!==m[f].dims[u])throw new Error("Input shapes are not matched.")}if(m[0].type!=="float32"&&m[0].type!=="float64")throw new Error("Invalid input type.");for(let f=1;f<m.length;f++)if(m[0].type!==m[f].type)throw new Error("Input types are not matched.")}},5723:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.tile=void 0;const l=d(782),p=d(2039);o.tile=(m,_)=>{c(_);const f={name:"Tile",inputNames:["A"],inputTypes:[p.TextureType.unpacked]};return[m.run(Object.assign(Object.assign({},f),{get:()=>b(m,_,f)}),_)]};const b=(m,_,f)=>{const u=_[0].dims.slice(),n=new Array(u.length),e=[];for(let g=0;g<u.length;g++)n[g]=u[g]*_[1].numberData[g],e.push(`inputIdx[${g}] = int(mod(float(outputIdx[${g}]), ${u[g]}.));`);const a=n.length,s=`
+      float process(int outputIdx[${a}]) {
+        int inputIdx[${a}];
+        ${e.join(`
+`)}
+        return _A(inputIdx);
+      }
+    `;return Object.assign(Object.assign({},f),{output:{dims:n,type:_[0].type,textureType:p.TextureType.unpacked},shaderSource:s})},c=m=>{if(!m||m.length!==2)throw new Error("Tile requires 2 input.");if(m[1].dims.length!==1)throw new Error("The second input shape must 1 dimension.");if(m[1].dims[0]!==m[0].dims.length)throw new Error("Invalid input shape.");if(l.NUMBER_TYPES.indexOf(m[0].type)===-1)throw new Error("Invalid input type.");if(m[1].type!=="int32"&&m[1].type!=="int16")throw new Error("Invalid repeat type.")}},3738:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseTransposeAttributes=o.transpose=void 0;const l=d(246),p=d(2517),b=d(2039),c={name:"Transpose",inputNames:["A"],inputTypes:[b.TextureType.unpacked]};o.transpose=(e,a,s)=>(n(a),[e.run(Object.assign(Object.assign({},c),{cacheHint:s.cacheKey,get:()=>m(e,a[0],s.perm)}),a)]),o.parseTransposeAttributes=e=>(0,l.createAttributeWithCacheKey)({perm:e.attributes.getInts("perm",[])});const m=(e,a,s)=>{const g=a.dims;s=_(g,s);const y=f(g,s),x=g.length,E=`
+      ${u("perm",s,x)}
+      float process(int indices[${x}]) {
+        int a[${x}];
+        perm(a, indices);
+        return _A(a);
+      }`;return Object.assign(Object.assign({},c),{output:{dims:y,type:a.type,textureType:b.TextureType.unpacked},shaderSource:E})},_=(e,a)=>(a&&a.length!==e.length&&(a=[...e.keys()].reverse()),a),f=(e,a)=>(a=_(e,a),p.ShapeUtil.sortBasedOnPerm(e,a)),u=(e,a,s)=>{const g=[];g.push(`void ${e}(out int a[${s}], int src[${s}]) {`);for(let y=0;y<s;++y)g.push(`	a[${a[y]}]=src[${y}];`);return g.push("	}"),g.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:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.encodeAsUint8=void 0;const l=d(5060),p=d(2039);o.encodeAsUint8=(b,c)=>{const m=c.shape,_=(0,l.getGlsl)(b.session.backend.glContext.version),f=`
+    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 = ${_.texture2D}(X,TexCoords).r;
+      ${_.output} = encodeAsUint8(value);
+    }`,u={name:"Uint8Encode",inputTypes:[p.TextureType.unpacked],inputNames:["X"],output:{dims:m,type:c.tensor.type,textureType:p.TextureType.downloadUint8AsFloat},shaderSource:f,hasMain:!0};return b.executeProgram(u,[c.tensor])}},4909:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.tanh=o.tan=o.sqrt=o.sin=o.sigmoid=o.relu=o.not=o.neg=o.log=o.parseLeakyReluAttributes=o.leakyRelu=o.identity=o.floor=o.exp=o.parseEluAttributes=o.elu=o.cos=o.ceil=o.clipV11=o.parseClipAttributes=o.clip=o.atan=o.asin=o.acos=o.abs=o.glslTanh=o.glslTan=o.glslSqrt=o.glslSigmoid=o.glslRelu=o.glslSin=o.glslNot=o.glslNeg=o.glslLog=o.glslLeakyRelu=o.glslIdentity=o.glslClip=o.glslFloor=o.glslExp=o.glslElu=o.glslCos=o.glslCeil=o.glslAtan=o.glslAsin=o.glslAcos=o.glslAbs=void 0;const l=d(246),p=d(2517),b=d(8520),c=d(5060),m=d(2039);function _(){return Y("abs")}function f(){return Y("acos")}function u(){return Y("asin")}function n(){return Y("atan")}function e(){return Y("ceil")}function a(){return Y("cos")}function s(F){const B="elu";return{body:`
+  const float alpha = float(${F});
+
+  float ${B}_(float a) {
+    return a >= 0.0 ? a: (exp(a) - 1.0) * alpha;
+  }
+  vec4 ${B}_(vec4 v) {
+    return vec4(${B}_(v.x), ${B}_(v.y), ${B}_(v.z), ${B}_(v.w));
+  }
+  `,name:B,type:b.FunctionType.ValueBased}}function g(){return Y("exp")}function y(){return Y("floor")}function x(F,B){const fe="clip";return{body:`
+  const float min = float(${F});
+  const float max = float(${B});
+
+  float ${fe}_(float a) {
+    return clamp(a, min, max);
+  }
+  vec4 ${fe}_(vec4 v) {
+    return clamp(v, min, max);
+  }
+  `,name:fe,type:b.FunctionType.ValueBased}}function E(){const F="indentity";return{body:`
+  float ${F}_(float a) {
+    return a;
+  }
+  vec4 ${F}_(vec4 v) {
+    return v;
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function S(F){const B="leakyRelu";return{body:`
+  const float alpha = float(${F});
+
+  float ${B}_(float a) {
+    return a < 0.0 ? a * alpha : a;
+  }
+  vec4 ${B}_(vec4 v) {
+    return vec4(${B}_(v.x), ${B}_(v.y), ${B}_(v.z), ${B}_(v.w));
+  }
+  `,name:B,type:b.FunctionType.ValueBased}}function P(){return Y("log")}function O(){const F="neg";return{body:`
+  float ${F}_(float a) {
+    return -a;
+  }
+  vec4 ${F}_(vec4 v) {
+    return -v;
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function k(){const F="not";return{body:`
+  float ${F}_(float a) {
+    return float( ! bool(a) );
+  }
+  bool ${F}_(bool a) {
+    return !a;
+  }
+  vec4 ${F}_(vec4 v) {
+    return vec4(!bool(v.x), !bool(v.y), !bool(v.z), !bool(v.w));
+  }
+  bvec4 ${F}_(bvec4 v) {
+    return bvec4(!v.x, !v.y, !v.z, !v.w);
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function D(){return Y("sin")}function C(){const F="relu";return{body:`
+  float ${F}_(float a) {
+    return max( a, 0.0 );
+  }
+  vec4 ${F}_(vec4 v) {
+    return max( v, 0.0 );
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function A(){const F="sigmoid";return{body:`
+  float ${F}_(float a) {
+    return 1.0 / (1.0 + exp(-a));
+  }
+  vec4 ${F}_(vec4 v) {
+    return 1.0 / (1.0 + exp(-v));
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function $(){return Y("sqrt")}function W(){return Y("tan")}function K(){const F="tanh";return{body:`
+  float ${F}_(float a) {
+    a = clamp(a, -10., 10.);
+    a = exp(2.*a);
+    return (a - 1.) / (a + 1.);
+  }
+  vec4 ${F}_(vec4 v) {
+    v = clamp(v, -10., 10.);
+    v = exp(2.*v);
+    return (v - 1.) / (v + 1.);
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}function Y(F){return{body:`
+  float ${F}_(float a) {
+    return ${F}(a);
+  }
+  vec4 ${F}_(vec4 v) {
+    return ${F}(v);
+  }
+  `,name:F,type:b.FunctionType.ValueBased}}o.glslAbs=_,o.glslAcos=f,o.glslAsin=u,o.glslAtan=n,o.glslCeil=e,o.glslCos=a,o.glslElu=s,o.glslExp=g,o.glslFloor=y,o.glslClip=x,o.glslIdentity=E,o.glslLeakyRelu=S,o.glslLog=P,o.glslNeg=O,o.glslNot=k,o.glslSin=D,o.glslRelu=C,o.glslSigmoid=A,o.glslSqrt=$,o.glslTan=W,o.glslTanh=K;const q=(F,B,fe,ne)=>{const z=F.session.pack?m.TextureType.packed:m.TextureType.unpacked,Q={name:fe.name,inputTypes:[z],inputNames:["A"],cacheHint:ne};return Object.assign(Object.assign({},Q),{get:()=>((re,ue,_e,ve)=>{const we=re.session.pack?m.TextureType.packed:m.TextureType.unpacked,Ae=(0,c.getGlsl)(re.session.backend.glContext.version);return Object.assign(Object.assign({},ue),{output:{dims:_e.dims,type:_e.type,textureType:we},shaderSource:`
+     ${ve.body}
+     void main() {
+       vec4 v = ${Ae.texture2D}(A, TexCoords);
+       v = ${ve.name}_(v);
+       ${Ae.output} = v;
+     }
+     `,hasMain:!0})})(F,Q,B,fe)})};o.abs=(F,B)=>[F.run(q(F,B[0],_()),B)],o.acos=(F,B)=>[F.run(q(F,B[0],f()),B)],o.asin=(F,B)=>[F.run(q(F,B[0],u()),B)],o.atan=(F,B)=>[F.run(q(F,B[0],n()),B)],o.clip=(F,B,fe)=>[F.run(q(F,B[0],x(fe.min,fe.max),fe.cacheKey),B)],o.parseClipAttributes=F=>(0,l.createAttributeWithCacheKey)({min:F.attributes.getFloat("min",p.MIN_CLIP),max:F.attributes.getFloat("max",p.MAX_CLIP)}),o.clipV11=(F,B)=>{const fe=se(F,B);return(0,o.clip)(F,[B[0]],fe)};const se=(F,B)=>{if(B.length>=3&&(!F.session.isInitializer(B[1].dataId)||!F.session.isInitializer(B[2].dataId)))throw new Error("dynamic clip attributes are not allowed");const fe=B.length>=3?B[1].numberData[0]:p.MIN_CLIP,ne=B.length>=3?B[2].numberData[0]:p.MAX_CLIP;return(0,l.createAttributeWithCacheKey)({min:fe,max:ne})};o.ceil=(F,B)=>[F.run(q(F,B[0],e()),B)],o.cos=(F,B)=>[F.run(q(F,B[0],a()),B)],o.elu=(F,B,fe)=>[F.run(q(F,B[0],s(fe.alpha),fe.cacheKey),B)],o.parseEluAttributes=F=>(0,l.createAttributeWithCacheKey)({alpha:F.attributes.getFloat("alpha",1)}),o.exp=(F,B)=>[F.run(q(F,B[0],g()),B)],o.floor=(F,B)=>[F.run(q(F,B[0],y()),B)],o.identity=(F,B)=>[F.run(q(F,B[0],E()),B)],o.leakyRelu=(F,B,fe)=>[F.run(q(F,B[0],S(fe.alpha),fe.cacheKey),B)],o.parseLeakyReluAttributes=F=>(0,l.createAttributeWithCacheKey)({alpha:F.attributes.getFloat("alpha",.01)}),o.log=(F,B)=>[F.run(q(F,B[0],P()),B)],o.neg=(F,B)=>[F.run(q(F,B[0],O()),B)],o.not=(F,B)=>[F.run(q(F,B[0],k()),B)],o.relu=(F,B)=>[F.run(q(F,B[0],C()),B)],o.sigmoid=(F,B)=>[F.run(q(F,B[0],A()),B)],o.sin=(F,B)=>[F.run(q(F,B[0],D()),B)],o.sqrt=(F,B)=>[F.run(q(F,B[0],$()),B)],o.tan=(F,B)=>[F.run(q(F,B[0],W()),B)],o.tanh=(F,B)=>[F.run(q(F,B[0],K()),B)]},5611:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createUnpackProgramInfoLoader=o.createUnpackProgramInfo=void 0;const l=d(5060),p=d(2039),b=d(9390),c=d(2827),m={name:"unpack",inputNames:["A"],inputTypes:[p.TextureType.packed]};o.createUnpackProgramInfo=(_,f)=>{const u=f.dims.length,n=(0,c.getChannels)("rc",u),e=n.slice(-2),a=(0,b.getCoordsDataType)(u),s=(0,c.unpackFromChannel)(),g=f.dims.length===0?"":function(E,S){if(E===1)return"rc";let P="";for(let O=0;O<E;O++)P+=S[O],O<E-1&&(P+=",");return P}(u,n),y=u<=1?"rc":`vec2(${e.join(",")})`,x=`
+    ${s}
+    void main() {
+      ${a} rc = getOutputCoords();
+
+       // Sample the texture with the coords to get the rgba channel value.
+       vec4 packedInput = getA(${g});
+
+       ${(0,l.getGlsl)(_.session.backend.glContext.version).output} = vec4(getChannel(packedInput, ${y}), 0, 0, 0);
+     }
+   `;return Object.assign(Object.assign({},m),{hasMain:!0,output:{dims:f.dims,type:f.type,textureType:p.TextureType.unpacked},shaderSource:x})},o.createUnpackProgramInfoLoader=(_,f)=>Object.assign(Object.assign({},m),{get:()=>(0,o.createUnpackProgramInfo)(_,f)})},8428:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.parseUnsqueezeAttributes=o.unsqueezeV13=o.unsqueeze=void 0;const l=d(2517);o.unsqueeze=(c,m,_)=>{p(m);const f=l.ShapeUtil.unsqueezeShape(m[0].dims,_);return[c.reshapeUnpacked(m[0],f)]},o.unsqueezeV13=(c,m)=>(b(m),(0,o.unsqueeze)(c,[m[0]],Array.from(m[1].integerData))),o.parseUnsqueezeAttributes=c=>c.attributes.getInts("axes");const p=c=>{if(!c||c.length!==1)throw new Error("Unsqueeze requires 1 input.");if(c[0].type==="string")throw new Error("invalid input tensor types.")},b=c=>{if(!c||c.length!==2)throw new Error("Unsqueeze requires 2 inputs.");if(c[1].type!=="int32")throw new Error("Invalid input type.")}},9793:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.scalesValidation=o.validateInputs=o.parseUpsampleAttributes=o.parseUpsampleAttributesV9=o.parseUpsampleAttributesV7=o.upsample=void 0;const l=d(246),p=d(5060),b=d(2039),c={name:"Upsample",inputNames:["X"],inputTypes:[b.TextureType.unpacked]};o.upsample=(_,f,u)=>((0,o.validateInputs)(f,u),[_.run(Object.assign(Object.assign({},c),{cacheHint:u.cacheKey,get:()=>m(_,f,u)}),f)]),o.parseUpsampleAttributesV7=_=>(0,o.parseUpsampleAttributes)(_,7),o.parseUpsampleAttributesV9=_=>(0,o.parseUpsampleAttributes)(_,9),o.parseUpsampleAttributes=(_,f)=>{const u=f>=10,n=_.attributes.getString("mode","nearest");if(n!=="nearest"&&n!=="linear"&&(f<11||n!=="cubic"))throw new Error(`unrecognized mode: ${n}`);let e=[];f<9&&(e=_.attributes.getFloats("scales"),(0,o.scalesValidation)(e,n,u));const a=_.attributes.getFloat("extrapolation_value",0),s=f>10?_.attributes.getString("coordinate_transformation_mode","half_pixel"):"asymmetric";if(["asymmetric","pytorch_half_pixel","tf_half_pixel_for_nn","align_corners","tf_crop_and_resize","half_pixel"].indexOf(s)===-1)throw new Error(`coordinate_transform_mode '${s}' is not supported`);const g=s==="tf_crop_and_resize",y=g,x=n==="nearest"&&f>=11?_.attributes.getString("nearest_mode","round_prefer_floor"):"";if(["round_prefer_floor","round_prefer_ceil","floor","ceil",""].indexOf(x)===-1)throw new Error(`nearest_mode '${x}' is not supported`);const E=_.attributes.getFloat("cubic_coeff_a",-.75),S=_.attributes.getInt("exclude_outside",0)!==0;if(S&&n!=="cubic")throw new Error("exclude_outside can be set to 1 only when mode is CUBIC.");const P=f<11||n==="nearest"&&s==="asymmetric"&&x==="floor";let O=0,k=0,D=0;return f>10?_.inputs.length>2?(O=1,k=2,D=3):(k=1,D=2):f===9&&(k=1),(0,l.createAttributeWithCacheKey)({opset:f,isResize:u,mode:n,scales:e,extrapolationValue:a,coordinateTransformMode:s,useExtrapolation:y,needRoiInput:g,nearestMode:x,cubicCoefficientA:E,excludeOutside:S,useNearest2xOptimization:P,roiInputIdx:O,scalesInputIdx:k,sizesInputIdx:D})};const m=(_,f,u)=>{const n=(0,p.getGlsl)(_.session.backend.glContext.version),[e,a]=_.calculateTextureWidthAndHeight(f[0].dims,b.TextureType.unpacked),s=f[0].dims.map((D,C)=>Math.floor(D*u.scales[C])),[g,y]=_.calculateTextureWidthAndHeight(s,b.TextureType.unpacked),x=s.length,E=new Array(x),S=new Array(x);let P=`
+      int output_pitches[${x}];
+      int input_pitches[${x}];
+      `;for(let D=x-1;D>=0;D--)E[D]=D===x-1?1:E[D+1]*s[D+1],S[D]=D===x-1?1:S[D+1]*f[0].dims[D+1],P+=`
+        output_pitches[${D}] = ${E[D]};
+        input_pitches[${D}] = ${S[D]};
+        `;const O=`
+      float getInputFloat(int index) {
+        vec2 coords = offsetToCoords(index, ${e}, ${a});
+        float value = getColorAsFloat(${n.texture2D}(X, coords));
+        return value;
+      }
+      `,k=u.mode==="nearest"?`
+    ${O}
+    float process(int indices[${x}]) {
+      int input_index = 0;
+      int output_index = coordsToOffset(TexCoords, ${g}, ${y});
+
+      ${P}
+
+      int d, m;
+      for (int dim = 0; dim < ${x}; ++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);
+    }`:x===4?`
+    ${O}
+    float process(int indices[4]) {
+      int input_index = 0;
+      int output_index = coordsToOffset(TexCoords, ${g}, ${y});
+
+      ${P}
+
+      int m;
+      int index_of_dim0, index_of_dim1, index_of_dim2, index_of_dim3;
+      index_of_dim0 = output_index / output_pitches[0];
+      m = output_index - index_of_dim0 * output_pitches[0];
+      index_of_dim1 = m / output_pitches[1];
+      m = m - index_of_dim1 * output_pitches[1];
+      index_of_dim2 = m / output_pitches[2];
+      m = m - index_of_dim2 * output_pitches[2];
+      index_of_dim3 = m;
+
+      int index_of_input_dim2, index_of_input_dim3, x_offset, y_offset;
+      index_of_input_dim2 = index_of_dim2 / scales[2];
+      y_offset = index_of_dim2 - index_of_input_dim2 * scales[2];
+      index_of_input_dim3 = index_of_dim3 / scales[3];
+      x_offset = index_of_dim3 - index_of_input_dim3 * scales[3];
+
+      input_index = index_of_dim0 * input_pitches[0] +
+            index_of_dim1 * input_pitches[1] +
+            index_of_input_dim2 * input_pitches[2] +
+            index_of_input_dim3;
+
+      float x00 = getInputFloat(input_index);
+      float x10, x01, x11;
+
+      bool end_of_dim2 = false;
+      if (index_of_input_dim2 == (${f[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]);
+    }`:`
+    ${O}
+    float process(int indices[2]) {
+      int input_index = 0;
+      int output_index = coordsToOffset(TexCoords, ${g}, ${y});
+
+      ${P}
+
+      int m;
+      int index_of_dim0, index_of_dim1;
+      index_of_dim0 = output_index / output_pitches[0];
+      m = output_index - index_of_dim0 * output_pitches[0];
+      index_of_dim1 = m;
+
+      int index_of_input_dim0, index_of_input_dim1, x_offset, y_offset;
+      index_of_input_dim0 = index_of_dim0 / scales[0];
+      y_offset = index_of_dim0 - index_of_input_dim0 * scales[0];
+      index_of_input_dim1 = index_of_dim1 / scales[1];
+      x_offset = index_of_dim1 - index_of_input_dim1 * scales[1];
+
+      input_index = index_of_input_dim0 * input_pitches[0] + index_of_input_dim1;
+
+      float x00 = getInputFloat(input_index);
+      float x10, x01, x11;
+
+      bool end_of_dim0 = false;
+      if (index_of_input_dim0 == (${f[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({},c),{output:{dims:s,type:f[0].type,textureType:b.TextureType.unpacked},shaderSource:k,variables:[{name:"scales",type:"int",arrayLength:u.scales.length,data:u.scales.map(D=>Math.ceil(D))}]})};o.validateInputs=(_,f)=>{if(!_||f.opset<9&&_.length!==1||f.opset>=9&&f.opset<11&&_.length!==2||f.opset>=11&&_.length<2)throw new Error("invalid inputs.");if(f.scales.length>0&&_[0].dims.length!==f.scales.length)throw new Error("Invalid input shape.");if(_[0].type==="string")throw new Error("Invalid input tensor types.")},o.scalesValidation=(_,f,u)=>{if(u){for(const n of _)if(n<=0)throw new Error("Scale value should be greater than 0.")}else for(const n of _)if(n<1)throw new Error("Scale value should be greater than or equal to 1.");if(!(f!=="linear"&&f!=="cubic"||_.length===2||_.length===4&&_[0]===1&&_[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 ${u?"Resize":"Upsample"} opeartor.`)}},1958:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.ProgramManager=void 0;const l=d(1670),p=d(6231),b=d(8879),c=d(5060);o.ProgramManager=class{constructor(m,_,f){this.profiler=m,this.glContext=_,this.textureLayoutStrategy=f,this.repo=new Map,this.attributesBound=!1}getArtifact(m){return this.repo.get(m)}setArtifact(m,_){this.repo.set(m,_)}run(m,_,f){var u;this.profiler.event("op",`ProgramManager.run ${(u=m.programInfo.name)!==null&&u!==void 0?u:"unknown kernel"}`,()=>{var n;const e=this.glContext.gl,a=m.program;e.useProgram(a);try{this.bindOutput(f),this.attributesBound||this.bindAttributes(m.attribLocations),this.bindUniforms(m.uniformLocations,(n=m.programInfo.variables)!==null&&n!==void 0?n:[],_)}catch(s){throw p.Logger.error("ProgramManager",m.programInfo.shaderSource),s}this.profiler.event("backend","GlContext.draw()",()=>{this.glContext.draw()})},this.glContext)}dispose(){this.vertexShader&&this.glContext.deleteShader(this.vertexShader),this.repo.forEach(m=>this.glContext.deleteProgram(m.program))}build(m,_,f){return this.profiler.event("backend","ProgramManager.build",()=>{const u=new b.GlslPreprocessor(this.glContext,m,_,f),n=u.preprocess(),e=this.compile(n);return{programInfo:m,program:e,uniformLocations:this.getUniformLocations(e,u.context.programInfo.inputNames,u.context.programInfo.variables),attribLocations:this.getAttribLocations(e)}})}compile(m){if(!this.vertexShader){p.Logger.verbose("ProrgramManager","Compiling and caching Vertex shader for the first time");const u=(0,c.getVertexShaderSource)(this.glContext.version);this.vertexShader=this.glContext.compileShader(u,this.glContext.gl.VERTEX_SHADER)}l.env.debug&&p.Logger.verbose("ProrgramManager",`FragShader:
+${m}
+`);const _=this.glContext.compileShader(m,this.glContext.gl.FRAGMENT_SHADER),f=this.glContext.createProgram(this.vertexShader,_);return this.glContext.deleteShader(_),f}bindOutput(m){const _=m.width,f=m.height;p.Logger.verbose("ProrgramManager",`Binding output texture to Framebuffer: w/h=${_}/${f}, shape=${m.shape}, type=${m.tensor.type}`),this.glContext.attachFramebuffer(m.texture,_,f)}bindAttributes(m){const _=m.position,f=m.textureCoord;this.glContext.setVertexAttributes(_,f),this.attributesBound=!0}bindUniforms(m,_,f){var u;const n=this.glContext.gl;let e=0;for(const{name:a,type:s,location:g,arrayLength:y}of m){const x=(u=_.find(E=>E.name===a))===null||u===void 0?void 0:u.data;if(s!=="sampler2D"&&!x)throw new Error(`variable '${a}' does not have data defined in program info`);switch(s){case"sampler2D":this.bindTexture(f[e],g,e),e++;break;case"float":y?n.uniform1fv(g,x):n.uniform1f(g,x);break;case"int":y?n.uniform1iv(g,x):n.uniform1i(g,x);break;default:throw new Error(`Uniform not implemented: ${s}`)}}}bindTexture(m,_,f){this.glContext.bindTextureToUniform(m.texture,f,_)}getAttribLocations(m){return{position:this.getAttribLocation(m,"position"),textureCoord:this.getAttribLocation(m,"textureCoord")}}getUniformLocations(m,_,f){const u=[];if(_)for(const n of _)u.push({name:n,type:"sampler2D",location:this.getUniformLocation(m,n)});if(f)for(const n of f)u.push(Object.assign(Object.assign({},n),{location:this.getUniformLocation(m,n.name)}));return u}getUniformLocation(m,_){const f=this.glContext.gl.getUniformLocation(m,_);if(f===null)throw new Error(`Uniform ${_} not found.`);return f}getAttribLocation(m,_){return this.glContext.gl.getAttribLocation(m,_)}}},6416:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.WebGLSessionHandler=void 0;const l=d(6231),p=d(1047),b=d(8316),c=d(1640),m=d(1958),_=d(7859),f=d(5702);o.WebGLSessionHandler=class{constructor(u,n){this.backend=u,this.context=n,this.layoutStrategy=new _.PreferLogicalStrategy(u.glContext.maxTextureSize),this.programManager=new m.ProgramManager(this.context.profiler,u.glContext,this.layoutStrategy),this.textureManager=new f.TextureManager(u.glContext,this.layoutStrategy,this.context.profiler,{reuseTextures:u.textureCacheMode==="full"}),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache=new Map,this.pack=u.pack,this.pack2unpackMap=new Map,this.unpack2packMap=new Map}createInferenceHandler(){return new b.WebGLInferenceHandler(this)}onGraphInitialized(u){const n=u.getValues().filter(e=>e.from===-1&&e.tensor).map(e=>e.tensor.dataId);this.initializers=new Set(n)}isInitializer(u){return!!this.initializers&&this.initializers.has(u)}addInitializer(u){this.initializers.add(u)}getTextureData(u,n){return n?this.packedTextureDataCache.get(u):this.unpackedTextureDataCache.get(u)}setTextureData(u,n,e=!1){l.Logger.verbose("WebGLSessionHandler","Storing Texture data in cache"),e?this.packedTextureDataCache.set(u,n):this.unpackedTextureDataCache.set(u,n)}dispose(){this.programManager.dispose(),this.textureManager.clearActiveTextures(),this.packedTextureDataCache.forEach(u=>this.textureManager.releaseTexture(u,!0)),this.packedTextureDataCache=new Map,this.unpackedTextureDataCache.forEach(u=>this.textureManager.releaseTexture(u,!0)),this.unpackedTextureDataCache=new Map}resolve(u,n,e){const a=(0,p.resolveOperator)(u,n,c.WEBGL_OP_RESOLVE_RULES);return{impl:a.opImpl,context:a.opInit?a.opInit(u,e):u}}}},7769:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.Uint8DataEncoder=o.RGBAFloatDataEncoder=o.RedFloat32DataEncoder=void 0;const l=d(6231);o.RedFloat32DataEncoder=class{constructor(p,b=1){if(b===1)this.internalFormat=p.R32F,this.format=p.RED,this.textureType=p.FLOAT,this.channelSize=b;else{if(b!==4)throw new Error(`Invalid number of channels: ${b}`);this.internalFormat=p.RGBA32F,this.format=p.RGBA,this.textureType=p.FLOAT,this.channelSize=b}}encode(p,b){let c,m;return p.constructor!==Float32Array&&(l.Logger.warning("Encoder","data was not of type Float32; creating new Float32Array"),m=new Float32Array(p)),b*this.channelSize>p.length?(l.Logger.warning("Encoder","Source data too small. 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width/height preferences were unattainable: shape:${u}, breakAxis:${n.breakAxis}`)}let s=u.slice(0);e&&(a*=2,s=s.map((y,x)=>x>=s.length-2?s[x]%2==0?s[x]:s[x]+1:s[x]),s.length===1&&(s=[2,s[0]])),s.length!==2&&(s=b(s).newShape);const g=_(s);return s.length<=1&&g<=a?[1,g]:s.length===2&&s[0]<=a&&s[1]<=a?s:s.length===3&&s[0]*s[1]<=a&&s[2]<=a?[s[0]*s[1],s[2]]:s.length===3&&s[0]<=a&&s[1]*s[2]<=a?[s[0],s[1]*s[2]]:s.length===4&&s[0]*s[1]*s[2]<=a&&s[3]<=a?[s[0]*s[1]*s[2],s[3]]:s.length===4&&s[0]<=a&&s[1]*s[2]*s[3]<=a?[s[0],s[1]*s[2]*s[3]]:e?f(g/4).map(y=>2*y):f(g)}},o.squeezeShape=b,o.parseAxisParam=c,o.isInt=m,o.sizeFromShape=_,o.getRowsCols=function(u){if(u.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[u.length>1?u[u.length-2]:1,u[u.length-1]]},o.sizeToSquarishShape=f,o.getBatchDim=function(u,n=2){return _(u.slice(0,u.length-n))}},4057:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.createTextureLayoutFromShape=o.calculateTextureWidthAndHeight=o.createTextureLayoutFromTextureType=void 0;const l=d(2517),p=d(2039);o.createTextureLayoutFromTextureType=(b,c,m)=>{const _=m===p.TextureType.unpacked||m===p.TextureType.unpackedReversed?1:4,f=m===p.TextureType.packed,u=m===p.TextureType.unpackedReversed||m===p.TextureType.packed,n=m===p.TextureType.packedLastDimension?c.length-1:void 0,e=m===p.TextureType.packedLastDimension?c.map((a,s)=>s===c.length-1?4*a:a):void 0;return(0,o.createTextureLayoutFromShape)(b,c,_,e,{isPacked:f,reverseWH:u,breakAxis:n})},o.calculateTextureWidthAndHeight=(b,c,m)=>{const _=(0,o.createTextureLayoutFromTextureType)(b,c,m);return[_.width,_.height]},o.createTextureLayoutFromShape=(b,c,m=1,_,f)=>{const u=!(!f||!f.isPacked),[n,e]=b.computeTextureWH(u&&_||c,f),a=c.length;let s=c.slice(0);if(a===0&&(s=[1]),m===1)_=c;else if(u){if(m!==4)throw new Error("a packed texture must be 4-channel");_=c,a>0&&(s[a-1]=Math.ceil(s[a-1]/2)),a>1&&(s[a-2]=Math.ceil(s[a-2]/2))}else if(!_)throw new Error("Unpacked shape is needed when using channels > 1");return{width:n,height:e,channels:m,isPacked:u,shape:s,strides:l.ShapeUtil.computeStrides(s),unpackedShape:_,reversedWH:f&&f.reverseWH}}},5702:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.TextureManager=void 0;const l=d(6231);o.TextureManager=class{constructor(p,b,c,m){this.glContext=p,this.layoutStrategy=b,this.profiler=c,this.config=m,this.pendingRead=new Map,m.reuseTextures&&(this.inUseTextures=new Map,this.idleTextures=new Map,this.textureLookup=new Map)}createTextureFromLayout(p,b,c,m){const _=this.toEncoderType(p),f=this.glContext.getEncoder(_,b.channels||1,m);if(b.isPacked&&m===1)throw new Error("not implemented");const u=b.width,n=b.height;let e,a;if(this.config.reuseTextures){e=`${u}x${n}_${f.format}_${f.internalFormat}_${f.textureType}`,a=this.inUseTextures.get(e),a||(a=[],this.inUseTextures.set(e,a));const g=this.idleTextures.get(e);if(g&&g.length>0){const y=g.pop();return a.push(y),m===1&&this.glContext.updateTexture(y,u,n,f,this.toTextureData(p,c)),y}}l.Logger.verbose("TextureManager",`Creating new texture of size ${b.width}x${b.height}`);const s=this.glContext.allocateTexture(u,n,f,this.toTextureData(p,c));return this.config.reuseTextures&&(a.push(s),this.textureLookup.set(s,e)),s}readTexture(p,b,c){return c||(c=1),this.profiler.event("backend","TextureManager.readTexture",()=>{const m=p.shape.reduce((f,u)=>f*u)*c,_=this.glContext.readTexture(p.texture,p.width,p.height,m,this.toEncoderType(b),c);return this.toTensorData(b,_)})}async readTextureAsync(p,b,c){const m=p.tensor.dataId;if(c||(c=1),this.pendingRead.has(m)){const _=this.pendingRead.get(m);return new Promise(f=>_==null?void 0:_.push(f))}return this.profiler.event("backend","TextureManager.readTextureAsync",async()=>{this.pendingRead.set(m,[]);const _=p.shape.reduce((e,a)=>e*a)*c;await this.glContext.createAndWaitForFence();const f=this.glContext.readTexture(p.texture,p.width,p.height,_,this.toEncoderType(b),c),u=this.toTensorData(b,f),n=this.pendingRead.get(m);return this.pendingRead.delete(m),n==null||n.forEach(e=>e(u)),u})}readUint8TextureAsFloat(p){return this.profiler.event("backend","TextureManager.readUint8TextureAsFloat",()=>{const b=p.shape.reduce((m,_)=>m*_),c=this.glContext.readTexture(p.texture,p.width,p.height,4*b,"byte",4);return new Float32Array(c.buffer,c.byteOffset,b)})}releaseTexture(p,b){let c;if(this.config.reuseTextures&&(c=this.textureLookup.get(p.texture),c)){b&&this.textureLookup.delete(c);const m=this.inUseTextures.get(c);if(m){const _=m.indexOf(p.texture);if(_!==-1){m.splice(_,1);let f=this.idleTextures.get(c);f||(f=[],this.idleTextures.set(c,f)),f.push(p.texture)}}}c&&!b||(l.Logger.verbose("TextureManager",`Deleting texture of size ${p.width}x${p.height}`),this.glContext.deleteTexture(p.texture))}toTensorData(p,b){switch(p){case"int16":return b instanceof Int16Array?b:Int16Array.from(b);case"int32":return b instanceof Int32Array?b:Int32Array.from(b);case"int8":return b instanceof Int8Array?b:Int8Array.from(b);case"uint16":return b instanceof Uint16Array?b:Uint16Array.from(b);case"uint32":return b instanceof Uint32Array?b:Uint32Array.from(b);case"uint8":case"bool":return b instanceof Uint8Array?b:Uint8Array.from(b);case"float32":return b instanceof Float32Array?b:Float32Array.from(b);case"float64":return b instanceof Float64Array?b:Float64Array.from(b);default:throw new Error(`TensorData type ${p} is not supported`)}}toTextureData(p,b){if(b)return b instanceof Float32Array?b:new Float32Array(b)}toEncoderType(p){return"float"}clearActiveTextures(){this.glContext.clearActiveTextures()}}},2039:(v,o)=>{var d;Object.defineProperty(o,"__esModule",{value:!0}),o.TextureType=void 0,(d=o.TextureType||(o.TextureType={}))[d.unpacked=0]="unpacked",d[d.unpackedReversed=1]="unpackedReversed",d[d.packed=2]="packed",d[d.downloadUint8AsFloat=3]="downloadUint8AsFloat",d[d.packedLastDimension=4]="packedLastDimension"},9390:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.getGlChannels=o.getCoordsDataType=o.getSqueezedParams=o.squeezeInputShape=o.generateShaderFuncNameFromInputSamplerNameAtOutCoords=o.generateShaderFuncNameFromInputSamplerName=o.repeatedTry=o.getPackedShape=void 0;const l=d(2517);o.getPackedShape=function(p){const b=p.length;return p.slice(0,b-1).concat(p[b-1]/4)},o.repeatedTry=async function(p,b=m=>0,c){return new Promise((m,_)=>{let f=0;const u=()=>{if(p())return void m();f++;const 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Error: ${n}`)}if((!m||m==="webgl")&&(f=_.getContext("webgl",u)||_.getContext("experimental-webgl",u),f))try{return new p.WebGLContext(f,1)}catch(n){l.Logger.warning("GlContextFactory",`failed to create WebGLContext using contextId 'webgl' or 'experimental-webgl'. Error: ${n}`)}throw new Error("WebGL is not supported")}o.createWebGLContext=function m(_){let f;_&&_!=="webgl2"||!("webgl2"in b)?_&&_!=="webgl"||!("webgl"in b)||(f=b.webgl):f=b.webgl2,f=f||c(_),_=_||f.version===1?"webgl":"webgl2";const u=f.gl;return b[_]=f,u.isContextLost()?(delete b[_],m(_)):(u.disable(u.DEPTH_TEST),u.disable(u.STENCIL_TEST),u.disable(u.BLEND),u.disable(u.DITHER),u.disable(u.POLYGON_OFFSET_FILL),u.disable(u.SAMPLE_COVERAGE),u.enable(u.SCISSOR_TEST),u.enable(u.CULL_FACE),u.cullFace(u.BACK),f)},o.createNewWebGLContext=c},1713:function(v,o,d){var l=this&&this.__createBinding||(Object.create?function(u,n,e,a){a===void 0&&(a=e);var s=Object.getOwnPropertyDescriptor(n,e);s&&!("get"in s?!n.__esModule:s.writable||s.configurable)||(s={enumerable:!0,get:function(){return n[e]}}),Object.defineProperty(u,a,s)}:function(u,n,e,a){a===void 0&&(a=e),u[a]=n[e]}),p=this&&this.__setModuleDefault||(Object.create?function(u,n){Object.defineProperty(u,"default",{enumerable:!0,value:n})}:function(u,n){u.default=n}),b=this&&this.__importStar||function(u){if(u&&u.__esModule)return u;var n={};if(u!=null)for(var e in u)e!=="default"&&Object.prototype.hasOwnProperty.call(u,e)&&l(n,u,e);return p(n,u),n};Object.defineProperty(o,"__esModule",{value:!0}),o.WebGLContext=o.linearSearchLastTrue=void 0;const c=d(1670),m=b(d(7769)),_=d(9390);function f(u){let n=0;for(;n<u.length&&u[n]();++n);return n-1}o.linearSearchLastTrue=f,o.WebGLContext=class{constructor(u,n){this.frameBufferBound=!1,this.itemsToPoll=[],this.gl=u,this.version=n,this.getExtensions(),this.vertexbuffer=this.createVertexbuffer(),this.framebuffer=this.createFramebuffer(),this.queryVitalParameters()}allocateTexture(u,n,e,a){const s=this.gl,g=s.createTexture();s.bindTexture(s.TEXTURE_2D,g),s.texParameteri(s.TEXTURE_2D,s.TEXTURE_MIN_FILTER,s.NEAREST),s.texParameteri(s.TEXTURE_2D,s.TEXTURE_MAG_FILTER,s.NEAREST),s.texParameteri(s.TEXTURE_2D,s.TEXTURE_WRAP_S,s.CLAMP_TO_EDGE),s.texParameteri(s.TEXTURE_2D,s.TEXTURE_WRAP_T,s.CLAMP_TO_EDGE);const y=a?e.encode(a,u*n):null;return s.texImage2D(s.TEXTURE_2D,0,e.internalFormat,u,n,0,e.format,e.textureType,y),this.checkError(),g}updateTexture(u,n,e,a,s){const g=this.gl;g.bindTexture(g.TEXTURE_2D,u);const y=a.encode(s,n*e);g.texSubImage2D(g.TEXTURE_2D,0,0,0,n,e,a.format,a.textureType,y),this.checkError()}attachFramebuffer(u,n,e){const a=this.gl;a.bindTexture(a.TEXTURE_2D,u),a.bindFramebuffer(a.FRAMEBUFFER,this.framebuffer),a.framebufferTexture2D(a.FRAMEBUFFER,a.COLOR_ATTACHMENT0,a.TEXTURE_2D,u,0),this.checkError(),a.viewport(0,0,n,e),a.scissor(0,0,n,e)}readTexture(u,n,e,a,s,g){const y=this.gl;g||(g=1),this.frameBufferBound||this.attachFramebuffer(u,n,e);const x=this.getEncoder(s,g),E=x.allocate(n*e);return y.bindTexture(y.TEXTURE_2D,u),y.framebufferTexture2D(y.FRAMEBUFFER,y.COLOR_ATTACHMENT0,y.TEXTURE_2D,u,0),y.readPixels(0,0,n,e,y.RGBA,x.textureType,E),this.checkError(),x.decode(E,a)}isFramebufferReady(){return!0}getActiveTexture(){const u=this.gl;return"TEXTURE"+(u.getParameter(this.gl.ACTIVE_TEXTURE)-u.TEXTURE0)}getTextureBinding(){return this.gl.getParameter(this.gl.TEXTURE_BINDING_2D)}getFramebufferBinding(){return this.gl.getParameter(this.gl.FRAMEBUFFER_BINDING)}setVertexAttributes(u,n){const e=this.gl;e.vertexAttribPointer(u,3,e.FLOAT,!1,20,0),e.enableVertexAttribArray(u),n!==-1&&(e.vertexAttribPointer(n,2,e.FLOAT,!1,20,12),e.enableVertexAttribArray(n)),this.checkError()}createProgram(u,n){const e=this.gl,a=e.createProgram();return e.attachShader(a,u),e.attachShader(a,n),e.linkProgram(a),a}compileShader(u,n){const e=this.gl,a=e.createShader(n);if(!a)throw new Error(`createShader() returned null with type ${n}`);if(e.shaderSource(a,u),e.compileShader(a),e.getShaderParameter(a,e.COMPILE_STATUS)===!1)throw new Error(`Failed to compile shader: ${e.getShaderInfoLog(a)}
+Shader source:
+${u}`);return a}deleteShader(u){this.gl.deleteShader(u)}bindTextureToUniform(u,n,e){const a=this.gl;a.activeTexture(a.TEXTURE0+n),this.checkError(),a.bindTexture(a.TEXTURE_2D,u),this.checkError(),a.uniform1i(e,n),this.checkError()}draw(){this.gl.drawArrays(this.gl.TRIANGLE_STRIP,0,4),this.checkError()}checkError(){if(c.env.debug){const u=this.gl,n=u.getError();let e="";switch(n){case u.NO_ERROR:return;case u.INVALID_ENUM:e="INVALID_ENUM";break;case u.INVALID_VALUE:e="INVALID_VALUE";break;case u.INVALID_OPERATION:e="INVALID_OPERATION";break;case u.INVALID_FRAMEBUFFER_OPERATION:e="INVALID_FRAMEBUFFER_OPERATION";break;case u.OUT_OF_MEMORY:e="OUT_OF_MEMORY";break;case u.CONTEXT_LOST_WEBGL:e="CONTEXT_LOST_WEBGL";break;default:e=`Unknown WebGL Error: ${n.toString(16)}`}throw new Error(e)}}deleteTexture(u){this.gl.deleteTexture(u)}deleteProgram(u){this.gl.deleteProgram(u)}getEncoder(u,n,e=0){if(this.version===2)return new m.RedFloat32DataEncoder(this.gl,n);switch(u){case"float":return e===1||this.isRenderFloat32Supported?new m.RGBAFloatDataEncoder(this.gl,n):new m.RGBAFloatDataEncoder(this.gl,n,this.textureHalfFloatExtension.HALF_FLOAT_OES);case"int":throw new Error("not implemented");case"byte":return new m.Uint8DataEncoder(this.gl,n);default:throw new Error(`Invalid dataType: ${u}`)}}clearActiveTextures(){const u=this.gl;for(let n=0;n<this.maxTextureImageUnits;++n)u.activeTexture(u.TEXTURE0+n),u.bindTexture(u.TEXTURE_2D,null)}dispose(){if(this.disposed)return;const u=this.gl;u.bindFramebuffer(u.FRAMEBUFFER,null),u.deleteFramebuffer(this.framebuffer),u.bindBuffer(u.ARRAY_BUFFER,null),u.deleteBuffer(this.vertexbuffer),u.bindBuffer(u.ELEMENT_ARRAY_BUFFER,null),u.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 u=this.gl,n=u.createBuffer();if(!n)throw new Error("createBuffer() returned null");const e=this.createDefaultGeometry();return u.bindBuffer(u.ARRAY_BUFFER,n),u.bufferData(u.ARRAY_BUFFER,e,u.STATIC_DRAW),this.checkError(),n}createFramebuffer(){const u=this.gl.createFramebuffer();if(!u)throw new Error("createFramebuffer returned null");return u}queryVitalParameters(){const u=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=u.getParameter(u.MAX_TEXTURE_SIZE),this.maxTextureImageUnits=u.getParameter(u.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 u=this.gl,n=u.createTexture();u.bindTexture(u.TEXTURE_2D,n);const e=this.version===2?u.RGBA32F:u.RGBA;u.texImage2D(u.TEXTURE_2D,0,e,1,1,0,u.RGBA,u.FLOAT,null);const a=u.createFramebuffer();u.bindFramebuffer(u.FRAMEBUFFER,a),u.framebufferTexture2D(u.FRAMEBUFFER,u.COLOR_ATTACHMENT0,u.TEXTURE_2D,n,0);const s=u.checkFramebufferStatus(u.FRAMEBUFFER)===u.FRAMEBUFFER_COMPLETE;return u.bindTexture(u.TEXTURE_2D,null),u.bindFramebuffer(u.FRAMEBUFFER,null),u.deleteTexture(n),u.deleteFramebuffer(a),s}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 u=this.gl;let n,e,a,s,g;try{n=u.createTexture(),e=u.createFramebuffer(),u.bindTexture(u.TEXTURE_2D,n);const y=this.version===2?u.RGBA32F:u.RGBA;return u.texImage2D(u.TEXTURE_2D,0,y,1,1,0,u.RGBA,u.FLOAT,null),u.bindFramebuffer(u.FRAMEBUFFER,e),u.framebufferTexture2D(u.FRAMEBUFFER,u.COLOR_ATTACHMENT0,u.TEXTURE_2D,n,0),u.enable(u.BLEND),a=u.createShader(u.VERTEX_SHADER),!!a&&(u.shaderSource(a,"void main(){}"),u.compileShader(a),s=u.createShader(u.FRAGMENT_SHADER),!!s&&(u.shaderSource(s,"precision highp float;void main(){gl_FragColor=vec4(0.5);}"),u.compileShader(s),g=u.createProgram(),!!g&&(u.attachShader(g,a),u.attachShader(g,s),u.linkProgram(g),u.useProgram(g),u.drawArrays(u.POINTS,0,1),u.getError()===u.NO_ERROR)))}finally{u.disable(u.BLEND),g&&u.deleteProgram(g),a&&u.deleteShader(a),s&&u.deleteShader(s),e&&(u.bindFramebuffer(u.FRAMEBUFFER,null),u.deleteFramebuffer(e)),n&&(u.bindTexture(u.TEXTURE_2D,null),u.deleteTexture(n))}}beginTimer(){if(this.version===2&&this.disjointTimerQueryWebgl2Extension){const u=this.gl,n=this.disjointTimerQueryWebgl2Extension,e=u.createQuery();return u.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 u=this.gl,n=this.disjointTimerQueryWebgl2Extension;u.endQuery(n.TIME_ELAPSED_EXT)}}isTimerResultAvailable(u){let n=!1,e=!1;if(this.version!==2||!this.disjointTimerQueryWebgl2Extension)throw new Error("WebGL1 profiling currently not supported");{const a=this.gl,s=this.disjointTimerQueryWebgl2Extension;n=a.getQueryParameter(u,a.QUERY_RESULT_AVAILABLE),e=a.getParameter(s.GPU_DISJOINT_EXT)}return n&&!e}getTimerResult(u){let n=0;if(this.version!==2)throw new Error("WebGL1 profiling currently not supported");{const e=this.gl;n=e.getQueryParameter(u,e.QUERY_RESULT),e.deleteQuery(u)}return n/1e6}async waitForQueryAndGetTime(u){return await(0,_.repeatedTry)(()=>this.isTimerResultAvailable(u)),this.getTimerResult(u)}async createAndWaitForFence(){const u=this.createFence(this.gl);return this.pollFence(u)}createFence(u){let n;const e=u,a=e.fenceSync(e.SYNC_GPU_COMMANDS_COMPLETE,0);return u.flush(),n=a===null?()=>!0:()=>{const s=e.clientWaitSync(a,0,0);return s===e.ALREADY_SIGNALED||s===e.CONDITION_SATISFIED},{query:a,isFencePassed:n}}async pollFence(u){return new Promise(n=>{this.addItemToPoll(()=>u.isFencePassed(),()=>n())})}pollItems(){const u=f(this.itemsToPoll.map(n=>n.isDoneFn));for(let n=0;n<=u;++n){const{resolveFn:e}=this.itemsToPoll[n];e()}this.itemsToPoll=this.itemsToPoll.slice(u+1)}async addItemToPoll(u,n){this.itemsToPoll.push({isDoneFn:u,resolveFn:n}),this.itemsToPoll.length>1||await(0,_.repeatedTry)(()=>(this.pollItems(),this.itemsToPoll.length===0))}}},1036:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.ExecutionPlan=void 0;const l=d(6231);class p{constructor(c,m){this.op=c,this.node=m}}o.ExecutionPlan=class{constructor(b,c,m){this.graph=b,this.profiler=m,this.initialize(c)}initialize(b){this.profiler.event("session","ExecutionPlan.initialize",()=>{const c=this.graph.getNodes();if(c.length!==b.length)throw new Error("The size of nodes and OPs do not match.");this._ops=b.map((m,_)=>new p(m,c[_])),this.reset(),this._starter=[],this._ops.forEach((m,_)=>{let f=!0;for(const u of m.node.inputs)if(!this._values[u]&&this.graph.getInputIndices().indexOf(u)===-1){f=!1;break}f&&this._starter.push(_)})})}reset(){this._values=this.graph.getValues().map(b=>b.tensor)}async execute(b,c){return this.profiler.event("session","ExecutionPlan.execute",async()=>{this.reset();const m=b.createInferenceHandler(),_=this.graph.getInputIndices();if(c.length!==_.length)throw new Error(`number of input tensors don't match the number of inputs to the model: actual: ${c.length} expected: ${_.length}`);c.forEach((s,g)=>{const y=_[g];this._values[y]=s});const f=this._starter.slice(0),u=this.graph.getValues(),n=this.graph.getNodes();let e=0;for(;e<f.length;){const s=f[e++],g=this._ops[s],y=g.node.inputs.map(P=>this._values[P]);if(y.indexOf(void 0)!==-1)throw new Error(`unresolved input detected: op: ${g.node}`);const x=y;l.Logger.verbose("ExecPlan",`Runing op:${g.node.name} (${x.map((P,O)=>`'${g.node.inputs[O]}': ${P.type}[${P.dims.join(",")}]`).join(", ")})`);const E=await this.profiler.event("node",g.node.name,async()=>g.op.impl(m,x,g.op.context));if(E.length!==g.node.outputs.length)throw new Error("the size of output does not match model definition.");E.forEach((P,O)=>{const k=g.node.outputs[O];if(this._values[k])throw new Error(`output [${k}] already has value: op:${g.node.name}`);this._values[k]=P});const S=new Set;E.forEach((P,O)=>{const k=g.node.outputs[O];for(const D of u[k].to){const C=n[D];let A=!0;for(const $ of C.inputs)if(!this._values[$]){A=!1;break}A&&S.add(D)}}),f.push(...S)}const a=[];for(let s=0;s<this.graph.getOutputIndices().length;s++){const g=this.graph.getOutputIndices()[s],y=this._values[g];if(y===void 0)throw new Error(`required output [${g}] does not have value`);g===0?await y.getData():y.data,a.push(y)}return l.Logger.verbose("ExecPlan","disposing of inferenceHandler"),m.dispose(),a})}}},7070:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.Graph=void 0;const l=d(1446),p=d(7778),b=d(9395),c=d(9162),m=d(2517);var _=b.onnxruntime.experimental.fbs;o.Graph={from:(e,a)=>new n(e,a)};class f{constructor(a){this._from=void 0,this._to=[],this.tensor=void 0,this.type=void 0,a&&(this.type=m.ProtoUtil.tensorValueTypeFromProto(a.type.tensorType))}get from(){return this._from}get to(){return this._to}}class u{constructor(a,s){a instanceof l.onnx.NodeProto?(this.name=a.name,this.opType=a.opType,this.attributes=new p.Attribute(a.attribute)):a instanceof _.Node&&(this.name=s??a.name(),this.opType=a.opType(),this.attributes=new p.Attribute(m.ProtoUtil.tensorAttributesFromORTFormat(a))),this.inputs=[],this.outputs=[],this.executeNode=!0}}class n{constructor(a,s){if(!a)throw new TypeError("graph is empty");this.buildGraph(a),this.transformGraph(s),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(a){if(a instanceof l.onnx.GraphProto)this.buildGraphFromOnnxFormat(a);else{if(!(a instanceof _.Graph))throw new TypeError("Graph type is not supported.");this.buildGraphFromOrtFormat(a)}}buildGraphFromOnnxFormat(a){const s=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const g=new Map;if(!a.input)throw new Error("missing information in graph: input");const y=[];for(const x of a.input){if(s.has(x.name))throw new Error(`duplicated input name: ${x.name}`);const E=this._allData.push(new f(x))-1;s.set(x.name,E),y.push(x.name)}if(!a.initializer)throw new Error("missing information in graph: initializer");for(const x of a.initializer){let E=s.get(x.name);if(E===void 0){const S=new f;S.type={shape:{dims:m.ProtoUtil.tensorDimsFromProto(x.dims)},tensorType:m.ProtoUtil.tensorDataTypeFromProto(x.dataType)},E=this._allData.push(S)-1,s.set(x.name,E)}this._allData[E]._from=-1,this._allData[E].tensor=c.Tensor.fromProto(x)}for(let x=0;x<this._allData.length;x++)this._allData[x].tensor||(this._allInputIndices.push(x),this._allInputNames.push(y[x]));if(!a.output)throw new Error("missing information in graph: output");for(const x of a.output){if(s.has(x.name))throw new Error(`duplicated output name: ${x.name}`);const E=this._allData.push(new f(x))-1;s.set(x.name,E),this._allOutputIndices.push(E),this._allOutputNames.push(x.name)}if(!a.node)throw new Error("missing information in graph: node");for(const x of a.node){if(!x.name)for(let S=0;;S++){const P=`unnamed_${x.opType}_${S}`;if(!g.has(P)){x.name=P;break}}if(g.has(x.name))throw new Error(`duplicated node name: ${x.name}`);const E=this._nodes.push(new u(x))-1;g.set(x.name,E)}for(let x=0;x<this._nodes.length;x++){const E=this._nodes[x],S=a.node[x];if(!S.output)throw new Error(`missing output for node: ${S.name}`);for(const P of S.output){let O=s.get(P);if(O===void 0&&(O=this._allData.push(new f)-1,s.set(P,O)),E.outputs.push(O),this._allData[O]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${O}`);if(this._allData[O]._from=x,S.opType==="Constant"){if(!S.attribute||S.attribute.length!==1||!S.attribute[0].t)throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(!S.output||S.output.length!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");E.outputs.pop(),E.executeNode=!1,this._allData[O]._from=-1,this._allData[O].tensor=c.Tensor.fromProto(S.attribute[0].t)}}}for(let x=0;x<this._nodes.length;x++){const E=this._nodes[x],S=a.node[x];if(!S.input)throw new Error(`missing input for node: ${S.name}`);for(const P of S.input){const O=s.get(P);if(O===void 0){if(P===""&&S.input.length===3&&S.opType==="Resize")continue;throw new Error(`unrecognized input '${P}' for node: ${S.name}`)}E.inputs.push(O),this._allData[O]._to.push(x)}}return!0}buildGraphFromOrtFormat(a){var s,g,y;const x=new Map;this._allData=[],this._allInputIndices=[],this._allInputNames=[],this._allOutputIndices=[],this._allOutputNames=[],this._nodes=[];const E=new Map,S=[];for(let P=0;P<a.inputsLength();P++){const O=a.inputs(P);if(x.has(O))throw new Error(`duplicated input name: ${O}`);for(let k=0;k<a.nodeArgsLength();k++)if(((s=a.nodeArgs(k))===null||s===void 0?void 0:s.name())===O){const D=new f;if(((y=(g=a.nodeArgs(k))===null||g===void 0?void 0:g.type())===null||y===void 0?void 0:y.valueType())!==_.TypeInfoValue.tensor_type)throw new Error("Unexpected value type for the nodeArg.");const C=a.nodeArgs(k).type().value(new _.TensorTypeAndShape),A=m.ProtoUtil.tensorDataTypeFromProto(C.elemType()),$=C.shape(),W=[];for(let Y=0;Y<$.dimLength();Y++)W.push(m.LongUtil.longToNumber($.dim(Y).value().dimValue()));D.type={shape:{dims:W},tensorType:A};const K=this._allData.push(D)-1;x.set(O,K),S.push(O)}}for(let P=0;P<a.initializersLength();P++){const O=a.initializers(P);let k=x.get(O.name());if(k===void 0){const D=new f,C=m.ProtoUtil.tensorDimsFromORTFormat(O),A=m.ProtoUtil.tensorDataTypeFromProto(O.dataType());D.type={shape:{dims:C},tensorType:A},k=this._allData.push(D)-1,x.set(O.name(),k)}this._allData[k]._from=-1,this._allData[k].tensor=c.Tensor.fromOrtTensor(O)}for(let P=0;P<this._allData.length;P++)this._allData[P].tensor||(this._allInputIndices.push(P),this._allInputNames.push(S[P]));for(let P=0;P<a.outputsLength();P++){const O=a.outputs(P);if(x.has(O))throw new Error(`duplicated output name: ${O}`);const k=this._allData.push(new f)-1;x.set(O,k),this._allOutputIndices.push(k),this._allOutputNames.push(O)}if(!a.nodes)throw new Error("missing information in graph: node");for(let P=0;P<a.nodesLength();P++){const O=a.nodes(P);let k=O.name();if(!k)for(let C=0;k=`unnamed_${O.opType()}_${C}`,E.has(k);C++);if(E.has(k))throw new Error(`duplicated node name: ${k}`);const D=this._nodes.push(new u(O,k))-1;E.set(k,D)}for(let P=0;P<this._nodes.length;P++){const O=this._nodes[P],k=a.nodes(P);if(k==null)throw new Error(`No node exists at index ${P}`);if((k==null?void 0:k.outputsLength())===0)throw new Error(`missing output for node: ${k.name}`);for(let D=0;D<(k==null?void 0:k.outputsLength());D++){const C=k==null?void 0:k.outputs(D);let A=x.get(C);if(A===void 0&&(A=this._allData.push(new f)-1,x.set(C,A)),O.outputs.push(A),this._allData[A]._from!==void 0)throw new Error(`multiple nodes output to one data value: ${A}`);if(this._allData[A]._from=P,k.opType()==="Constant"){if(k.attributesLength()!==1||!k.attributes(0).t())throw new Error("missing attributes or missing tensor value in attributes for this Constant operator");if(k.outputsLength()!==1)throw new Error("missing output or incorrect number of outputs for this Constant operator");O.outputs.pop(),O.executeNode=!1,this._allData[A]._from=-1,this._allData[A].tensor=c.Tensor.fromOrtTensor(k.attributes(0).t())}}}for(let P=0;P<this._nodes.length;P++){const O=this._nodes[P],k=a.nodes(P);if(k.inputsLength()===0)throw new Error(`missing input for node: ${k.name}`);for(let D=0;D<k.inputsLength();D++){const C=k.inputs(D),A=x.get(C);if(A===void 0)throw new Error(`unrecognized input '${C}' for node: ${k.name()}`);O.inputs.push(A),this._allData[A]._to.push(P)}}}checkIsAcyclic(){const a=new Set;this._allInputIndices.forEach(y=>{this._allData[y]._to.forEach(x=>{a.add(x)})});const s=Array.from(a),g=new 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f{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 f).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsModel(n,e){return n.setPosition(n.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new f).__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 a=this.bb.__offset(this.bb_pos,6);return a?(e||new c.experimental.fbs.OperatorSetId).__init(this.bb.__indirect(this.bb.__vector(this.bb_pos+a)+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 c.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 a=e.length-1;a>=0;a--)n.addOffset(e[a]);return n.endVector()}static startOpsetImportVector(n,e){n.startVector(4,e,4)}static addProducerName(n,e){n.addFieldOffset(2,e,0)}static 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createSubGraphSessionStatesVector(n,e){n.startVector(4,e.length,4);for(let a=e.length-1;a>=0;a--)n.addOffset(e[a]);return n.endVector()}static startSubGraphSessionStatesVector(n,e){n.startVector(4,e,4)}static endSessionState(n){return n.endObject()}static createSessionState(n,e,a){return f.startSessionState(n),f.addKernels(n,e),f.addSubGraphSessionStates(n,a),f.endSessionState(n)}}_.SessionState=f})(m.fbs||(m.fbs={}))})(c.experimental||(c.experimental={}))}(o.onnxruntime||(o.onnxruntime={})),function(c){(function(m){(function(_){class f{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 f).__init(n.readInt32(n.position())+n.position(),n)}static getSizePrefixedRootAsInferenceSession(n,e){return n.setPosition(n.position()+l.flatbuffers.SIZE_PREFIX_LENGTH),(e||new f).__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 c.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 c.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,a,s){return f.startInferenceSession(n),f.addOrtVersion(n,e),f.addModel(n,a),f.addSessionState(n,s),f.endInferenceSession(n)}}_.InferenceSession=f})(m.fbs||(m.fbs={}))})(c.experimental||(c.experimental={}))}(o.onnxruntime||(o.onnxruntime={}))},7448:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.OnnxjsSessionHandler=void 0;const l=d(1670),p=d(9162);o.OnnxjsSessionHandler=class{constructor(b){this.session=b,this.inputNames=this.session.inputNames,this.outputNames=this.session.outputNames}async dispose(){}async run(b,c,m){const _=new Map;for(const n in b)if(Object.hasOwnProperty.call(b,n)){const e=b[n];_.set(n,new p.Tensor(e.dims,e.type,void 0,void 0,e.data))}const f=await this.session.run(_),u={};return f.forEach((n,e)=>{u[e]=new l.Tensor(n.type,n.data,n.dims)}),u}startProfiling(){this.session.startProfiling()}endProfiling(){this.session.endProfiling()}}},6919:(v,o,d)=>{Object.defineProperty(o,"__esModule",{value:!0}),o.Session=void 0;const l=d(7067),p=d(1296),b=d(7091),c=d(1036),m=d(6231),_=d(2644);o.Session=class{constructor(f={}){this._initialized=!1,this.backendHint=f.backendHint,this.profiler=m.Profiler.create(f.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(f,u,n){await this.profiler.event("session","Session.loadModel",async()=>{const e=await(0,b.resolveBackend)(this.backendHint);if(this.sessionHandler=e.createSessionHandler(this.context),this._model=new _.Model,typeof f=="string"){const a=f.endsWith(".ort");if(typeof fetch>"u"){const s=await(0,p.promisify)(l.readFile)(f);this.initialize(s,a)}else{const s=await fetch(f),g=await s.arrayBuffer();this.initialize(new Uint8Array(g),a)}}else if(ArrayBuffer.isView(f))this.initialize(f);else{const a=new Uint8Array(f,u||0,n||f.byteLength);this.initialize(a)}})}initialize(f,u){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(f,n,u),this.sessionHandler.onGraphInitialized&&this.sessionHandler.onGraphInitialized(this._model.graph),this.initializeOps(this._model.graph),this._executionPlan=new c.ExecutionPlan(this._model.graph,this._ops,this.profiler)}),this._initialized=!0}async run(f){if(!this._initialized)throw new Error("session not initialized yet");return this.profiler.event("session","Session.run",async()=>{const u=this.normalizeAndValidateInputs(f),n=await this._executionPlan.execute(this.sessionHandler,u);return this.createOutput(n)})}normalizeAndValidateInputs(f){const u=this._model.graph.getInputNames();if(Array.isArray(f)){if(f.length!==u.length)throw new Error(`incorrect input array length: expected ${u.length} but got ${f.length}`)}else{if(f.size!==u.length)throw new Error(`incorrect input map size: expected ${u.length} but got ${f.size}`);const n=new Array(f.size);let e=0;for(let a=0;a<u.length;++a){const s=f.get(u[a]);if(!s)throw new Error(`missing input tensor for: '${name}'`);n[e++]=s}f=n}if(this.context.graphInputTypes&&this.context.graphInputTypes.length!==0&&this.context.graphInputDims&&this.context.graphInputDims.length!==0)this.validateInputTensorDims(this.context.graphInputDims,f,!1);else{const n=this._model.graph.getInputIndices(),e=this._model.graph.getValues(),a=new Array(n.length);for(let s=0;s<n.length;++s){const g=e[n[s]];a[s]=g.type.shape.dims,this.context.graphInputTypes.push(g.type.tensorType),this.context.graphInputDims.push(f[s].dims)}this.validateInputTensorDims(a,f,!0)}return this.validateInputTensorTypes(this.context.graphInputTypes,f),f}validateInputTensorTypes(f,u){for(let n=0;n<u.length;n++){const e=f[n],a=u[n].type;if(e!==a)throw new Error(`input tensor[${n}] check failed: expected type '${e}' but got ${a}`)}}validateInputTensorDims(f,u,n){for(let e=0;e<u.length;e++){const a=f[e],s=u[e].dims;if(!this.compareTensorDims(a,s,n))throw new Error(`input tensor[${e}] check failed: expected shape '[${a.join(",")}]' but got [${s.join(",")}]`)}}compareTensorDims(f,u,n){if(f.length!==u.length)return!1;for(let e=0;e<f.length;++e)if(f[e]!==u[e]&&(!n||f[e]!==0))return!1;return!0}createOutput(f){const u=this._model.graph.getOutputNames();if(f.length!==u.length)throw new Error("expected number of outputs do not match number of generated outputs");const n=new Map;for(let e=0;e<u.length;++e)n.set(u[e],f[e]);return n}initializeOps(f){const u=f.getNodes();this._ops=new Array(u.length);for(let n=0;n<u.length;n++)this._ops[n]=this.sessionHandler.resolve(u[n],this._model.opsets,f)}}},9162:function(v,o,d){var l=this&&this.__importDefault||function(g){return g&&g.__esModule?g:{default:g}};Object.defineProperty(o,"__esModule",{value:!0}),o.Tensor=void 0;const p=d(3442),b=l(d(3720)),c=d(1446),m=d(9395),_=d(2517);var f=m.onnxruntime.experimental.fbs;class u{get data(){if(this.cache===void 0){const y=this.dataProvider(this.dataId);if(y.length!==this.size)throw new Error("Length of data provided by the Data Provider is inconsistent with the dims of this Tensor.");this.cache=y}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(y){return this.data[_.ShapeUtil.indicesToOffset(y,this.strides)]}set(y,x){this.data[_.ShapeUtil.indicesToOffset(y,this.strides)]=x}async getData(){return this.cache===void 0&&(this.cache=await this.asyncDataProvider(this.dataId)),this.cache}get strides(){return this._strides||(this._strides=_.ShapeUtil.computeStrides(this.dims)),this._strides}constructor(y,x,E,S,P,O=p.Guid.create()){this.dims=y,this.type=x,this.dataProvider=E,this.asyncDataProvider=S,this.cache=P,this.dataId=O,this.size=_.ShapeUtil.validateDimsAndCalcSize(y);const k=this.size,D=E===void 0&&S===void 0&&P===void 0;if(P!==void 0&&P.length!==k)throw new RangeError("Input dims doesn't match data length.");if(x==="string"){if(!(P===void 0||Array.isArray(P)&&P.every(C=>typeof C=="string")))throw new TypeError("cache should be a string array");D&&(this.cache=new Array(k))}else{if(P!==void 0){const C=e(x);if(!(P instanceof C))throw new TypeError(`cache should be type ${C.name}`)}if(D){const C=new ArrayBuffer(k*function(A){switch(A){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 ${A}`)}}(x));this.cache=function(A,$){return new(e($))(A)}(C,x)}}}static fromProto(y){if(!y)throw new Error("cannot construct Value from an empty tensor");const x=_.ProtoUtil.tensorDataTypeFromProto(y.dataType),E=_.ProtoUtil.tensorDimsFromProto(y.dims),S=new u(E,x);if(x==="string")y.stringData.forEach((P,O)=>{S.data[O]=(0,_.decodeUtf8String)(P)});else if(y.rawData&&typeof y.rawData.byteLength=="number"&&y.rawData.byteLength>0){const P=S.data,O=new DataView(y.rawData.buffer,y.rawData.byteOffset,y.rawData.byteLength),k=n(y.dataType),D=y.rawData.byteLength/k;if(y.rawData.byteLength%k!=0)throw new Error("invalid buffer length");if(P.length!==D)throw new Error("buffer length mismatch");for(let C=0;C<D;C++){const A=s(O,y.dataType,C*k);P[C]=A}}else{let P;switch(y.dataType){case c.onnx.TensorProto.DataType.FLOAT:P=y.floatData;break;case c.onnx.TensorProto.DataType.INT32:case c.onnx.TensorProto.DataType.INT16:case c.onnx.TensorProto.DataType.UINT16:case c.onnx.TensorProto.DataType.INT8:case c.onnx.TensorProto.DataType.UINT8:case c.onnx.TensorProto.DataType.BOOL:P=y.int32Data;break;case c.onnx.TensorProto.DataType.INT64:P=y.int64Data;break;case c.onnx.TensorProto.DataType.DOUBLE:P=y.doubleData;break;case c.onnx.TensorProto.DataType.UINT32:case c.onnx.TensorProto.DataType.UINT64:P=y.uint64Data;break;default:throw new Error("unspecific error")}if(P==null)throw new Error("failed to populate data from a tensorproto value");const O=S.data;if(O.length!==P.length)throw new Error("array length mismatch");for(let k=0;k<P.length;k++){const D=P[k];b.default.isLong(D)?O[k]=a(D,y.dataType):O[k]=D}}return S}static fromData(y,x,E){return new u(x,E,void 0,void 0,y)}static fromOrtTensor(y){if(!y)throw new Error("cannot construct Value from an empty tensor");const x=_.ProtoUtil.tensorDimsFromORTFormat(y),E=_.ProtoUtil.tensorDataTypeFromProto(y.dataType()),S=new u(x,E);if(E==="string")for(let P=0;P<y.stringDataLength();P++)S.data[P]=y.stringData(P);else if(y.rawDataArray()&&typeof y.rawDataLength()=="number"&&y.rawDataLength()>0){const P=S.data,O=new DataView(y.rawDataArray().buffer,y.rawDataArray().byteOffset,y.rawDataLength()),k=n(y.dataType()),D=y.rawDataLength()/k;if(y.rawDataLength()%k!=0)throw new Error("invalid buffer length");if(P.length!==D)throw new Error("buffer length mismatch");for(let C=0;C<D;C++){const A=s(O,y.dataType(),C*k);P[C]=A}}return S}}function n(g){switch(g){case c.onnx.TensorProto.DataType.UINT8:case c.onnx.TensorProto.DataType.INT8:case c.onnx.TensorProto.DataType.BOOL:return 1;case c.onnx.TensorProto.DataType.UINT16:case c.onnx.TensorProto.DataType.INT16:return 2;case c.onnx.TensorProto.DataType.FLOAT:case c.onnx.TensorProto.DataType.INT32:case c.onnx.TensorProto.DataType.UINT32:return 4;case c.onnx.TensorProto.DataType.INT64:case c.onnx.TensorProto.DataType.DOUBLE:case c.onnx.TensorProto.DataType.UINT64:return 8;default:throw new Error(`cannot calculate sizeof() on type ${c.onnx.TensorProto.DataType[g]}`)}}function e(g){switch(g){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 a(g,y){if(y===c.onnx.TensorProto.DataType.INT64||y===f.TensorDataType.INT64){if(g.greaterThanOrEqual(2147483648)||g.lessThan(-2147483648))throw new TypeError("int64 is not supported")}else{if(y!==c.onnx.TensorProto.DataType.UINT32&&y!==f.TensorDataType.UINT32&&y!==c.onnx.TensorProto.DataType.UINT64&&y!==f.TensorDataType.UINT64)throw new TypeError(`not a LONG type: ${c.onnx.TensorProto.DataType[y]}`);if(g.greaterThanOrEqual(4294967296)||g.lessThan(0))throw new TypeError("uint64 is not supported")}return g.toNumber()}function s(g,y,x){switch(y){case c.onnx.TensorProto.DataType.BOOL:case c.onnx.TensorProto.DataType.UINT8:return g.getUint8(x);case c.onnx.TensorProto.DataType.INT8:return g.getInt8(x);case c.onnx.TensorProto.DataType.UINT16:return g.getUint16(x,!0);case c.onnx.TensorProto.DataType.INT16:return g.getInt16(x,!0);case c.onnx.TensorProto.DataType.FLOAT:return g.getFloat32(x,!0);case c.onnx.TensorProto.DataType.INT32:return g.getInt32(x,!0);case c.onnx.TensorProto.DataType.UINT32:return g.getUint32(x,!0);case c.onnx.TensorProto.DataType.INT64:return a(b.default.fromBits(g.getUint32(x,!0),g.getUint32(x+4,!0),!1),y);case c.onnx.TensorProto.DataType.DOUBLE:return g.getFloat64(x,!0);case c.onnx.TensorProto.DataType.UINT64:return a(b.default.fromBits(g.getUint32(x,!0),g.getUint32(x+4,!0),!0),y);default:throw new Error(`cannot read from DataView for type ${c.onnx.TensorProto.DataType[y]}`)}}o.Tensor=u},2517:function(v,o,d){var l=this&&this.__importDefault||function(y){return y&&y.__esModule?y:{default:y}};Object.defineProperty(o,"__esModule",{value:!0}),o.decodeUtf8String=o.MAX_CLIP=o.MIN_CLIP=o.PoolConvUtil=o.ReduceUtil=o.SplitUtil=o.MathUtil=o.ShapeUtil=o.LongUtil=o.ProtoUtil=o.GemmUtil=o.arrayCopyHelper=o.BroadcastUtil=o.MatMulUtil=o.ArrayUtil=o.assert=o.checkInputsShape=void 0;const p=d(5686),b=l(d(3720)),c=d(1446),m=d(9162);o.checkInputsShape=function(y,...x){if(!y||y.length!==x.length)return!1;for(let E=0;E<y.length;E++)if(!y[E].dims||y[E].dims.length!==x[E])return!1;return!0},o.assert=function(y,x){if(!y)throw new Error(typeof x=="string"?x:x())},o.ArrayUtil=class{static arraysEqual(y,x){if(y.length!==x.length)return!1;for(let E=0;E<y.length;E++)if(y[E]!==x[E])return!1;return!0}};class _{static preprocessInputShapes(x,E){return[x.length===1?[1,x[0]]:x,E.length===1?[E[0],1]:E]}static postprocessOutputShape(x,E,S){E===1&&x.splice(x.length-2,1),S===1&&x.pop()}static calcMatMulShape(x,E){return x[1]!==E[0]?void 0:[x[0],E[1]]}}o.MatMulUtil=_;class f{static calcShape(x,E,S=!1){const P=x.length,O=E.length;if(P===0)return E;if(O===0)return x;const k=Math.max(x.length,E.length),D=new Array(k);if(S){if(P<2||O<2)return;const C=_.calcMatMulShape([x[P-2],x[P-1]],[E[O-2],E[O-1]]);if(C===void 0)return;[D[k-2],D[k-1]]=C}for(let C=S?3:1;C<=k;C++){const A=P-C<0?1:x[P-C],$=O-C<0?1:E[O-C];if(A!==$&&A>1&&$>1)return;D[k-C]=Math.max(A,$)}return D}static index(x,E){const S=new Array(E.length);return f.fillIndex(x,E,S),S}static fillIndex(x,E,S){const P=x.length-E.length;for(let O=0;O<E.length;O++)S[O]=x[P+O]%E[O]}static calc(x,E,S,P,O){const k=f.calcShape(x.dims,E.dims);if(k){if(P&&!e.areEqual(k,x.dims))return;const D=e.size(k),C=P?x:new m.Tensor(k,O||x.type);if(k.length===0)C.set([],S(x.get([]),E.get([])));else{const A=new Array(k.length),$=new Array(x.dims.length),W=new Array(E.dims.length);let K,Y=0,q=0,se=!1,F=!1;x.dims.length===0&&(Y=x.get([]),se=!0),E.dims.length===0&&(q=E.get([]),F=!0);for(let B=0;B<D;B++){K=B;for(let fe=k.length-1;fe>=0;fe--)A[fe]=K%k[fe],K=Math.floor(K/k[fe]);se||(f.fillIndex(A,x.dims,$),Y=x.get($)),F||(f.fillIndex(A,E.dims,W),q=E.get(W)),C.set(A,S(Y,q))}}return C}}static isValidBroadcast(x,E){const S=x.length,P=E.length;if(S>P)return!1;for(let O=1;O<=S;O++)if(x[S-O]!==1&&x[S-O]!==E[P-O])return!1;return!0}static getBroadcastDims(x,E){const S=x.length,P=[];for(let O=0;O<S;O++){const k=S-1-O,D=x[k]||1;(E[E.length-1-O]||1)>1&&D===1&&P.unshift(k)}return P}}o.BroadcastUtil=f,o.arrayCopyHelper=function(y,x,E,S,P){if(S<0||S>=x.length)throw new Error("sourceIndex out of bounds");if(E<0||E>=y.length)throw new Error("targetIndex out of bounds");if(S+P>x.length)throw new Error("source indices to be copied are outside bounds");if(E+P>y.length)throw new Error("target array is too small to hold result");for(let O=0;O<P;O++)y[E+O]=x[S+O]},o.GemmUtil=class{static getShapeOfGemmResult(y,x,E,S,P){if(y.length!==2||E.length!==2)throw new Error("shape need to be of size 2");let O,k,D;x?(O=y[1],k=y[0]):(O=y[0],k=y[1]);let C=-1;if(S?(D=E[0],C=1):(D=E[1],C=0),E[C]!==k)throw new Error("dimension mismatch");if(O<=0||D<=0||k<=0)throw new Error("invalid shape specified");if(P&&!f.isValidBroadcast(P,[O,D]))throw new Error("gemm: invalid bias shape for broadcast");return[O,D,k]}};class u{static tensorDataTypeFromProto(x){switch(x){case c.onnx.TensorProto.DataType.INT8:return"int8";case c.onnx.TensorProto.DataType.UINT8:return"uint8";case c.onnx.TensorProto.DataType.BOOL:return"bool";case c.onnx.TensorProto.DataType.INT16:return"int16";case c.onnx.TensorProto.DataType.UINT16:return"uint16";case c.onnx.TensorProto.DataType.INT32:return"int32";case c.onnx.TensorProto.DataType.UINT32:return"uint32";case c.onnx.TensorProto.DataType.FLOAT:return"float32";case c.onnx.TensorProto.DataType.DOUBLE:return"float64";case c.onnx.TensorProto.DataType.STRING:return"string";case c.onnx.TensorProto.DataType.INT64:return"int32";case c.onnx.TensorProto.DataType.UINT64:return"uint32";default:throw new Error(`unsupported data type: ${c.onnx.TensorProto.DataType[x]}`)}}static tensorDataTypeStringToEnum(x){switch(x){case"int8":return c.onnx.TensorProto.DataType.INT8;case"uint8":return c.onnx.TensorProto.DataType.UINT8;case"bool":return c.onnx.TensorProto.DataType.BOOL;case"int16":return c.onnx.TensorProto.DataType.INT16;case"uint16":return c.onnx.TensorProto.DataType.UINT16;case"int32":return c.onnx.TensorProto.DataType.INT32;case"uint32":return c.onnx.TensorProto.DataType.UINT32;case"float32":return c.onnx.TensorProto.DataType.FLOAT;case"float64":return c.onnx.TensorProto.DataType.DOUBLE;case"string":return c.onnx.TensorProto.DataType.STRING;case"int64":return c.onnx.TensorProto.DataType.INT64;case"uint64":return c.onnx.TensorProto.DataType.UINT64;default:throw new Error(`unsupported data type: ${x}`)}}static tensorDimsFromProto(x){return x.map(E=>b.default.isLong(E)?E.toNumber():E)}static tensorValueTypeFromProto(x){return{tensorType:u.tensorDataTypeFromProto(x.elemType),shape:{dims:u.tensorDimsFromProto(x.shape.dim.map(E=>E.dimValue))}}}static tensorDimsFromORTFormat(x){const E=[];for(let S=0;S<x.dimsLength();S++)E.push(n.longToNumber(x.dims(S)));return E}static tensorAttributesFromORTFormat(x){const E=[];for(let S=0;S<x.attributesLength();S++)E.push(x.attributes(S));return E}}o.ProtoUtil=u;class n{static longToNumber(x,E){return b.default.isLong(x)?x.toNumber():x instanceof p.flatbuffers.Long?b.default.fromValue({low:x.low,high:x.high,unsigned:E!=null&&E}).toNumber():x}static isLong(x){return b.default.isLong(x)||x instanceof p.flatbuffers.Long}}o.LongUtil=n;class e{static size(x){return e.getSizeFromDimensionRange(x,0,x.length)}static sizeFromDimension(x,E){if(E<0||E>x.length)throw new Error(`invalid dimension of ${E} for sizeFromDimension as Tensor has ${x.length} dimensions.`);return e.getSizeFromDimensionRange(x,E,x.length)}static sizeToDimension(x,E){if(E<0||E>x.length)throw new Error(`invalid dimension of ${E} for sizeToDimension as Tensor has ${x.length} dimensions.`);return e.getSizeFromDimensionRange(x,0,E)}static getSizeFromDimensionRange(x,E,S){let P=1;for(let O=E;O<S;O++){if(x[O]<=0)throw new Error("cannot get valid size from specified dimension range. 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env$1={version:VERSION,remoteHost:"https://huggingface.co/",remotePathTemplate:"{model}/resolve/{revision}/",localModelPath,useFS:FS_AVAILABLE,useBrowserCache:WEB_CACHE_AVAILABLE,useFSCache:FS_AVAILABLE,cacheDir:DEFAULT_CACHE_DIR};function isEmpty(v){return Object.keys(v).length===0}var define_process_env_default={};class FileResponse{constructor(o){if(Ht(this,"_CONTENT_TYPE_MAP",{txt:"text/plain",html:"text/html",css:"text/css",js:"text/javascript",json:"application/json",png:"image/png",jpg:"image/jpeg",jpeg:"image/jpeg",gif:"image/gif"}),this.filePath=o,this.headers=new Headers,this.exists=sharp.existsSync(o),this.exists){this.status=200,this.statusText="OK";let d=sharp.statSync(o);this.headers.set("content-length",d.size.toString()),this.updateContentType();let l=this;this.body=new ReadableStream({start(p){l.arrayBuffer().then(b=>{p.enqueue(new Uint8Array(b)),p.close()})}})}else this.status=404,this.statusText="Not Found",this.body=null}updateContentType(){const 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d=!!(define_process_env_default!=null&&define_process_env_default.TESTING_REMOTELY),l=env$1.version,p=new Headers;if(p.set("User-Agent",`transformers.js/${l}; is_ci/${d};`),isValidUrl(v,["http:","https:"],["huggingface.co","hf.co"])){const b=(define_process_env_default==null?void 0:define_process_env_default.HF_TOKEN)??(define_process_env_default==null?void 0:define_process_env_default.HF_ACCESS_TOKEN);b&&p.set("Authorization",`Bearer ${b}`)}return fetch(v,{headers:p})}else return fetch(v)}const ERROR_MAPPING={400:"Bad request error occurred while trying to load file",401:"Unauthorized access to file",403:"Forbidden access to file",404:"Could not locate file",408:"Request timeout error occurred while trying to load file",500:"Internal server error error occurred while trying to load file",502:"Bad gateway error occurred while trying to load file",503:"Service unavailable error occurred while trying to load file",504:"Gateway timeout error occurred while trying to load file"};function 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P2FFT{constructor(o){if(this.size=o|0,this.size<=1||!isPowerOfTwo(this.size))throw new Error("FFT size must be a power of two larger than 1");this._csize=o<<1,this.table=new Float64Array(this.size*2);for(let l=0;l<this.table.length;l+=2){const p=Math.PI*l/this.size;this.table[l]=Math.cos(p),this.table[l+1]=-Math.sin(p)}let d=0;for(let l=1;this.size>l;l<<=1)++d;this._width=d%2===0?d-1:d,this._bitrev=new Int32Array(1<<this._width);for(let l=0;l<this._bitrev.length;++l){this._bitrev[l]=0;for(let p=0;p<this._width;p+=2){const b=this._width-p-2;this._bitrev[l]|=(l>>>p&3)<<b}}}createComplexArray(){return new Float64Array(this._csize)}fromComplexArray(o,d){const l=d||new Array(o.length>>>1);for(let p=0;p<o.length;p+=2)l[p>>>1]=o[p];return l}toComplexArray(o,d){const l=d||this.createComplexArray();for(let p=0;p<l.length;p+=2)l[p]=o[p>>>1],l[p+1]=0;return l}transform(o,d){if(o===d)throw new Error("Input and output buffers must be different");this._transform4(o,d,1)}realTransform(o,d){if(o===d)throw new Error("Input and output buffers must be different");this._realTransform4(o,d,1)}inverseTransform(o,d){if(o===d)throw new Error("Input and output buffers must be different");this._transform4(o,d,-1);for(let l=0;l<o.length;++l)o[l]/=this.size}_transform4(o,d,l){const p=this._csize;let b=1<<this._width,c=p/b<<1,m,_;const f=this._bitrev;if(c===4)for(m=0,_=0;m<p;m+=c,++_){const n=f[_];this._singleTransform2(d,o,m,n,b)}else for(m=0,_=0;m<p;m+=c,++_){const n=f[_];this._singleTransform4(d,o,m,n,b,l)}const u=this.table;for(b>>=2;b>=2;b>>=2){c=p/b<<1;const n=c>>>2;for(m=0;m<p;m+=c){const e=m+n-1;for(let a=m,s=0;a<e;a+=2,s+=b){const g=a,y=g+n,x=y+n,E=x+n,S=o[g],P=o[g+1],O=o[y],k=o[y+1],D=o[x],C=o[x+1],A=o[E],$=o[E+1],W=u[s],K=l*u[s+1],Y=O*W-k*K,q=O*K+k*W,se=u[2*s],F=l*u[2*s+1],B=D*se-C*F,fe=D*F+C*se,ne=u[3*s],z=l*u[3*s+1],Q=A*ne-$*z,re=A*z+$*ne,ue=S+B,_e=P+fe,ve=S-B,we=P-fe,Ae=Y+Q,Me=q+re,tt=l*(Y-Q),Ze=l*(q-re);o[g]=ue+Ae,o[g+1]=_e+Me,o[y]=ve+Ze,o[y+1]=we-tt,o[x]=ue-Ae,o[x+1]=_e-Me,o[E]=ve-Ze,o[E+1]=we+tt}}}}_singleTransform2(o,d,l,p,b){const c=o[p],m=o[p+1],_=o[p+b],f=o[p+b+1];d[l]=c+_,d[l+1]=m+f,d[l+2]=c-_,d[l+3]=m-f}_singleTransform4(o,d,l,p,b,c){const m=b*2,_=b*3,f=o[p],u=o[p+1],n=o[p+b],e=o[p+b+1],a=o[p+m],s=o[p+m+1],g=o[p+_],y=o[p+_+1],x=f+a,E=u+s,S=f-a,P=u-s,O=n+g,k=e+y,D=c*(n-g),C=c*(e-y);d[l]=x+O,d[l+1]=E+k,d[l+2]=S+C,d[l+3]=P-D,d[l+4]=x-O,d[l+5]=E-k,d[l+6]=S-C,d[l+7]=P+D}_realTransform4(o,d,l){const p=this._csize;let b=1<<this._width,c=p/b<<1,m,_;const f=this._bitrev;if(c===4)for(m=0,_=0;m<p;m+=c,++_){const e=f[_];this._singleRealTransform2(d,o,m,e>>>1,b>>>1)}else for(m=0,_=0;m<p;m+=c,++_){const e=f[_];this._singleRealTransform4(d,o,m,e>>>1,b>>>1,l)}const u=this.table;for(b>>=2;b>=2;b>>=2){c=p/b<<1;const e=c>>>1,a=e>>>1,s=a>>>1;for(m=0;m<p;m+=c)for(let g=0,y=0;g<=s;g+=2,y+=b){const x=m+g,E=x+a,S=E+a,P=S+a,O=o[x],k=o[x+1],D=o[E],C=o[E+1],A=o[S],$=o[S+1],W=o[P],K=o[P+1],Y=O,q=k,se=u[y],F=l*u[y+1],B=D*se-C*F,fe=D*F+C*se,ne=u[2*y],z=l*u[2*y+1],Q=A*ne-$*z,re=A*z+$*ne,ue=u[3*y],_e=l*u[3*y+1],ve=W*ue-K*_e,we=W*_e+K*ue,Ae=Y+Q,Me=q+re,tt=Y-Q,Ze=q-re,ot=B+ve,Ue=fe+we,Qe=l*(B-ve),nt=l*(fe-we);if(o[x]=Ae+ot,o[x+1]=Me+Ue,o[E]=tt+nt,o[E+1]=Ze-Qe,g===0){o[S]=Ae-ot,o[S+1]=Me-Ue;continue}if(g===s)continue;const Lt=m+a-g,Bt=m+e-g;o[Lt]=tt-l*nt,o[Lt+1]=-Ze-l*Qe,o[Bt]=Ae-l*ot,o[Bt+1]=-Me+l*Ue}}const n=p>>>1;for(let e=2;e<n;e+=2)o[p-e]=o[e],o[p-e+1]=-o[e+1]}_singleRealTransform2(o,d,l,p,b){const c=o[p],m=o[p+b];d[l]=c+m,d[l+1]=0,d[l+2]=c-m,d[l+3]=0}_singleRealTransform4(o,d,l,p,b,c){const m=b*2,_=b*3,f=o[p],u=o[p+b],n=o[p+m],e=o[p+_],a=f+n,s=f-n,g=u+e,y=c*(u-e);d[l]=a+g,d[l+1]=0,d[l+2]=s,d[l+3]=-y,d[l+4]=a-g,d[l+5]=0,d[l+6]=s,d[l+7]=y}}class NP2FFT{constructor(o){const d=2*(o-1),l=2*(2*o-1),p=2**Math.ceil(Math.log2(l));this.bufferSize=p,this._a=d;const b=new Float64Array(l),c=new Float64Array(p);this._chirpBuffer=new Float64Array(p),this._buffer1=new Float64Array(p),this._buffer2=new Float64Array(p),this._outBuffer1=new Float64Array(p),this._outBuffer2=new Float64Array(p);const m=-2*Math.PI/o,_=Math.cos(m),f=Math.sin(m);for(let u=0;u<l>>1;++u){const n=(u+1-o)**2/2,e=Math.sqrt(_**2+f**2)**n,a=n*Math.atan2(f,_),s=2*u;b[s]=e*Math.cos(a),b[s+1]=e*Math.sin(a),c[s]=b[s],c[s+1]=-b[s+1]}this._slicedChirpBuffer=b.subarray(d,l),this._f=new P2FFT(p>>1),this._f.transform(this._chirpBuffer,c)}_transform(o,d,l){const p=this._buffer1,b=this._buffer2,c=this._outBuffer1,m=this._outBuffer2,_=this._chirpBuffer,f=this._slicedChirpBuffer,u=this._a;if(l)for(let n=0;n<f.length;n+=2){const e=n+1,a=n>>1,s=d[a];p[n]=s*f[n],p[e]=s*f[e]}else for(let n=0;n<f.length;n+=2){const e=n+1;p[n]=d[n]*f[n]-d[e]*f[e],p[e]=d[n]*f[e]+d[e]*f[n]}this._f.transform(c,p);for(let n=0;n<_.length;n+=2){const e=n+1;b[n]=c[n]*_[n]-c[e]*_[e],b[e]=c[n]*_[e]+c[e]*_[n]}this._f.inverseTransform(m,b);for(let n=0;n<m.length;n+=2){const e=m[n+u],a=m[n+u+1],s=f[n],g=f[n+1];o[n]=e*s-a*g,o[n+1]=e*g+a*s}}transform(o,d){this._transform(o,d,!1)}realTransform(o,d){this._transform(o,d,!0)}}class FFT{constructor(o){this.fft_length=o,this.isPowerOfTwo=isPowerOfTwo(o),this.isPowerOfTwo?(this.fft=new P2FFT(o),this.outputBufferSize=2*o):(this.fft=new NP2FFT(o),this.outputBufferSize=this.fft.bufferSize)}realTransform(o,d){this.fft.realTransform(o,d)}transform(o,d){this.fft.transform(o,d)}}function medianFilter(v,o){if(o%2===0||o<=0)throw new Error("Window size must be a positive odd number");const d=new v.constructor(v.length),l=new v.constructor(o),p=Math.floor(o/2);for(let b=0;b<v.length;++b){let c=0;for(let m=-p;m<=p;++m){let _=b+m;_<0?_=Math.abs(_):_>=v.length&&(_=2*(v.length-1)-_),l[c++]=v[_]}l.sort(),d[b]=l[p]}return d}function bankers_round(v){const o=Math.round(v);return Math.abs(v)%1===.5?o%2===0?o:o-1:o}const DataTypeMap=Object.freeze({float32:Float32Array,float64:Float64Array,string:Array,int8:Int8Array,uint8:Uint8Array,int16:Int16Array,uint16:Uint16Array,int32:Int32Array,uint32:Uint32Array,int64:BigInt64Array,uint64:BigUint64Array,bool:Uint8Array}),ONNXTensor$1=ONNX.Tensor;class Tensor{constructor(...o){return Ht(this,"dims"),Ht(this,"type"),Ht(this,"data"),Ht(this,"size"),o[0]instanceof ONNXTensor$1?Object.assign(this,o[0]):Object.assign(this,new ONNXTensor$1(o[0],o[1],o[2])),new Proxy(this,{get:(d,l)=>{if(typeof l=="string"){let p=Number(l);if(Number.isInteger(p))return d._getitem(p)}return d[l]},set:(d,l,p)=>d[l]=p})}*[Symbol.iterator](){const[o,...d]=this.dims;if(d.length>0){const l=d.reduce((p,b)=>p*b);for(let p=0;p<o;++p)yield this._subarray(p,l,d)}else yield*this.data}_getitem(o){const[d,...l]=this.dims;if(o=safeIndex(o,d),l.length>0){const p=l.reduce((b,c)=>b*c);return this._subarray(o,p,l)}else return new Tensor(this.type,[this.data[o]],l)}indexOf(o){for(let d=0;d<this.data.length;++d)if(this.data[d]==o)return d;return-1}_subarray(o,d,l){const p=o*d,b=(o+1)*d,c="subarray"in this.data?this.data.subarray(p,b):this.data.slice(p,b);return new Tensor(this.type,c,l)}item(){if(this.data.length!==1)throw new Error(`a Tensor with ${this.data.length} elements cannot be converted to Scalar`);return this.data[0]}tolist(){return reshape(this.data,this.dims)}sigmoid(){return this.clone().sigmoid_()}sigmoid_(){for(let o=0;o<this.data.length;++o)this.data[o]=1/(1+Math.exp(-this.data[o]));return this}mul(o){return this.clone().mul_(o)}mul_(o){for(let d=0;d<this.data.length;++d)this.data[d]*=o;return this}add(o){return this.clone().add_(o)}add_(o){for(let d=0;d<this.data.length;++d)this.data[d]+=o;return this}clone(){return new Tensor(this.type,this.data.slice(),this.dims.slice())}slice(...o){let d=[],l=[];for(let _=0;_<this.dims.length;++_){let f=o[_];if(f==null)l.push([0,this.dims[_]]),d.push(this.dims[_]);else if(typeof f=="number")f=safeIndex(f,this.dims[_],_),l.push([f,f+1]);else if(Array.isArray(f)&&f.length===2){if(f[0]>f[1])throw new Error(`Invalid slice: ${f}`);let u=[Math.max(f[0],0),Math.min(f[1],this.dims[_])];l.push(u),d.push(u[1]-u[0])}else throw new Error(`Invalid slice: ${f}`)}let p=l.map(([_,f])=>f-_),b=p.reduce((_,f)=>_*f),c=new this.data.constructor(b);const m=this.stride();for(let _=0;_<b;++_){let f=0;for(let u=p.length-1,n=_;u>=0;--u){const e=p[u];f+=(n%e+l[u][0])*m[u],n=Math.floor(n/e)}c[_]=this.data[f]}return new Tensor(this.type,c,d)}permute(...o){return permute(this,o)}transpose(...o){return this.permute(...o)}sum(o=null,d=!1){return this.norm(1,o,d)}norm(o="fro",d=null,l=!1){if(o==="fro")o=2;else if(typeof o=="string")throw Error(`Unsupported norm: ${o}`);if(d===null){let c=this.data.reduce((m,_)=>m+_**o,0)**(1/o);return new Tensor(this.type,[c],[])}d=safeIndex(d,this.dims.length);const p=this.dims.slice();p[d]=1;const b=new this.data.constructor(this.data.length/this.dims[d]);for(let c=0;c<this.data.length;++c){let m=0;for(let _=this.dims.length-1,f=c,u=1;_>=0;--_){const n=this.dims[_];if(_!==d){const e=f%n;m+=e*u,u*=p[_]}f=Math.floor(f/n)}b[m]+=this.data[c]**o}if(o!==1)for(let c=0;c<b.length;++c)b[c]=b[c]**(1/o);return l||p.splice(d,1),new Tensor(this.type,b,p)}normalize_(o=2,d=1){d=safeIndex(d,this.dims.length);const l=this.norm(o,d,!0);for(let p=0;p<this.data.length;++p){let b=0;for(let c=this.dims.length-1,m=p,_=1;c>=0;--c){const f=this.dims[c];if(c!==d){const u=m%f;b+=u*_,_*=this.dims[c]}m=Math.floor(m/f)}this.data[p]/=l.data[b]}return this}normalize(o=2,d=1){return this.clone().normalize_(o,d)}stride(){return dimsToStride(this.dims)}squeeze(o=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,o))}squeeze_(o=null){return this.dims=calc_squeeze_dims(this.dims,o),this}unsqueeze(o=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,o))}unsqueeze_(o=null){return this.dims=calc_unsqueeze_dims(this.dims,o),this}flatten_(o=0,d=-1){d=(d+this.dims.length)%this.dims.length;let l=this.dims.slice(0,o),p=this.dims.slice(o,d+1),b=this.dims.slice(d+1);return this.dims=[...l,p.reduce((c,m)=>c*m,1),...b],this}flatten(o=0,d=-1){return this.clone().flatten_(o,d)}view(...o){let d=-1;for(let l=0;l<o.length;++l)if(o[l]===-1){if(d!==-1)throw new Error("Only one dimension can be inferred");d=l}if(d!==-1){const l=o.reduce((p,b,c)=>c!==d?p*b:p,1);o[d]=this.data.length/l}return new Tensor(this.type,this.data,o)}neg_(){for(let o=0;o<this.data.length;++o)this.data[o]=-this.data[o];return this}neg(){return this.clone().neg_()}clamp_(o,d){for(let l=0;l<this.data.length;++l)this.data[l]=Math.min(Math.max(this.data[l],o),d);return this}clamp(o,d){return this.clone().clamp_(o,d)}round_(){for(let o=0;o<this.data.length;++o)this.data[o]=Math.round(this.data[o]);return this}round(){return this.clone().round_()}to(o){if(this.type===o)return this;if(!DataTypeMap.hasOwnProperty(o))throw new Error(`Unsupported type: ${o}`);return new Tensor(o,DataTypeMap[o].from(this.data),this.dims)}}function reshape(v,o){const d=v.length,l=o.reduce((b,c)=>b*c);if(d!==l)throw Error(`cannot reshape array of size ${d} into shape (${o})`);let p=v;for(let b=o.length-1;b>=0;b--)p=p.reduce((c,m)=>{let _=c[c.length-1];return _.length<o[b]?_.push(m):c.push([m]),c},[[]]);return p[0]}function permute(v,o){const[d,l]=permute_data(v.data,v.dims,o);return new Tensor(v.type,d,l)}function interpolate(v,[o,d],l="bilinear",p=!1){const b=v.dims.at(-3)??1,c=v.dims.at(-2),m=v.dims.at(-1);let _=interpolate_data(v.data,[b,c,m],[o,d],l,p);return new Tensor(v.type,_,[b,o,d])}function calc_squeeze_dims(v,o){return v=v.slice(),o===null?v=v.filter(d=>d!==1):typeof o=="number"?v[o]===1&&v.splice(o,1):Array.isArray(o)&&(v=v.filter((d,l)=>d!==1||!o.includes(l))),v}function calc_unsqueeze_dims(v,o){return o=safeIndex(o,v.length+1),v=v.slice(),v.splice(o,0,1),v}function safeIndex(v,o,d=null){if(v<-o||v>=o)throw new Error(`IndexError: index ${v} is out of bounds for dimension${d===null?"":" "+d} with size ${o}`);return v<0&&(v=(v%o+o)%o),v}function cat(v,o=0){o=safeIndex(o,v[0].dims.length);const d=v[0].dims.slice();d[o]=v.reduce((c,m)=>c+m.dims[o],0);const l=d.reduce((c,m)=>c*m,1),p=new v[0].data.constructor(l),b=v[0].type;if(o===0){let c=0;for(let m of v)p.set(m.data,c),c+=m.data.length}else{let c=0;for(let m=0;m<v.length;++m){let _=v[m];for(let f=0;f<_.data.length;++f){let u=0;for(let n=_.dims.length-1,e=f,a=1;n>=0;--n){const s=_.dims[n];let g=e%s;n===o&&(g+=c),u+=g*a,a*=d[n],e=Math.floor(e/s)}p[u]=_.data[f]}c+=_.dims[o]}}return new Tensor(b,p,d)}function stack(v,o=0){return cat(v.map(d=>d.unsqueeze(o)),o)}function std_mean(v,o=null,d=1,l=!1){if(o===null){const m=v.data.reduce((u,n)=>u+n,0)/v.data.length,_=Math.sqrt(v.data.reduce((u,n)=>u+(n-m)**2,0)/(v.data.length-d)),f=new Tensor(v.type,[m],[]);return[new Tensor(v.type,[_],[]),f]}o=safeIndex(o,v.dims.length);const p=mean(v,o,l),b=v.dims.slice();b[o]=1;const c=new v.data.constructor(v.data.length/v.dims[o]);for(let m=0;m<v.data.length;++m){let _=0;for(let f=v.dims.length-1,u=m,n=1;f>=0;--f){const e=v.dims[f];if(f!==o){const a=u%e;_+=a*n,n*=b[f]}u=Math.floor(u/e)}c[_]+=(v.data[m]-p.data[_])**2}for(let m=0;m<c.length;++m)c[m]=Math.sqrt(c[m]/(v.dims[o]-d));return l||b.splice(o,1),[new Tensor(v.type,c,b),p]}function mean(v,o=null,d=!1){if(o===null){let b=v.data.reduce((c,m)=>c+m,0);return new Tensor(v.type,[b/v.data.length],[])}o=safeIndex(o,v.dims.length);const l=v.dims.slice();l[o]=1;const p=new v.data.constructor(v.data.length/v.dims[o]);for(let b=0;b<v.data.length;++b){let c=0;for(let m=v.dims.length-1,_=b,f=1;m>=0;--m){const u=v.dims[m];if(m!==o){const n=_%u;c+=n*f,f*=l[m]}_=Math.floor(_/u)}p[c]+=v.data[b]}if(v.dims[o]!==1)for(let b=0;b<p.length;++b)p[b]=p[b]/v.dims[o];return d||l.splice(o,1),new Tensor(v.type,p,l)}function dynamicTimeWarping(v){const[o,d]=v.dims,l=[o+1,d+1],p=new Tensor("float32",new Float32Array(l[0]*l[1]).fill(1/0),l),b=new Tensor("float32",new Float32Array(l[0]*l[1]).fill(-1),l);p[0].data[0]=0;for(let u=1;u<d+1;++u)for(let n=1;n<o+1;++n){const e=p[n-1][u-1].item(),a=p[n-1][u].item(),s=p[n][u-1].item();let g,y;e<a&&e<s?(g=e,y=0):a<e&&a<s?(g=a,y=1):(g=s,y=2),p[n].data[u]=v[n-1][u-1].item()+g,b[n].data[u]=y}let c=o,m=d;b.data.fill(2,0,l[1]);for(let u=0;u<l[0];++u)b[u].data[0]=1;let _=[],f=[];for(;c>0||m>0;)switch(_.push(c-1),f.push(m-1),b[c][m].item()){case 0:--c,--m;break;case 1:--c;break;case 2:--m;break;default:throw new Error(`Internal error in dynamic time warping. Unexpected trace[${c}, ${m}]. Please file a bug report.`)}return _.reverse(),f.reverse(),[_,f]}function dimsToStride(v){const o=new Array(v.length);for(let d=v.length-1,l=1;d>=0;--d)o[d]=l,l*=v[d];return o}function ones(v){const o=v.reduce((d,l)=>d*l,1);return new Tensor("int64",new BigInt64Array(o).fill(1n),v)}function ones_like(v){return ones(v.dims)}var TOKEN_TYPES=Object.freeze({Text:"Text",NumericLiteral:"NumericLiteral",BooleanLiteral:"BooleanLiteral",StringLiteral:"StringLiteral",Identifier:"Identifier",Equals:"Equals",OpenParen:"OpenParen",CloseParen:"CloseParen",OpenStatement:"OpenStatement",CloseStatement:"CloseStatement",OpenExpression:"OpenExpression",CloseExpression:"CloseExpression",OpenSquareBracket:"OpenSquareBracket",CloseSquareBracket:"CloseSquareBracket",OpenCurlyBracket:"OpenCurlyBracket",CloseCurlyBracket:"CloseCurlyBracket",Comma:"Comma",Dot:"Dot",Colon:"Colon",Pipe:"Pipe",CallOperator:"CallOperator",AdditiveBinaryOperator:"AdditiveBinaryOperator",MultiplicativeBinaryOperator:"MultiplicativeBinaryOperator",ComparisonBinaryOperator:"ComparisonBinaryOperator",UnaryOperator:"UnaryOperator",Set:"Set",If:"If",For:"For",In:"In",Is:"Is",NotIn:"NotIn",Else:"Else",EndIf:"EndIf",ElseIf:"ElseIf",EndFor:"EndFor",And:"And",Or:"Or",Not:"UnaryOperator"});Object.freeze({set:TOKEN_TYPES.Set,for:TOKEN_TYPES.For,in:TOKEN_TYPES.In,is:TOKEN_TYPES.Is,if:TOKEN_TYPES.If,else:TOKEN_TYPES.Else,endif:TOKEN_TYPES.EndIf,elif:TOKEN_TYPES.ElseIf,endfor:TOKEN_TYPES.EndFor,and:TOKEN_TYPES.And,or:TOKEN_TYPES.Or,not:TOKEN_TYPES.Not,"not in":TOKEN_TYPES.NotIn,true:TOKEN_TYPES.BooleanLiteral,false:TOKEN_TYPES.BooleanLiteral});TOKEN_TYPES.OpenStatement,TOKEN_TYPES.CloseStatement,TOKEN_TYPES.OpenExpression,TOKEN_TYPES.CloseExpression,TOKEN_TYPES.OpenParen,TOKEN_TYPES.CloseParen,TOKEN_TYPES.OpenCurlyBracket,TOKEN_TYPES.CloseCurlyBracket,TOKEN_TYPES.OpenSquareBracket,TOKEN_TYPES.CloseSquareBracket,TOKEN_TYPES.Comma,TOKEN_TYPES.Dot,TOKEN_TYPES.Colon,TOKEN_TYPES.Pipe,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.ComparisonBinaryOperator,TOKEN_TYPES.AdditiveBinaryOperator,TOKEN_TYPES.AdditiveBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.MultiplicativeBinaryOperator,TOKEN_TYPES.Equals;const BYTES_TO_UNICODE=(()=>{const v=[...Array.from({length:94},(p,b)=>b+33),...Array.from({length:12},(p,b)=>b+161),...Array.from({length:82},(p,b)=>b+174)],o=v.slice();let d=0;for(let p=0;p<256;++p)v.includes(p)||(v.push(p),o.push(256+d),d+=1);const l=o.map(p=>String.fromCharCode(p));return Object.fromEntries(v.map((p,b)=>[p,l[b]]))})();reverseDictionary(BYTES_TO_UNICODE);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"]];new Map(WHISPER_LANGUAGES);new Map([...WHISPER_LANGUAGES.map(([v,o])=>[o,v]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);async function loadConfig(v,o){return await getModelJSON(v,"config.json",!0,o)}class PretrainedConfig{constructor(o){this.model_type=null,this.is_encoder_decoder=!1,Object.assign(this,o)}static async from_pretrained(o,{progress_callback:d=null,config:l=null,cache_dir:p=null,local_files_only:b=!1,revision:c="main"}={}){let m=l??await loadConfig(o,{progress_callback:d,cache_dir:p,local_files_only:b,revision:c});return new this(m)}}class AutoConfig{static async from_pretrained(...o){return PretrainedConfig.from_pretrained(...o)}}class LogitsProcessorList extends Callable{constructor(){super(),this.processors=[]}push(o){this.processors.push(o)}extend(o){this.processors.push(...o)}_call(o,d){for(let l of d)this.processors.forEach(p=>p(o,l))}[Symbol.iterator](){return this.processors.values()}}class LogitsProcessor extends Callable{_call(o,d){throw Error("`_call` should be implemented in a subclass")}}class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(o){super(),this.force_token_map=Object.fromEntries(o??[])}_call(o,d){let l=this.force_token_map[o.length];return exists(l)&&(d.data.fill(-1/0),d.data[l]=0),d}}class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(o){super(),this.bos_token_id=o}_call(o,d){return o.length===1&&(d.data.fill(-1/0),d.data[this.bos_token_id]=0),d}}class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(o,d){super(),this.max_length=o,this.forced_eos_token_id=d}_call(o,d){}}class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(o,d){super(),this.begin_suppress_tokens=o,this.begin_index=d}_call(o,d){if(o.length===this.begin_index)for(let l of this.begin_suppress_tokens)d.data[l]=-1/0;return d}}class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(o){super(),this.eos_token_id=o.eos_token_id,this.no_timestamps_token_id=o.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(o.forced_decoder_ids||[]).length+2,o.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=o.max_initial_timestamp_index}_call(o,d){const l=d.data;if(l[this.no_timestamps_token_id]=-1/0,o.length===this.begin_index-1)return l.fill(-1/0),l[this.timestamp_begin]=0,d;const p=o.slice(this.begin_index),b=p.length>=1&&p[p.length-1]>=this.timestamp_begin,c=p.length<2||p[p.length-2]>=this.timestamp_begin;if(b&&(c?l.subarray(this.timestamp_begin).fill(-1/0):l.subarray(0,this.eos_token_id).fill(-1/0)),o.length===this.begin_index&&this.max_initial_timestamp_index!==null){const u=this.timestamp_begin+this.max_initial_timestamp_index;l.subarray(u+1).fill(-1/0)}const m=log_softmax(l),_=Math.log(m.subarray(this.timestamp_begin).map(Math.exp).reduce((u,n)=>u+n)),f=max(m.subarray(0,this.timestamp_begin))[0];return _>f&&l.subarray(0,this.timestamp_begin).fill(-1/0),d}}class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(o){super(),this.no_repeat_ngram_size=o}getNgrams(o){const d=o.length,l=[];for(let b=0;b<d+1-this.no_repeat_ngram_size;++b){const c=[];for(let m=0;m<this.no_repeat_ngram_size;++m)c.push(o[b+m]);l.push(c)}const p=new Map;for(const b of l){const c=b.slice(0,b.length-1),m=JSON.stringify(c),_=p.get(m)??[];_.push(b[b.length-1]),p.set(m,_)}return p}getGeneratedNgrams(o,d){const l=d.slice(d.length+1-this.no_repeat_ngram_size,d.length);return o.get(JSON.stringify(l))??[]}calcBannedNgramTokens(o){const d=[];if(o.length+1<this.no_repeat_ngram_size)return d;{const l=this.getNgrams(o);return this.getGeneratedNgrams(l,o)}}_call(o,d){const l=this.calcBannedNgramTokens(o);for(const p of l)d.data[p]=-1/0;return d}}class RepetitionPenaltyLogitsProcessor extends LogitsProcessor{constructor(o){super(),this.penalty=o}_call(o,d){for(const l of o)d.data[l]<0?d.data[l]*=this.penalty:d.data[l]/=this.penalty;return d}}class MinLengthLogitsProcessor extends LogitsProcessor{constructor(o,d){super(),this.min_length=o,this.eos_token_id=Array.isArray(d)?d:[d]}_call(o,d){if(o.length<this.min_length)for(const l of this.eos_token_id)d.data[l]=-1/0;return d}}class MinNewTokensLengthLogitsProcessor extends LogitsProcessor{constructor(o,d,l){super(),this.prompt_length_to_skip=o,this.min_new_tokens=d,this.eos_token_id=Array.isArray(l)?l:[l]}_call(o,d){if(o.length-this.prompt_length_to_skip<this.min_new_tokens)for(const l of this.eos_token_id)d.data[l]=-1/0;return d}}class NoBadWordsLogitsProcessor extends LogitsProcessor{constructor(o,d){super(),this.bad_words_ids=o,this.eos_token_id=Array.isArray(d)?d:[d]}_call(o,d){for(const l of this.bad_words_ids){let p=!0;for(let b=1;b<=l.length-1&&l.length<o.length;++b)if(l.at(-b-1)!==o.at(-b)){p=!1;break}p&&(d.data[l.at(-1)]=-1/0)}return d}}const GenerationConfig=class{constructor(v={}){this.max_length=v.max_length??20,this.max_new_tokens=v.max_new_tokens??null,this.min_length=v.min_length??0,this.min_new_tokens=v.min_new_tokens??null,this.early_stopping=v.early_stopping??!1,this.max_time=v.max_time??null,this.do_sample=v.do_sample??!1,this.num_beams=v.num_beams??1,this.num_beam_groups=v.num_beam_groups??1,this.penalty_alpha=v.penalty_alpha??null,this.use_cache=v.use_cache??!0,this.temperature=v.temperature??1,this.top_k=v.top_k??50,this.top_p=v.top_p??1,this.typical_p=v.typical_p??1,this.epsilon_cutoff=v.epsilon_cutoff??0,this.eta_cutoff=v.eta_cutoff??0,this.diversity_penalty=v.diversity_penalty??0,this.repetition_penalty=v.repetition_penalty??1,this.encoder_repetition_penalty=v.encoder_repetition_penalty??1,this.length_penalty=v.length_penalty??1,this.no_repeat_ngram_size=v.no_repeat_ngram_size??0,this.bad_words_ids=v.bad_words_ids??null,this.force_words_ids=v.force_words_ids??null,this.renormalize_logits=v.renormalize_logits??!1,this.constraints=v.constraints??null,this.forced_bos_token_id=v.forced_bos_token_id??null,this.forced_eos_token_id=v.forced_eos_token_id??null,this.remove_invalid_values=v.remove_invalid_values??!1,this.exponential_decay_length_penalty=v.exponential_decay_length_penalty??null,this.suppress_tokens=v.suppress_tokens??null,this.begin_suppress_tokens=v.begin_suppress_tokens??null,this.forced_decoder_ids=v.forced_decoder_ids??null,this.num_return_sequences=v.num_return_sequences??1,this.output_attentions=v.output_attentions??!1,this.output_hidden_states=v.output_hidden_states??!1,this.output_scores=v.output_scores??!1,this.return_dict_in_generate=v.return_dict_in_generate??!1,this.pad_token_id=v.pad_token_id??null,this.bos_token_id=v.bos_token_id??null,this.eos_token_id=v.eos_token_id??null,this.encoder_no_repeat_ngram_size=v.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=v.decoder_start_token_id??null,this.generation_kwargs=v.generation_kwargs??{}}};class Sampler extends Callable{constructor(o){super(),this.generation_config=o}_call(o,d=-1){return this.sample(o,d)}sample(o,d){throw Error("sample should be implemented in subclasses.")}getLogits(o,d){let l=o.dims.at(-1),p=o.data;if(d===-1)p=p.slice(-l);else{let b=d*l;p=p.slice(b,b+l)}return this.generation_config.temperature>0&&(p=p.map(b=>b/this.generation_config.temperature)),p}randomSelect(o){let d=o.reduce((p,b)=>p+b,0),l=Math.random()*d;for(let p=0;p<o.length;++p)if(l-=o[p],l<=0)return p;return 0}static getSampler(o){if(o.do_sample)return new MultinomialSampler(o);if(o.num_beams>1)return new BeamSearchSampler(o);if(o.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${o.num_return_sequences}.`);return new GreedySampler(o)}}class GreedySampler extends Sampler{sample(o,d=-1){let l=this.getLogits(o,d);return[[max(l)[1],0]]}}class MultinomialSampler extends Sampler{sample(o,d=-1){let l=o.dims.at(-1);this.generation_config.top_k>0&&(l=Math.min(this.generation_config.top_k,l));const p=this.getLogits(o,d),b=getTopItems(p,l),c=softmax(b.map(m=>m[1]));return Array.from({length:this.generation_config.num_beams},()=>{const m=this.randomSelect(c);return[b[m][0],Math.log(c[m])]})}}class BeamSearchSampler extends Sampler{sample(o,d=-1){let l=o.dims.at(-1);this.generation_config.top_k>0&&(l=Math.min(this.generation_config.top_k,l));const p=this.getLogits(o,d),b=getTopItems(p,l),c=softmax(b.map(m=>m[1]));return Array.from({length:this.generation_config.num_beams},(m,_)=>[b[_][0],Math.log(c[_])])}}const{InferenceSession,Tensor:ONNXTensor,env}=ONNX,MODEL_TYPES={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,MaskGeneration:5},MODEL_TYPE_MAPPING=new Map,MODEL_NAME_TO_CLASS_MAPPING=new Map,MODEL_CLASS_TO_NAME_MAPPING=new Map;async function constructSession(v,o,d){let l=`onnx/${o}${d.quantized?"_quantized":""}.onnx`,p=await getModelFile(v,l,!0,d);try{return await InferenceSession.create(p,{executionProviders})}catch(b){if(executionProviders.length===1&&executionProviders[0]==="wasm")throw b;return console.warn(b),console.warn("Something went wrong during model construction (most likely a missing operation). Using `wasm` as a fallback. "),await InferenceSession.create(p,{executionProviders:["wasm"]})}}function validateInputs(v,o){const d=Object.create(null),l=[];for(const c of v.inputNames){const m=o[c];if(!(m instanceof Tensor)){l.push(c);continue}d[c]=env.wasm.proxy?m.clone():m}if(l.length>0)throw new Error(`An error occurred during model execution: "Missing the following inputs: ${l.join(", ")}.`);const p=Object.keys(o).length,b=v.inputNames.length;if(p>b){let c=Object.keys(o).filter(m=>!v.inputNames.includes(m));console.warn(`WARNING: Too many inputs were provided (${p} > ${b}). The following inputs will be ignored: "${c.join(", ")}".`)}return d}async function sessionRun(v,o){const d=validateInputs(v,o);try{let l=await v.run(d);return l=replaceTensors(l),l}catch(l){throw console.error(`An error occurred during model execution: "${l}".`),console.error("Inputs given to model:",d),l}}function replaceTensors(v){for(let o in v)v[o]instanceof ONNXTensor?v[o]=new Tensor(v[o]):typeof v[o]=="object"&&replaceTensors(v[o]);return v}function toI64Tensor(v){if(v instanceof Tensor)return v;if(v.length===0)throw Error("items must be non-empty");if(Array.isArray(v[0])){if(v.some(o=>o.length!==v[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(v.flat().map(o=>BigInt(o))),[v.length,v[0].length])}else return new Tensor("int64",BigInt64Array.from(v.map(o=>BigInt(o))),[1,v.length])}function prepareAttentionMask(v,o){let d=v.config.pad_token_id??null,l=v.config.eos_token_id??null;isIntegralNumber(l)&&(l=[l]);let p=o.indexOf(d)!==-1,b=l===null||!l.includes(d);if(p&&b){let c=BigInt64Array.from(o.data.map(m=>m!=d));return new Tensor("int64",c,o.dims)}else return ones_like(o)}function preparePositionIds(v,o,d){if(!v.inputNames.includes("position_ids"))return;const l=new BigInt64Array(o.attention_mask.data.length);for(let p=0;p<o.attention_mask.dims[0];++p){let b=p*o.attention_mask.dims[1],c=BigInt(0);for(let m=0;m<o.attention_mask.dims[1];++m){const _=b+m;o.attention_mask.data[_]===0n?l[_]=BigInt(1):(l[_]=c,c+=o.attention_mask.data[_])}}o.position_ids=new Tensor("int64",l,o.attention_mask.dims),d&&(o.position_ids=o.position_ids.slice(null,-1).unsqueeze_(-1))}function boolTensor(v){return new Tensor("bool",[v],[1])}async function seq2seqForward(v,o){let{encoder_outputs:d,past_key_values:l}=o;d||(d=(await encoderForward(v,o)).last_hidden_state);let p={input_ids:o.decoder_input_ids,encoder_hidden_states:d};const b=!!l;v.decoder_merged_session.inputNames.includes("use_cache_branch")&&(p.use_cache_branch=boolTensor(b)),v.decoder_merged_session.inputNames.includes("encoder_attention_mask")&&(p.encoder_attention_mask=o.attention_mask),preparePositionIds(v.decoder_merged_session,p,b),v.addPastKeyValues(p,l);const c=await sessionRun(v.decoder_merged_session,p);let m=c.logits;l=v.getPastKeyValues(c,l);const _=v.getAttentions(c);return new Seq2SeqLMOutput({logits:m,past_key_values:l,encoder_outputs:d,..._})}function seq2seqStartBeams(v,o,d,l){let p=[],b=0;const c=v.requires_attention_mask??!0;let m=d.decoder_input_ids??d.decoder_start_token_id??d.bos_token_id??d.eos_token_id;m instanceof Tensor?m=m.tolist().flat():Array.isArray(m)||(m=[m]);for(let _ of o){_.dims=[1,..._.dims];let f={inputs:_,encoder_outputs:null,prev_model_outputs:null,output_token_ids:m,done:!1,score:0,id:b++};c&&(f.attention_mask=prepareAttentionMask(v,_)),p.push(f)}return p}async function seq2seqRunBeam(v,o){var d;const l=v.main_input_name;let p=o.output_token_ids;o.prev_model_outputs&&(p=p.slice(-1));let b={[l]:o.inputs,decoder_input_ids:toI64Tensor(p),encoder_outputs:o.encoder_outputs,past_key_values:(d=o.prev_model_outputs)==null?void 0:d.past_key_values};o.attention_mask&&(b.attention_mask=o.attention_mask);let c=await v.forward(b);return o.prev_model_outputs=c,o.encoder_outputs=c.encoder_outputs,c}function seq2seqUpdatebeam(v,o){v.output_token_ids=[...v.output_token_ids,o]}async function encoderForward(v,o){const d=Object.create(null);for(const l of v.session.inputNames)d[l]=o[l];return v.session.inputNames.includes("token_type_ids")&&!d.token_type_ids&&(d.token_type_ids=new Tensor("int64",new BigInt64Array(d.input_ids.data.length),d.input_ids.dims)),await sessionRun(v.session,d)}async function decoderForward(v,o){let{input_ids:d,past_key_values:l,attention_mask:p}=o,b={input_ids:d,attention_mask:p??prepareAttentionMask(v,d)};const c=!!l;v.session.inputNames.includes("use_cache_branch")&&(b.use_cache_branch=boolTensor(c)),preparePositionIds(v.session,b,c),v.addPastKeyValues(b,l);let m=await sessionRun(v.session,b),_=m.logits;return l=v.getPastKeyValues(m,l),{logits:_,past_key_values:l}}function decoderStartBeams(v,o,d,l,p){let b=[],c=0;for(let m of o){let _=m.tolist().map(Number);m.dims=[1,...m.dims];let f;p?(f=p[c],f.dims=[1,...f.dims]):f=prepareAttentionMask(v,m);let u={input:m,model_input_ids:m,attention_mask:f,prev_model_outputs:null,output_token_ids:_,num_output_tokens:l,done:!1,score:0,id:c++};b.push(u)}return b}async function decoderRunBeam(v,o){var d;let l=new BigInt64Array(o.output_token_ids.length).fill(1n),p={input_ids:o.model_input_ids,attention_mask:new Tensor("int64",l,[1,l.length]),past_key_values:(d=o.prev_model_outputs)==null?void 0:d.past_key_values},b=await v.forward(p);return o.prev_model_outputs=b,b}function decoderUpdatebeam(v,o){v.output_token_ids=[...v.output_token_ids,o],v.model_input_ids=new Tensor("int64",[BigInt(o)],[1,1])}class PreTrainedModel extends Callable{constructor(o,d){super(),Ht(this,"main_input_name","input_ids"),this.config=o,this.session=d;const l=MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor),p=MODEL_TYPE_MAPPING.get(l);this.can_generate=!1,this._runBeam=null,this._getStartBeams=null,this._updateBeam=null,this._forward=null,p===MODEL_TYPES.DecoderOnly?(this.can_generate=!0,this._runBeam=decoderRunBeam,this._getStartBeams=decoderStartBeams,this._updateBeam=decoderUpdatebeam,this._forward=decoderForward):p===MODEL_TYPES.Seq2Seq||p===MODEL_TYPES.Vision2Seq?(this.can_generate=!0,this._runBeam=seq2seqRunBeam,this._getStartBeams=seq2seqStartBeams,this._updateBeam=seq2seqUpdatebeam,this._forward=seq2seqForward):p===MODEL_TYPES.EncoderDecoder?this._forward=encoderForward:this._forward=encoderForward}async dispose(){const o=[];for(let d of Object.keys(this)){const l=this[d];l instanceof InferenceSession&&o.push(l.handler.dispose())}return await Promise.all(o)}static async from_pretrained(o,{quantized:d=!0,progress_callback:l=null,config:p=null,cache_dir:b=null,local_files_only:c=!1,revision:m="main",model_file_name:_=null}={}){let f={quantized:d,progress_callback:l,config:p,cache_dir:b,local_files_only:c,revision:m,model_file_name:_};const u=MODEL_CLASS_TO_NAME_MAPPING.get(this),n=MODEL_TYPE_MAPPING.get(u);let e;return n===MODEL_TYPES.DecoderOnly?e=await Promise.all([AutoConfig.from_pretrained(o,f),constructSession(o,f.model_file_name??"decoder_model_merged",f),getModelJSON(o,"generation_config.json",!1,f)]):n===MODEL_TYPES.Seq2Seq||n===MODEL_TYPES.Vision2Seq?e=await Promise.all([AutoConfig.from_pretrained(o,f),constructSession(o,"encoder_model",f),constructSession(o,"decoder_model_merged",f),getModelJSON(o,"generation_config.json",!1,f)]):n===MODEL_TYPES.MaskGeneration?e=await Promise.all([AutoConfig.from_pretrained(o,f),constructSession(o,"vision_encoder",f),constructSession(o,"prompt_encoder_mask_decoder",f)]):n===MODEL_TYPES.EncoderDecoder?e=await Promise.all([AutoConfig.from_pretrained(o,f),constructSession(o,"encoder_model",f),constructSession(o,"decoder_model_merged",f)]):(n!==MODEL_TYPES.EncoderOnly&&console.warn(`Model type for '${u??(p==null?void 0:p.model_type)}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`),e=await Promise.all([AutoConfig.from_pretrained(o,f),constructSession(o,f.model_file_name??"model",f)])),new this(...e)}async _call(o){return await this.forward(o)}async forward(o){return await this._forward(this,o)}_get_logits_processor(o,d,l=null){const p=new LogitsProcessorList;if(o.repetition_penalty!==null&&o.repetition_penalty!==1&&p.push(new RepetitionPenaltyLogitsProcessor(o.repetition_penalty)),o.no_repeat_ngram_size!==null&&o.no_repeat_ngram_size>0&&p.push(new NoRepeatNGramLogitsProcessor(o.no_repeat_ngram_size)),o.bad_words_ids!==null&&p.push(new NoBadWordsLogitsProcessor(o.bad_words_ids,o.eos_token_id)),o.min_length!==null&&o.eos_token_id!==null&&o.min_length>0&&p.push(new MinLengthLogitsProcessor(o.min_length,o.eos_token_id)),o.min_new_tokens!==null&&o.eos_token_id!==null&&o.min_new_tokens>0&&p.push(new MinNewTokensLengthLogitsProcessor(d,o.min_new_tokens,o.eos_token_id)),o.forced_bos_token_id!==null&&p.push(new ForcedBOSTokenLogitsProcessor(o.forced_bos_token_id)),o.forced_eos_token_id!==null&&p.push(new ForcedEOSTokenLogitsProcessor(o.max_length,o.forced_eos_token_id)),o.begin_suppress_tokens!==null){let b=d>1||o.forced_bos_token_id===null?d:d+1;o.forced_decoder_ids!==null&&(b+=o.forced_decoder_ids[o.forced_decoder_ids.length-1][0]),p.push(new SuppressTokensAtBeginLogitsProcessor(o.begin_suppress_tokens,b))}return o.forced_decoder_ids!==null&&p.push(new ForceTokensLogitsProcessor(o.forced_decoder_ids)),l!==null&&p.extend(l),p}_get_generation_config(o){let d=new GenerationConfig(this.config);return"generation_config"in this&&Object.assign(d,this.generation_config),o!==null&&Object.assign(d,o),d}async generate(o,d=null,l=null,{inputs_attention_mask:p=null}={}){if(!this.can_generate){let g=`The current model class (${MODEL_CLASS_TO_NAME_MAPPING.get(this.constructor)}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;const y=this.config.model_type,x=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(y)??MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES.get(y)??MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES.get(y)??MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES.get(y);throw x&&(g+=` Please use the following class instead: '${x[0]}'`),Error(g)}if(!(o instanceof Tensor)&&!isTypedArray(o)&&!Array.isArray(o))throw Error(`\`inputs\` must be a Tensor, TypedArray, or Array, but is "${o.constructor.name}".`);let b;if(this.config.is_encoder_decoder)b=0;else if(b=o instanceof Tensor?o.dims.at(-1):o.length,b===0)throw Error("Must supply a non-empty array of input token ids.");d=this._get_generation_config(d),l=l??new LogitsProcessorList,l=this._get_logits_processor(d,b,l);let c=d.eos_token_id;c!==null&&!Array.isArray(c)&&(c=[c]);let m=1;const _=m+(d.max_new_tokens??1/0),f=Number.isInteger(d.max_length)&&(d.max_new_tokens??null)===null;let u=Sampler.getSampler(d),n=this.getStartBeams(o,d,m,p);for(;n.some(g=>!g.done)&&m<_;){let g=[];for(let y of n){if(y.done){g.push(y);continue}if(f&&y.output_token_ids.length>=d.max_length){y.done=!0,g.push(y);continue}let x=await this.runBeam(y);d.output_attentions&&this.addAttentionsToBeam(y,x),d.output_scores;let E=x.logits.slice(null,-1,null);l(y.output_token_ids,E);let S=u(E);for(let[P,O]of S){let k={...y};this.updateBeam(k,P),k.score+=O,c&&c.includes(P)&&(k.done=!0),g.push(k)}}++m,g=this.groupBeams(g).map(y=>y.sort((x,E)=>E.score-x.score).slice(0,d.num_beams)),n=g.flat(),d.callback_function&&d.callback_function(n)}const e=this.groupBeams(n),a=g=>e.map(y=>d.num_return_sequences>1?y.slice(0,d.num_return_sequences).map(x=>x[g]):[y[0][g]]).flat(),s=a("output_token_ids");if(d.return_dict_in_generate){const g=a("decoder_attentions"),y=a("cross_attentions");return{sequences:s,decoder_attentions:g,cross_attentions:y}}else return s}addAttentionsToBeam(o,d){if(this.config.is_encoder_decoder){if(!d.cross_attentions||d.cross_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce cross-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.cross_attentions||(o.cross_attentions=[]),o.cross_attentions.push(d.cross_attentions)}if(!d.decoder_attentions||d.decoder_attentions.length===0)throw Error("`output_attentions` is true, but the model did not produce decoder-attentions. This is most likely because the model was not exported with `output_attentions=True`.");o.decoder_attentions||(o.decoder_attentions=[]),o.decoder_attentions.push(d.decoder_attentions)}groupBeams(o){const d=Object.create(null);for(const l of o)d[l.id]===void 0?d[l.id]=[l]:d[l.id].push(l);return Object.values(d)}getPastKeyValues(o,d){const l=Object.create(null);for(const p in o)if(p.startsWith("present")){let b=p.replace("present","past_key_values");d&&p.includes("encoder")?l[b]=d[b]:l[b]=o[p]}return l}getAttentions(o){const d=Object.create(null);for(const l of["cross_attentions","decoder_attentions"]){const p=[];for(const b in o)if(b.startsWith(l)){const c=b.split(".").pop();p[c]=o[b]}d[l]=p}return d}addPastKeyValues(o,d){if(d)Object.assign(o,d);else if(this.config.is_encoder_decoder&&(this.add_encoder_pkv??!0)){let l=[1,this.num_encoder_heads,0,this.encoder_dim_kv],p=[1,this.num_decoder_heads,0,this.decoder_dim_kv];for(let b=0;b<this.num_decoder_layers;++b)o[`past_key_values.${b}.encoder.key`]=new Tensor("float32",[],l),o[`past_key_values.${b}.encoder.value`]=new Tensor("float32",[],l),o[`past_key_values.${b}.decoder.key`]=new Tensor("float32",[],p),o[`past_key_values.${b}.decoder.value`]=new Tensor("float32",[],p)}else if(this.config.model_type==="falcon"){let l=[1*this.num_heads,0,this.dim_kv];for(let p=0;p<this.num_layers;++p)o[`past_key_values.${p}.key`]=new Tensor("float32",[],l),o[`past_key_values.${p}.value`]=new Tensor("float32",[],l)}else if(this.config.multi_query){let l=[1*this.num_heads,0,2*this.dim_kv];for(let p=0;p<this.num_layers;++p)o[`past_key_values.${p}.key_value`]=new Tensor("float32",[],l)}else if(this.config.model_type==="bloom"){let l=[1*this.num_heads,this.dim_kv,0],p=[1*this.num_heads,0,this.dim_kv];for(let b=0;b<this.num_layers;++b)o[`past_key_values.${b}.key`]=new Tensor("float32",[],l),o[`past_key_values.${b}.value`]=new Tensor("float32",[],p)}else{let l=[1,this.num_heads,0,this.dim_kv];for(let p=0;p<this.num_layers;++p)o[`past_key_values.${p}.key`]=new Tensor("float32",[],l),o[`past_key_values.${p}.value`]=new Tensor("float32",[],l)}}getStartBeams(o,d,l,p){return this._getStartBeams(this,o,d,l,p)}async runBeam(o){return await this._runBeam(this,o)}updateBeam(o,d){return this._updateBeam(o,d)}}class ModelOutput{}class BertPreTrainedModel extends PreTrainedModel{}class BertModel extends BertPreTrainedModel{}class BertForMaskedLM extends BertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class BertForSequenceClassification extends BertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class BertForTokenClassification extends BertPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class BertForQuestionAnswering extends BertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class NomicBertPreTrainedModel extends PreTrainedModel{}class NomicBertModel extends NomicBertPreTrainedModel{}class RoFormerPreTrainedModel extends PreTrainedModel{}class RoFormerModel extends RoFormerPreTrainedModel{}class RoFormerForMaskedLM extends RoFormerPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class RoFormerForSequenceClassification extends RoFormerPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class RoFormerForTokenClassification extends RoFormerPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class RoFormerForQuestionAnswering extends RoFormerPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class ConvBertPreTrainedModel extends PreTrainedModel{}class ConvBertModel extends ConvBertPreTrainedModel{}class ConvBertForMaskedLM extends ConvBertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class ConvBertForSequenceClassification extends ConvBertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class ConvBertForTokenClassification extends ConvBertPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class ConvBertForQuestionAnswering extends ConvBertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class ElectraPreTrainedModel extends PreTrainedModel{}class ElectraModel extends ElectraPreTrainedModel{}class ElectraForMaskedLM extends ElectraPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class ElectraForSequenceClassification extends ElectraPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class ElectraForTokenClassification extends ElectraPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class ElectraForQuestionAnswering extends ElectraPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class CamembertPreTrainedModel extends PreTrainedModel{}class CamembertModel extends CamembertPreTrainedModel{}class CamembertForMaskedLM extends CamembertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class CamembertForSequenceClassification extends CamembertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class CamembertForTokenClassification extends CamembertPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class CamembertForQuestionAnswering extends CamembertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class DebertaPreTrainedModel extends PreTrainedModel{}class DebertaModel extends DebertaPreTrainedModel{}class DebertaForMaskedLM extends DebertaPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class DebertaForSequenceClassification extends DebertaPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class DebertaForTokenClassification extends DebertaPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class DebertaForQuestionAnswering extends DebertaPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class DebertaV2PreTrainedModel extends PreTrainedModel{}class DebertaV2Model extends DebertaV2PreTrainedModel{}class DebertaV2ForMaskedLM extends DebertaV2PreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class DebertaV2ForSequenceClassification extends DebertaV2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class DebertaV2ForTokenClassification extends DebertaV2PreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class DebertaV2ForQuestionAnswering extends DebertaV2PreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class DistilBertPreTrainedModel extends PreTrainedModel{}class DistilBertModel extends DistilBertPreTrainedModel{}class DistilBertForSequenceClassification extends DistilBertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class DistilBertForTokenClassification extends DistilBertPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class DistilBertForQuestionAnswering extends DistilBertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class DistilBertForMaskedLM extends DistilBertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class EsmPreTrainedModel extends PreTrainedModel{}class EsmModel extends EsmPreTrainedModel{}class EsmForMaskedLM extends EsmPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class EsmForSequenceClassification extends EsmPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class EsmForTokenClassification extends EsmPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class MobileBertPreTrainedModel extends PreTrainedModel{}class MobileBertModel extends MobileBertPreTrainedModel{}class MobileBertForMaskedLM extends MobileBertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class MobileBertForSequenceClassification extends MobileBertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class MobileBertForQuestionAnswering extends MobileBertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class MPNetPreTrainedModel extends PreTrainedModel{}class MPNetModel extends MPNetPreTrainedModel{}class MPNetForMaskedLM extends MPNetPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class MPNetForSequenceClassification extends MPNetPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class MPNetForTokenClassification extends MPNetPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class MPNetForQuestionAnswering extends MPNetPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class SqueezeBertPreTrainedModel extends PreTrainedModel{}class SqueezeBertModel extends SqueezeBertPreTrainedModel{}class SqueezeBertForMaskedLM extends SqueezeBertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class SqueezeBertForSequenceClassification extends SqueezeBertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class SqueezeBertForQuestionAnswering extends SqueezeBertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class AlbertPreTrainedModel extends PreTrainedModel{}class AlbertModel extends AlbertPreTrainedModel{}class AlbertForSequenceClassification extends AlbertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class AlbertForQuestionAnswering extends AlbertPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class AlbertForMaskedLM extends AlbertPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class T5PreTrainedModel extends PreTrainedModel{}class T5Model extends T5PreTrainedModel{}class T5ForConditionalGeneration extends T5PreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,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(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,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(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,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(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BartForSequenceClassification extends BartPretrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class MBartPreTrainedModel extends PreTrainedModel{}class MBartModel extends MBartPreTrainedModel{}class MBartForConditionalGeneration extends MBartPreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class MBartForSequenceClassification extends MBartPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class MBartForCausalLM extends MBartPreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BlenderbotPreTrainedModel extends PreTrainedModel{}class BlenderbotModel extends BlenderbotPreTrainedModel{}class BlenderbotForConditionalGeneration extends BlenderbotPreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class BlenderbotSmallPreTrainedModel extends PreTrainedModel{}class BlenderbotSmallModel extends BlenderbotSmallPreTrainedModel{}class BlenderbotSmallForConditionalGeneration extends BlenderbotSmallPreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class RobertaPreTrainedModel extends PreTrainedModel{}class RobertaModel extends RobertaPreTrainedModel{}class RobertaForMaskedLM extends RobertaPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class RobertaForSequenceClassification extends RobertaPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class RobertaForTokenClassification extends RobertaPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class RobertaForQuestionAnswering extends RobertaPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class XLMPreTrainedModel extends PreTrainedModel{}class XLMModel extends XLMPreTrainedModel{}class XLMWithLMHeadModel extends XLMPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class XLMForSequenceClassification extends XLMPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class XLMForTokenClassification extends XLMPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class XLMForQuestionAnswering extends XLMPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class XLMRobertaPreTrainedModel extends PreTrainedModel{}class XLMRobertaModel extends XLMRobertaPreTrainedModel{}class XLMRobertaForMaskedLM extends XLMRobertaPreTrainedModel{async _call(o){return new MaskedLMOutput(await super._call(o))}}class XLMRobertaForSequenceClassification extends XLMRobertaPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class XLMRobertaForTokenClassification extends XLMRobertaPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class XLMRobertaForQuestionAnswering extends XLMRobertaPreTrainedModel{async _call(o){return new QuestionAnsweringModelOutput(await super._call(o))}}class ASTPreTrainedModel extends PreTrainedModel{}class ASTModel extends ASTPreTrainedModel{}class ASTForAudioClassification extends ASTPreTrainedModel{}class WhisperPreTrainedModel extends PreTrainedModel{}class WhisperModel extends WhisperPreTrainedModel{}class WhisperForConditionalGeneration extends WhisperPreTrainedModel{constructor(o,d,l,p){super(o,d),Ht(this,"requires_attention_mask",!1),Ht(this,"main_input_name","input_features"),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}async generate(o,d=null,l=null){if(d=this._get_generation_config(d),d.return_timestamps??(d.return_timestamps=!1),d.return_timestamps&&(l=[new WhisperTimeStampLogitsProcessor(d)]),d.return_token_timestamps&&(d.output_attentions=!0,d.return_dict_in_generate=!0,d.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),!d.alignment_heads))throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");const p=await super.generate(o,d,l);return d.return_token_timestamps&&d.alignment_heads&&(p.token_timestamps=this._extract_token_timestamps(p,d.alignment_heads,d.num_frames)),p}_extract_token_timestamps(o,d,l=null,p=.02){if(!o.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");let b=this.config.median_filter_width;b===void 0&&(console.warn("Model config has no `median_filter_width`, using default value of 7."),b=7);const c=o.cross_attentions.map(f=>{let u=Array.from({length:this.config.decoder_layers},(g,y)=>cat(f.map(x=>x[y]),2)),n=stack(d.map(([g,y])=>l?u[g].slice(null,y,null,[0,l]):u[g].slice(null,y)));n=n.transpose(1,0,2,3);let[e,a]=std_mean(n,-2,0,!0),s=n.clone();for(let g=0;g<s.dims[0];++g){let y=s[g];for(let x=0;x<y.dims[0];++x){let E=y[x];const S=e[g][x][0],P=a[g][x][0];for(let O=0;O<E.dims[0];++O){let k=E[O];for(let D=0;D<k.data.length;++D)k.data[D]=(k.data[D]-P.data[D])/S.data[D];k.data.set(medianFilter(k.data,b))}}}return mean(s,1)}),m=[o.sequences.length,o.sequences[0].length],_=new Tensor("float32",new Float32Array(m[0]*m[1]),m);for(let f=0;f<m[0];++f){const u=c[f].neg().squeeze_(0);let[n,e]=dynamicTimeWarping(u),a=Array.from({length:n.length-1},(y,x)=>n[x+1]-n[x]),s=mergeArrays([1],a).map(y=>!!y),g=[];for(let y=0;y<s.length;++y)s[y]&&g.push(e[y]*p);_[f].data.set(g,1)}return _}}class VisionEncoderDecoderModel extends PreTrainedModel{constructor(o,d,l,p){super(o,d),Ht(this,"main_input_name","pixel_values"),this.decoder_merged_session=l,this.generation_config=p;const b=this.config.encoder,c=this.config.decoder,m=b.model_type;(MODEL_MAPPING_NAMES_ENCODER_ONLY.get(m)??MODEL_MAPPING_NAMES_ENCODER_DECODER.get(m))||console.warn(`Model type for encoder '${m}' not found, assuming encoder-only architecture. Please report this at https://github.com/xenova/transformers.js/issues/new/choose.`);const _=MODEL_WITH_LM_HEAD_MAPPING_NAMES.get(c.model_type);if(!_)throw new Error(`Unable to construct \`VisionEncoderDecoder\` due to unsupported decoder: "${this.config.decoder.model_type}"`);const f=_[1],u=new f(c,l,p);this.add_encoder_pkv="num_decoder_layers"in u,this.add_encoder_pkv?(this.num_decoder_layers=u.num_decoder_layers,this.num_decoder_heads=u.num_decoder_heads,this.decoder_dim_kv=u.decoder_dim_kv,this.num_encoder_layers=u.num_encoder_layers,this.num_encoder_heads=u.num_encoder_heads,this.encoder_dim_kv=u.encoder_dim_kv):(this.num_layers=u.num_layers,this.num_heads=u.num_heads,this.dim_kv=u.dim_kv)}}class CLIPPreTrainedModel extends PreTrainedModel{}class CLIPModel extends CLIPPreTrainedModel{}class CLIPTextModelWithProjection extends CLIPPreTrainedModel{static async from_pretrained(o,d={}){return d.model_file_name??(d.model_file_name="text_model"),super.from_pretrained(o,d)}}class CLIPVisionModelWithProjection extends CLIPPreTrainedModel{static async from_pretrained(o,d={}){return d.model_file_name??(d.model_file_name="vision_model"),super.from_pretrained(o,d)}}class SiglipPreTrainedModel extends PreTrainedModel{}class SiglipModel extends SiglipPreTrainedModel{}class SiglipTextModel extends SiglipPreTrainedModel{static async from_pretrained(o,d={}){return d.model_file_name??(d.model_file_name="text_model"),super.from_pretrained(o,d)}}class SiglipVisionModel extends CLIPPreTrainedModel{static async from_pretrained(o,d={}){return d.model_file_name??(d.model_file_name="vision_model"),super.from_pretrained(o,d)}}class ChineseCLIPPreTrainedModel extends PreTrainedModel{}class ChineseCLIPModel extends ChineseCLIPPreTrainedModel{}class CLIPSegPreTrainedModel extends PreTrainedModel{}class CLIPSegModel extends CLIPSegPreTrainedModel{}class CLIPSegForImageSegmentation extends CLIPSegPreTrainedModel{}class GPT2PreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class LlamaModel extends LlamaPreTrainedModel{}class LlamaForCausalLM extends LlamaPreTrainedModel{}class Qwen2PreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_key_value_heads??this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.config.num_attention_heads}}class Qwen2Model extends Qwen2PreTrainedModel{}class Qwen2ForCausalLM extends Qwen2PreTrainedModel{}class PhiPreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,this.config.pad_token_id=this.config.eos_token_id,this.num_heads=this.config.num_attention_heads,this.num_layers=this.config.num_hidden_layers,this.dim_kv=this.config.hidden_size/this.num_heads}}class PhiModel extends PhiPreTrainedModel{}class PhiForCausalLM extends PhiPreTrainedModel{}class BloomPreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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(o){return new SequenceClassifierOutput(await super._call(o))}}class FastViTPreTrainedModel extends PreTrainedModel{}class FastViTModel extends FastViTPreTrainedModel{}class FastViTForImageClassification extends FastViTPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class VitMattePreTrainedModel extends PreTrainedModel{}class VitMatteForImageMatting extends VitMattePreTrainedModel{async _call(o){return new ImageMattingOutput(await super._call(o))}}class MobileViTPreTrainedModel extends PreTrainedModel{}class MobileViTModel extends MobileViTPreTrainedModel{}class MobileViTForImageClassification extends MobileViTPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class MobileViTV2PreTrainedModel extends PreTrainedModel{}class MobileViTV2Model extends MobileViTV2PreTrainedModel{}class MobileViTV2ForImageClassification extends MobileViTV2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class OwlViTPreTrainedModel extends PreTrainedModel{}class OwlViTModel extends OwlViTPreTrainedModel{}class OwlViTForObjectDetection extends OwlViTPreTrainedModel{}class Owlv2PreTrainedModel extends PreTrainedModel{}class Owlv2Model extends Owlv2PreTrainedModel{}class Owlv2ForObjectDetection extends Owlv2PreTrainedModel{}class BeitPreTrainedModel extends PreTrainedModel{}class BeitModel extends BeitPreTrainedModel{}class BeitForImageClassification extends BeitPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class DetrPreTrainedModel extends PreTrainedModel{}class DetrModel extends DetrPreTrainedModel{}class DetrForObjectDetection extends DetrPreTrainedModel{async _call(o){return new DetrObjectDetectionOutput(await super._call(o))}}class DetrForSegmentation extends DetrPreTrainedModel{async _call(o){return new DetrSegmentationOutput(await super._call(o))}}class DetrObjectDetectionOutput extends ModelOutput{constructor({logits:o,pred_boxes:d}){super(),this.logits=o,this.pred_boxes=d}}class DetrSegmentationOutput extends ModelOutput{constructor({logits:o,pred_boxes:d,pred_masks:l}){super(),this.logits=o,this.pred_boxes=d,this.pred_masks=l}}class TableTransformerPreTrainedModel extends PreTrainedModel{}class TableTransformerModel extends TableTransformerPreTrainedModel{}class TableTransformerForObjectDetection extends TableTransformerPreTrainedModel{async _call(o){return new TableTransformerObjectDetectionOutput(await super._call(o))}}class TableTransformerObjectDetectionOutput extends DetrObjectDetectionOutput{}class DeiTPreTrainedModel extends PreTrainedModel{}class DeiTModel extends DeiTPreTrainedModel{}class DeiTForImageClassification extends DeiTPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class ResNetPreTrainedModel extends PreTrainedModel{}class ResNetModel extends ResNetPreTrainedModel{}class ResNetForImageClassification extends ResNetPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class SwinPreTrainedModel extends PreTrainedModel{}class SwinModel extends SwinPreTrainedModel{}class SwinForImageClassification extends SwinPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class Swin2SRPreTrainedModel extends PreTrainedModel{}class Swin2SRModel extends Swin2SRPreTrainedModel{}class Swin2SRForImageSuperResolution extends Swin2SRPreTrainedModel{}class DPTPreTrainedModel extends PreTrainedModel{}class DPTModel extends DPTPreTrainedModel{}class DPTForDepthEstimation extends DPTPreTrainedModel{}class DepthAnythingPreTrainedModel extends PreTrainedModel{}class DepthAnythingForDepthEstimation extends DepthAnythingPreTrainedModel{}class GLPNPreTrainedModel extends PreTrainedModel{}class GLPNModel extends GLPNPreTrainedModel{}class GLPNForDepthEstimation extends GLPNPreTrainedModel{}class DonutSwinPreTrainedModel extends PreTrainedModel{}class DonutSwinModel extends DonutSwinPreTrainedModel{}class ConvNextPreTrainedModel extends PreTrainedModel{}class ConvNextModel extends ConvNextPreTrainedModel{}class ConvNextForImageClassification extends ConvNextPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class ConvNextV2PreTrainedModel extends PreTrainedModel{}class ConvNextV2Model extends ConvNextV2PreTrainedModel{}class ConvNextV2ForImageClassification extends ConvNextV2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class Dinov2PreTrainedModel extends PreTrainedModel{}class Dinov2Model extends Dinov2PreTrainedModel{}class Dinov2ForImageClassification extends Dinov2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class YolosPreTrainedModel extends PreTrainedModel{}class YolosModel extends YolosPreTrainedModel{}class YolosForObjectDetection extends YolosPreTrainedModel{async _call(o){return new YolosObjectDetectionOutput(await super._call(o))}}class YolosObjectDetectionOutput extends ModelOutput{constructor({logits:o,pred_boxes:d}){super(),this.logits=o,this.pred_boxes=d}}class SamPreTrainedModel extends PreTrainedModel{}class SamModel extends SamPreTrainedModel{constructor(o,d,l){super(o,d),this.prompt_encoder_mask_decoder=l}async get_image_embeddings({pixel_values:o}){return await encoderForward(this,{pixel_values:o})}async forward(o){if((!o.image_embeddings||!o.image_positional_embeddings)&&(o={...o,...await this.get_image_embeddings(o)}),!o.input_labels){const d=o.input_points.dims.slice(0,-1),l=d.reduce((p,b)=>p*b,1);o.input_labels=new Tensor("int64",new BigInt64Array(l).fill(1n),d)}return await sessionRun(this.prompt_encoder_mask_decoder,{input_points:o.input_points,input_labels:o.input_labels,image_embeddings:o.image_embeddings,image_positional_embeddings:o.image_positional_embeddings})}async _call(o){return new SamImageSegmentationOutput(await super._call(o))}}class SamImageSegmentationOutput extends ModelOutput{constructor({iou_scores:o,pred_masks:d}){super(),this.iou_scores=o,this.pred_masks=d}}class MarianPreTrainedModel extends PreTrainedModel{}class MarianModel extends MarianPreTrainedModel{}class MarianMTModel extends MarianPreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class M2M100PreTrainedModel extends PreTrainedModel{}class M2M100Model extends M2M100PreTrainedModel{}class M2M100ForConditionalGeneration extends M2M100PreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.d_model/this.num_decoder_heads,this.num_encoder_layers=this.config.encoder_layers,this.num_encoder_heads=this.config.encoder_attention_heads,this.encoder_dim_kv=this.config.d_model/this.num_encoder_heads}}class Wav2Vec2PreTrainedModel extends PreTrainedModel{}class Wav2Vec2Model extends Wav2Vec2PreTrainedModel{}class Wav2Vec2ForCTC extends Wav2Vec2PreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class Wav2Vec2ForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class Wav2Vec2ForAudioFrameClassification extends Wav2Vec2PreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class UniSpeechPreTrainedModel extends PreTrainedModel{}class UniSpeechModel extends UniSpeechPreTrainedModel{}class UniSpeechForCTC extends UniSpeechPreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class UniSpeechForSequenceClassification extends UniSpeechPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class UniSpeechSatPreTrainedModel extends PreTrainedModel{}class UniSpeechSatModel extends UniSpeechSatPreTrainedModel{}class UniSpeechSatForCTC extends UniSpeechSatPreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class UniSpeechSatForSequenceClassification extends UniSpeechSatPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class UniSpeechSatForAudioFrameClassification extends UniSpeechSatPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class Wav2Vec2BertPreTrainedModel extends PreTrainedModel{}class Wav2Vec2BertModel extends Wav2Vec2BertPreTrainedModel{}class Wav2Vec2BertForCTC extends Wav2Vec2BertPreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class Wav2Vec2BertForSequenceClassification extends Wav2Vec2BertPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class HubertModel extends Wav2Vec2PreTrainedModel{}class HubertForCTC extends Wav2Vec2PreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class HubertForSequenceClassification extends Wav2Vec2PreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class WavLMPreTrainedModel extends PreTrainedModel{}class WavLMModel extends WavLMPreTrainedModel{}class WavLMForCTC extends WavLMPreTrainedModel{async _call(o){return new CausalLMOutput(await super._call(o))}}class WavLMForSequenceClassification extends WavLMPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class WavLMForXVector extends WavLMPreTrainedModel{async _call(o){return new XVectorOutput(await super._call(o))}}class WavLMForAudioFrameClassification extends WavLMPreTrainedModel{async _call(o){return new TokenClassifierOutput(await super._call(o))}}class SpeechT5PreTrainedModel extends PreTrainedModel{}class SpeechT5ForSpeechToText extends SpeechT5PreTrainedModel{}class SpeechT5ForTextToSpeech extends SpeechT5PreTrainedModel{constructor(o,d,l,p){super(o,d),this.decoder_merged_session=l,this.generation_config=p,this.num_decoder_layers=this.config.decoder_layers,this.num_decoder_heads=this.config.decoder_attention_heads,this.decoder_dim_kv=this.config.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(o,d,{threshold:l=.5,minlenratio:p=0,maxlenratio:b=20,vocoder:c=null}={}){const m={input_ids:o},{encoder_outputs:_,encoder_attention_mask:f}=await encoderForward(this,m),u=_.dims[1]/this.config.reduction_factor,n=Math.floor(u*b),e=Math.floor(u*p),a=this.config.num_mel_bins;let s=[],g=null,y=null,x=0;for(;;){++x;const P=boolTensor(!!y);let O;y?O=y.output_sequence_out:O=new Tensor("float32",new Float32Array(a),[1,1,a]);let k={use_cache_branch:P,output_sequence:O,encoder_attention_mask:f,speaker_embeddings:d,encoder_hidden_states:_};this.addPastKeyValues(k,g),y=await sessionRun(this.decoder_merged_session,k),g=this.getPastKeyValues(y,g);const{prob:D,spectrum:C}=y;if(s.push(C),x>=e&&(Array.from(D.data).filter(A=>A>=l).length>0||x>=n))break}const E=cat(s),{waveform:S}=await sessionRun(c.session,{spectrogram:E});return{spectrogram:E,waveform:S}}}class SpeechT5HifiGan extends PreTrainedModel{constructor(){super(...arguments),Ht(this,"main_input_name","spectrogram")}}class TrOCRPreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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(o,d,l){super(o,d),this.generation_config=l,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 Starcoder2PreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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 Starcoder2Model extends Starcoder2PreTrainedModel{}class Starcoder2ForCausalLM extends Starcoder2PreTrainedModel{}class FalconPreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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(o,d={}){return d.model_file_name??(d.model_file_name="text_model"),super.from_pretrained(o,d)}}class ClapAudioModelWithProjection extends ClapPreTrainedModel{static async from_pretrained(o,d={}){return d.model_file_name??(d.model_file_name="audio_model"),super.from_pretrained(o,d)}}class VitsPreTrainedModel extends PreTrainedModel{}class VitsModel extends VitsPreTrainedModel{async _call(o){return new VitsModelOutput(await super._call(o))}}class SegformerPreTrainedModel extends PreTrainedModel{}class SegformerForImageClassification extends SegformerPreTrainedModel{}class SegformerForSemanticSegmentation extends SegformerPreTrainedModel{}class StableLmPreTrainedModel extends PreTrainedModel{constructor(o,d,l){super(o,d),this.generation_config=l,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 StableLmForCausalLM extends StableLmPreTrainedModel{}class EfficientNetPreTrainedModel extends PreTrainedModel{}class EfficientNetModel extends EfficientNetPreTrainedModel{}class EfficientNetForImageClassification extends EfficientNetPreTrainedModel{async _call(o){return new SequenceClassifierOutput(await super._call(o))}}class PretrainedMixin{static async from_pretrained(o,{quantized:d=!0,progress_callback:l=null,config:p=null,cache_dir:b=null,local_files_only:c=!1,revision:m="main",model_file_name:_=null}={}){let f={quantized:d,progress_callback:l,config:p,cache_dir:b,local_files_only:c,revision:m,model_file_name:_};if(p=await AutoConfig.from_pretrained(o,f),f.config||(f.config=p),!this.MODEL_CLASS_MAPPINGS)throw new Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);for(let u of this.MODEL_CLASS_MAPPINGS){const n=u.get(p.model_type);if(n)return await n[1].from_pretrained(o,f)}if(this.BASE_IF_FAIL)return console.warn(`Unknown model class "${p.model_type}", attempting to construct from base class.`),await PreTrainedModel.from_pretrained(o,f);throw Error(`Unsupported model type: ${p.model_type}`)}}Ht(PretrainedMixin,"MODEL_CLASS_MAPPINGS",null),Ht(PretrainedMixin,"BASE_IF_FAIL",!1);const MODEL_MAPPING_NAMES_ENCODER_ONLY=new Map([["bert",["BertModel",BertModel]],["nomic_bert",["NomicBertModel",NomicBertModel]],["roformer",["RoFormerModel",RoFormerModel]],["electra",["ElectraModel",ElectraModel]],["esm",["EsmModel",EsmModel]],["convbert",["ConvBertModel",ConvBertModel]],["camembert",["CamembertModel",CamembertModel]],["deberta",["DebertaModel",DebertaModel]],["deberta-v2",["DebertaV2Model",DebertaV2Model]],["mpnet",["MPNetModel",MPNetModel]],["albert",["AlbertModel",AlbertModel]],["distilbert",["DistilBertModel",DistilBertModel]],["roberta",["RobertaModel",RobertaModel]],["xlm",["XLMModel",XLMModel]],["xlm-roberta",["XLMRobertaModel",XLMRobertaModel]],["clap",["ClapModel",ClapModel]],["clip",["CLIPModel",CLIPModel]],["clipseg",["CLIPSegModel",CLIPSegModel]],["chinese_clip",["ChineseCLIPModel",ChineseCLIPModel]],["siglip",["SiglipModel",SiglipModel]],["mobilebert",["MobileBertModel",MobileBertModel]],["squeezebert",["SqueezeBertModel",SqueezeBertModel]],["wav2vec2",["Wav2Vec2Model",Wav2Vec2Model]],["wav2vec2-bert",["Wav2Vec2BertModel",Wav2Vec2BertModel]],["unispeech",["UniSpeechModel",UniSpeechModel]],["unispeech-sat",["UniSpeechSatModel",UniSpeechSatModel]],["hubert",["HubertModel",HubertModel]],["wavlm",["WavLMModel",WavLMModel]],["audio-spectrogram-transformer",["ASTModel",ASTModel]],["vits",["VitsModel",VitsModel]],["detr",["DetrModel",DetrModel]],["table-transformer",["TableTransformerModel",TableTransformerModel]],["vit",["ViTModel",ViTModel]],["fastvit",["FastViTModel",FastViTModel]],["mobilevit",["MobileViTModel",MobileViTModel]],["mobilevitv2",["MobileViTV2Model",MobileViTV2Model]],["owlvit",["OwlViTModel",OwlViTModel]],["owlv2",["Owlv2Model",Owlv2Model]],["beit",["BeitModel",BeitModel]],["deit",["DeiTModel",DeiTModel]],["convnext",["ConvNextModel",ConvNextModel]],["convnextv2",["ConvNextV2Model",ConvNextV2Model]],["dinov2",["Dinov2Model",Dinov2Model]],["resnet",["ResNetModel",ResNetModel]],["swin",["SwinModel",SwinModel]],["swin2sr",["Swin2SRModel",Swin2SRModel]],["donut-swin",["DonutSwinModel",DonutSwinModel]],["yolos",["YolosModel",YolosModel]],["dpt",["DPTModel",DPTModel]],["glpn",["GLPNModel",GLPNModel]],["hifigan",["SpeechT5HifiGan",SpeechT5HifiGan]],["efficientnet",["EfficientNetModel",EfficientNetModel]]]),MODEL_MAPPING_NAMES_ENCODER_DECODER=new Map([["t5",["T5Model",T5Model]],["longt5",["LongT5Model",LongT5Model]],["mt5",["MT5Model",MT5Model]],["bart",["BartModel",BartModel]],["mbart",["MBartModel",MBartModel]],["marian",["MarianModel",MarianModel]],["whisper",["WhisperModel",WhisperModel]],["m2m_100",["M2M100Model",M2M100Model]],["blenderbot",["BlenderbotModel",BlenderbotModel]],["blenderbot-small",["BlenderbotSmallModel",BlenderbotSmallModel]]]),MODEL_MAPPING_NAMES_DECODER_ONLY=new Map([["bloom",["BloomModel",BloomModel]],["gpt2",["GPT2Model",GPT2Model]],["gptj",["GPTJModel",GPTJModel]],["gpt_bigcode",["GPTBigCodeModel",GPTBigCodeModel]],["gpt_neo",["GPTNeoModel",GPTNeoModel]],["gpt_neox",["GPTNeoXModel",GPTNeoXModel]],["codegen",["CodeGenModel",CodeGenModel]],["llama",["LlamaModel",LlamaModel]],["qwen2",["Qwen2Model",Qwen2Model]],["phi",["PhiModel",PhiModel]],["mpt",["MptModel",MptModel]],["opt",["OPTModel",OPTModel]],["mistral",["MistralModel",MistralModel]],["starcoder2",["Starcoder2Model",Starcoder2Model]],["falcon",["FalconModel",FalconModel]]]),MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForSpeechToText",SpeechT5ForSpeechToText]],["whisper",["WhisperForConditionalGeneration",WhisperForConditionalGeneration]]]),MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES=new Map([["speecht5",["SpeechT5ForTextToSpeech",SpeechT5ForTextToSpeech]]]),MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES=new Map([["vits",["VitsModel",VitsModel]]]),MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForSequenceClassification",BertForSequenceClassification]],["roformer",["RoFormerForSequenceClassification",RoFormerForSequenceClassification]],["electra",["ElectraForSequenceClassification",ElectraForSequenceClassification]],["esm",["EsmForSequenceClassification",EsmForSequenceClassification]],["convbert",["ConvBertForSequenceClassification",ConvBertForSequenceClassification]],["camembert",["CamembertForSequenceClassification",CamembertForSequenceClassification]],["deberta",["DebertaForSequenceClassification",DebertaForSequenceClassification]],["deberta-v2",["DebertaV2ForSequenceClassification",DebertaV2ForSequenceClassification]],["mpnet",["MPNetForSequenceClassification",MPNetForSequenceClassification]],["albert",["AlbertForSequenceClassification",AlbertForSequenceClassification]],["distilbert",["DistilBertForSequenceClassification",DistilBertForSequenceClassification]],["roberta",["RobertaForSequenceClassification",RobertaForSequenceClassification]],["xlm",["XLMForSequenceClassification",XLMForSequenceClassification]],["xlm-roberta",["XLMRobertaForSequenceClassification",XLMRobertaForSequenceClassification]],["bart",["BartForSequenceClassification",BartForSequenceClassification]],["mbart",["MBartForSequenceClassification",MBartForSequenceClassification]],["mobilebert",["MobileBertForSequenceClassification",MobileBertForSequenceClassification]],["squeezebert",["SqueezeBertForSequenceClassification",SqueezeBertForSequenceClassification]]]),MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES=new Map([["bert",["BertForTokenClassification",BertForTokenClassification]],["roformer",["RoFormerForTokenClassification",RoFormerForTokenClassification]],["electra",["ElectraForTokenClassification",ElectraForTokenClassification]],["esm",["EsmForTokenClassification",EsmForTokenClassification]],["convbert",["ConvBertForTokenClassification",ConvBertForTokenClassification]],["camembert",["CamembertForTokenClassification",CamembertForTokenClassification]],["deberta",["DebertaForTokenClassification",DebertaForTokenClassification]],["deberta-v2",["DebertaV2ForTokenClassification",DebertaV2ForTokenClassification]],["mpnet",["MPNetForTokenClassification",MPNetForTokenClassification]],["distilbert",["DistilBertForTokenClassification",DistilBertForTokenClassification]],["roberta",["RobertaForTokenClassification",RobertaForTokenClassification]],["xlm",["XLMForTokenClassification",XLMForTokenClassification]],["xlm-roberta",["XLMRobertaForTokenClassification",XLMRobertaForTokenClassification]]]),MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES=new Map([["t5",["T5ForConditionalGeneration",T5ForConditionalGeneration]],["longt5",["LongT5ForConditionalGeneration",LongT5ForConditionalGeneration]],["mt5",["MT5ForConditionalGeneration",MT5ForConditionalGeneration]],["bart",["BartForConditionalGeneration",BartForConditionalGeneration]],["mbart",["MBartForConditionalGeneration",MBartForConditionalGeneration]],["marian",["MarianMTModel",MarianMTModel]],["m2m_100",["M2M100ForConditionalGeneration",M2M100ForConditionalGeneration]],["blenderbot",["BlenderbotForConditionalGeneration",BlenderbotForConditionalGeneration]],["blenderbot-small",["BlenderbotSmallForConditionalGeneration",BlenderbotSmallForConditionalGeneration]]]),MODEL_WITH_LM_HEAD_MAPPING_NAMES=new Map([["bloom",["BloomForCausalLM",BloomForCausalLM]],["gpt2",["GPT2LMHeadModel",GPT2LMHeadModel]],["gptj",["GPTJForCausalLM",GPTJForCausalLM]],["gpt_bigcode",["GPTBigCodeForCausalLM",GPTBigCodeForCausalLM]],["gpt_neo",["GPTNeoForCausalLM",GPTNeoForCausalLM]],["gpt_neox",["GPTNeoXForCausalLM",GPTNeoXForCausalLM]],["codegen",["CodeGenForCausalLM",CodeGenForCausalLM]],["llama",["LlamaForCausalLM",LlamaForCausalLM]],["qwen2",["Qwen2ForCausalLM",Qwen2ForCausalLM]],["phi",["PhiForCausalLM",PhiForCausalLM]],["mpt",["MptForCausalLM",MptForCausalLM]],["opt",["OPTForCausalLM",OPTForCausalLM]],["mbart",["MBartForCausalLM",MBartForCausalLM]],["mistral",["MistralForCausalLM",MistralForCausalLM]],["starcoder2",["Starcoder2ForCausalLM",Starcoder2ForCausalLM]],["falcon",["FalconForCausalLM",FalconForCausalLM]],["trocr",["TrOCRForCausalLM",TrOCRForCausalLM]],["stablelm",["StableLmForCausalLM",StableLmForCausalLM]]]),MODEL_FOR_MASKED_LM_MAPPING_NAMES=new Map([["bert",["BertForMaskedLM",BertForMaskedLM]],["roformer",["RoFormerForMaskedLM",RoFormerForMaskedLM]],["electra",["ElectraForMaskedLM",ElectraForMaskedLM]],["esm",["EsmForMaskedLM",EsmForMaskedLM]],["convbert",["ConvBertForMaskedLM",ConvBertForMaskedLM]],["camembert",["CamembertForMaskedLM",CamembertForMaskedLM]],["deberta",["DebertaForMaskedLM",DebertaForMaskedLM]],["deberta-v2",["DebertaV2ForMaskedLM",DebertaV2ForMaskedLM]],["mpnet",["MPNetForMaskedLM",MPNetForMaskedLM]],["albert",["AlbertForMaskedLM",AlbertForMaskedLM]],["distilbert",["DistilBertForMaskedLM",DistilBertForMaskedLM]],["roberta",["RobertaForMaskedLM",RobertaForMaskedLM]],["xlm",["XLMWithLMHeadModel",XLMWithLMHeadModel]],["xlm-roberta",["XLMRobertaForMaskedLM",XLMRobertaForMaskedLM]],["mobilebert",["MobileBertForMaskedLM",MobileBertForMaskedLM]],["squeezebert",["SqueezeBertForMaskedLM",SqueezeBertForMaskedLM]]]),MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES=new Map([["bert",["BertForQuestionAnswering",BertForQuestionAnswering]],["roformer",["RoFormerForQuestionAnswering",RoFormerForQuestionAnswering]],["electra",["ElectraForQuestionAnswering",ElectraForQuestionAnswering]],["convbert",["ConvBertForQuestionAnswering",ConvBertForQuestionAnswering]],["camembert",["CamembertForQuestionAnswering",CamembertForQuestionAnswering]],["deberta",["DebertaForQuestionAnswering",DebertaForQuestionAnswering]],["deberta-v2",["DebertaV2ForQuestionAnswering",DebertaV2ForQuestionAnswering]],["mpnet",["MPNetForQuestionAnswering",MPNetForQuestionAnswering]],["albert",["AlbertForQuestionAnswering",AlbertForQuestionAnswering]],["distilbert",["DistilBertForQuestionAnswering",DistilBertForQuestionAnswering]],["roberta",["RobertaForQuestionAnswering",RobertaForQuestionAnswering]],["xlm",["XLMForQuestionAnswering",XLMForQuestionAnswering]],["xlm-roberta",["XLMRobertaForQuestionAnswering",XLMRobertaForQuestionAnswering]],["mobilebert",["MobileBertForQuestionAnswering",MobileBertForQuestionAnswering]],["squeezebert",["SqueezeBertForQuestionAnswering",SqueezeBertForQuestionAnswering]]]),MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES=new Map([["vision-encoder-decoder",["VisionEncoderDecoderModel",VisionEncoderDecoderModel]]]),MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES=new Map([["vit",["ViTForImageClassification",ViTForImageClassification]],["fastvit",["FastViTForImageClassification",FastViTForImageClassification]],["mobilevit",["MobileViTForImageClassification",MobileViTForImageClassification]],["mobilevitv2",["MobileViTV2ForImageClassification",MobileViTV2ForImageClassification]],["beit",["BeitForImageClassification",BeitForImageClassification]],["deit",["DeiTForImageClassification",DeiTForImageClassification]],["convnext",["ConvNextForImageClassification",ConvNextForImageClassification]],["convnextv2",["ConvNextV2ForImageClassification",ConvNextV2ForImageClassification]],["dinov2",["Dinov2ForImageClassification",Dinov2ForImageClassification]],["resnet",["ResNetForImageClassification",ResNetForImageClassification]],["swin",["SwinForImageClassification",SwinForImageClassification]],["segformer",["SegformerForImageClassification",SegformerForImageClassification]],["efficientnet",["EfficientNetForImageClassification",EfficientNetForImageClassification]]]),MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES=new Map([["detr",["DetrForObjectDetection",DetrForObjectDetection]],["table-transformer",["TableTransformerForObjectDetection",TableTransformerForObjectDetection]],["yolos",["YolosForObjectDetection",YolosForObjectDetection]]]),MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES=new Map([["owlvit",["OwlViTForObjectDetection",OwlViTForObjectDetection]],["owlv2",["Owlv2ForObjectDetection",Owlv2ForObjectDetection]]]),MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES=new Map([["detr",["DetrForSegmentation",DetrForSegmentation]],["clipseg",["CLIPSegForImageSegmentation",CLIPSegForImageSegmentation]]]),MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES=new Map([["segformer",["SegformerForSemanticSegmentation",SegformerForSemanticSegmentation]]]),MODEL_FOR_MASK_GENERATION_MAPPING_NAMES=new Map([["sam",["SamModel",SamModel]]]),MODEL_FOR_CTC_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForCTC",Wav2Vec2ForCTC]],["wav2vec2-bert",["Wav2Vec2BertForCTC",Wav2Vec2BertForCTC]],["unispeech",["UniSpeechForCTC",UniSpeechForCTC]],["unispeech-sat",["UniSpeechSatForCTC",UniSpeechSatForCTC]],["wavlm",["WavLMForCTC",WavLMForCTC]],["hubert",["HubertForCTC",HubertForCTC]]]),MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES=new Map([["wav2vec2",["Wav2Vec2ForSequenceClassification",Wav2Vec2ForSequenceClassification]],["wav2vec2-bert",["Wav2Vec2BertForSequenceClassification",Wav2Vec2BertForSequenceClassification]],["unispeech",["UniSpeechForSequenceClassification",UniSpeechForSequenceClassification]],["unispeech-sat",["UniSpeechSatForSequenceClassification",UniSpeechSatForSequenceClassification]],["wavlm",["WavLMForSequenceClassification",WavLMForSequenceClassification]],["hubert",["HubertForSequenceClassification",HubertForSequenceClassification]],["audio-spectrogram-transformer",["ASTForAudioClassification",ASTForAudioClassification]]]),MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES=new Map([["wavlm",["WavLMForXVector",WavLMForXVector]]]),MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES=new Map([["unispeech-sat",["UniSpeechSatForAudioFrameClassification",UniSpeechSatForAudioFrameClassification]],["wavlm",["WavLMForAudioFrameClassification",WavLMForAudioFrameClassification]],["wav2vec2",["Wav2Vec2ForAudioFrameClassification",Wav2Vec2ForAudioFrameClassification]]]),MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES=new Map([["vitmatte",["VitMatteForImageMatting",VitMatteForImageMatting]]]),MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES=new Map([["swin2sr",["Swin2SRForImageSuperResolution",Swin2SRForImageSuperResolution]]]),MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES=new Map([["dpt",["DPTForDepthEstimation",DPTForDepthEstimation]],["depth_anything",["DepthAnythingForDepthEstimation",DepthAnythingForDepthEstimation]],["glpn",["GLPNForDepthEstimation",GLPNForDepthEstimation]]]),MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES=new Map([["clip",["CLIPVisionModelWithProjection",CLIPVisionModelWithProjection]],["siglip",["SiglipVisionModel",SiglipVisionModel]]]),MODEL_CLASS_TYPE_MAPPING=[[MODEL_MAPPING_NAMES_ENCODER_ONLY,MODEL_TYPES.EncoderOnly],[MODEL_MAPPING_NAMES_ENCODER_DECODER,MODEL_TYPES.EncoderDecoder],[MODEL_MAPPING_NAMES_DECODER_ONLY,MODEL_TYPES.DecoderOnly],[MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_WITH_LM_HEAD_MAPPING_NAMES,MODEL_TYPES.DecoderOnly],[MODEL_FOR_MASKED_LM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,MODEL_TYPES.Vision2Seq],[MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_MASK_GENERATION_MAPPING_NAMES,MODEL_TYPES.MaskGeneration],[MODEL_FOR_CTC_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES,MODEL_TYPES.Seq2Seq],[MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly],[MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES,MODEL_TYPES.EncoderOnly]];for(const[v,o]of MODEL_CLASS_TYPE_MAPPING)for(const[d,l]of v.values())MODEL_TYPE_MAPPING.set(d,o),MODEL_CLASS_TO_NAME_MAPPING.set(l,d),MODEL_NAME_TO_CLASS_MAPPING.set(d,l);const CUSTOM_MAPPING=[["CLIPTextModelWithProjection",CLIPTextModelWithProjection,MODEL_TYPES.EncoderOnly],["SiglipTextModel",SiglipTextModel,MODEL_TYPES.EncoderOnly],["ClapTextModelWithProjection",ClapTextModelWithProjection,MODEL_TYPES.EncoderOnly],["ClapAudioModelWithProjection",ClapAudioModelWithProjection,MODEL_TYPES.EncoderOnly]];for(const[v,o,d]of CUSTOM_MAPPING)MODEL_TYPE_MAPPING.set(v,d),MODEL_CLASS_TO_NAME_MAPPING.set(o,v),MODEL_NAME_TO_CLASS_MAPPING.set(v,o);class AutoModel extends PretrainedMixin{}Ht(AutoModel,"MODEL_CLASS_MAPPINGS",MODEL_CLASS_TYPE_MAPPING.map(v=>v[0])),Ht(AutoModel,"BASE_IF_FAIL",!0);class Seq2SeqLMOutput extends ModelOutput{constructor({logits:o,past_key_values:d,encoder_outputs:l,decoder_attentions:p=null,cross_attentions:b=null}){super(),this.logits=o,this.past_key_values=d,this.encoder_outputs=l,this.decoder_attentions=p,this.cross_attentions=b}}class SequenceClassifierOutput extends ModelOutput{constructor({logits:o}){super(),this.logits=o}}class XVectorOutput extends ModelOutput{constructor({logits:o,embeddings:d}){super(),this.logits=o,this.embeddings=d}}class TokenClassifierOutput extends ModelOutput{constructor({logits:o}){super(),this.logits=o}}class MaskedLMOutput extends ModelOutput{constructor({logits:o}){super(),this.logits=o}}class QuestionAnsweringModelOutput extends ModelOutput{constructor({start_logits:o,end_logits:d}){super(),this.start_logits=o,this.end_logits=d}}class CausalLMOutput extends ModelOutput{constructor({logits:o}){super(),this.logits=o}}class ImageMattingOutput extends ModelOutput{constructor({alphas:o}){super(),this.alphas=o}}class VitsModelOutput extends ModelOutput{constructor({waveform:o,spectrogram:d}){super(),this.waveform=o,this.spectrogram=d}}const BROWSER_ENV=typeof self<"u";if(!BROWSER_ENV&&!sharp)throw new Error("Unable to load image processing library.");function hanning(v){if(v<1)return new Float64Array;if(v===1)return new Float64Array([1]);const o=v-1,d=Math.PI/o,l=new Float64Array(v);for(let p=0;p<v;++p){const b=2*p-o;l[p]=.5+.5*Math.cos(d*b)}return l}const HERTZ_TO_MEL_MAPPING={htk:v=>2595*Math.log10(1+v/700),kaldi:v=>1127*Math.log(1+v/700),slaney:(v,o=1e3,d=15,l=27/Math.log(6.4))=>v>=o?d+Math.log(v/o)*l:3*v/200};function hertz_to_mel(v,o="htk"){const d=HERTZ_TO_MEL_MAPPING[o];if(!d)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof v=="number"?d(v):v.map(l=>d(l))}const MEL_TO_HERTZ_MAPPING={htk:v=>700*(10**(v/2595)-1),kaldi:v=>700*(Math.exp(v/1127)-1),slaney:(v,o=1e3,d=15,l=Math.log(6.4)/27)=>v>=d?o*Math.exp(l*(v-d)):200*v/3};function mel_to_hertz(v,o="htk"){const d=MEL_TO_HERTZ_MAPPING[o];if(!d)throw new Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return typeof v=="number"?d(v):v.map(l=>d(l))}function _create_triangular_filter_bank(v,o){const d=Float64Array.from({length:o.length-1},(c,m)=>o[m+1]-o[m]),l=Array.from({length:v.length},()=>new Array(o.length));for(let c=0;c<v.length;++c){const m=l[c];for(let _=0;_<o.length;++_)m[_]=o[_]-v[c]}const p=o.length-2,b=Array.from({length:p},()=>new Array(v.length));for(let c=0;c<v.length;++c){const m=l[c];for(let _=0;_<p;++_){const f=-m[_]/d[_],u=m[_+2]/d[_+1];b[_][c]=Math.max(0,Math.min(f,u))}}return b}function linspace(v,o,d){const l=(o-v)/(d-1);return Float64Array.from({length:d},(p,b)=>v+l*b)}function mel_filter_bank(v,o,d,l,p,b=null,c="htk",m=!1){if(b!==null&&b!=="slaney")throw new Error('norm must be one of null or "slaney"');const _=hertz_to_mel(d,c),f=hertz_to_mel(l,c),u=linspace(_,f,o+2);let n=mel_to_hertz(u,c),e;if(m){const s=p/(v*2);e=hertz_to_mel(Float64Array.from({length:v},(g,y)=>y*s),c),n=u}else e=linspace(0,Math.floor(p/2),v);const a=_create_triangular_filter_bank(e,n);if(b!==null&&b==="slaney")for(let s=0;s<o;++s){const g=a[s],y=2/(n[s+2]-n[s]);for(let x=0;x<v;++x)g[x]*=y}return a}function padReflect(v,o,d){const l=new v.constructor(v.length+o+d),p=v.length-1;for(let b=0;b<v.length;++b)l[o+b]=v[b];for(let b=1;b<=o;++b)l[o-b]=v[calculateReflectOffset(b,p)];for(let b=1;b<=d;++b)l[p+o+b]=v[calculateReflectOffset(p-b,p)];return l}function _db_conversion_helper(v,o,d,l,p){if(d<=0)throw new Error("reference must be greater than zero");if(l<=0)throw new Error("min_value must be greater than zero");d=Math.max(l,d);const b=Math.log10(d);for(let c=0;c<v.length;++c)v[c]=o*Math.log10(Math.max(l,v[c])-b);if(p!==null){if(p<=0)throw new Error("db_range must be greater than zero");const c=max(v)[0]-p;for(let m=0;m<v.length;++m)v[m]=Math.max(v[m],c)}return v}function amplitude_to_db(v,o=1,d=1e-5,l=null){return _db_conversion_helper(v,20,o,d,l)}function power_to_db(v,o=1,d=1e-10,l=null){return _db_conversion_helper(v,10,o,d,l)}function spectrogram(v,o,d,l,{fft_length:p=null,power:b=1,center:c=!0,pad_mode:m="reflect",onesided:_=!0,preemphasis:f=null,mel_filters:u=null,mel_floor:n=1e-10,log_mel:e=null,reference:a=1,min_value:s=1e-10,db_range:g=null,remove_dc_offset:y=null,max_num_frames:x=null,do_pad:E=!0,transpose:S=!1}={}){const P=o.length;if(p===null&&(p=d),d>p)throw Error(`frame_length (${d}) may not be larger than fft_length (${p})`);if(P!==d)throw new Error(`Length of the window (${P}) must equal frame_length (${d})`);if(l<=0)throw new Error("hop_length must be greater than zero");if(b===null&&u!==null)throw new Error("You have provided `mel_filters` but `power` is `None`. Mel spectrogram computation is not yet supported for complex-valued spectrogram. Specify `power` to fix this issue.");if(c){if(m!=="reflect")throw new Error(`pad_mode="${m}" not implemented yet.`);const F=Math.floor((p-1)/2)+1;v=padReflect(v,F,F)}const O=Math.floor(1+Math.floor((v.length-d)/l)),k=_?Math.floor(p/2)+1:p;let D=O,C=O;x!==null&&(x>O?E&&(C=x):C=D=x);const A=new FFT(p),$=new Float64Array(p),W=new Float64Array(A.outputBufferSize),K=new Array(D);for(let F=0;F<D;++F){const B=F*l;for(let ne=0;ne<d;++ne)$[ne]=v[B+ne];if(y){let ne=0;for(let Q=0;Q<d;++Q)ne+=$[Q];const z=ne/d;for(let Q=0;Q<d;++Q)$[Q]-=z}if(f!==null){for(let ne=d-1;ne>=1;--ne)$[ne]-=f*$[ne-1];$[0]*=1-f}for(let ne=0;ne<o.length;++ne)$[ne]*=o[ne];A.realTransform(W,$);const fe=new Array(k);for(let ne=0;ne<fe.length;++ne){const z=ne<<1;fe[ne]=W[z]**2+W[z+1]**2}K[F]=fe}if(b!==null&&b!==2){const F=2/b;for(let B=0;B<K.length;++B){const fe=K[B];for(let ne=0;ne<fe.length;++ne)fe[ne]**=F}}const Y=u.length,q=new Float32Array(Y*C),se=S?[C,Y]:[Y,C];for(let F=0;F<Y;++F){const B=u[F];for(let fe=0;fe<D;++fe){const ne=K[fe];let z=0;for(let Q=0;Q<k;++Q)z+=B[Q]*ne[Q];q[S?fe*Y+F:F*D+fe]=Math.max(n,z)}}if(b!==null&&e!==null){const F=Math.min(q.length,D*Y);switch(e){case"log":for(let B=0;B<F;++B)q[B]=Math.log(q[B]);break;case"log10":for(let B=0;B<F;++B)q[B]=Math.log10(q[B]);break;case"dB":if(b===1)amplitude_to_db(q,a,s,g);else if(b===2)power_to_db(q,a,s,g);else throw new Error(`Cannot use log_mel option '${e}' with power ${b}`);break;default:throw new Error(`log_mel must be one of null, 'log', 'log10' or 'dB'. Got '${e}'`)}}return{data:q,dims:se}}function window_function(v,o,{periodic:d=!0,frame_length:l=null,center:p=!0}={}){const b=d?v+1:v;let c;switch(o){case"boxcar":c=new Float64Array(b).fill(1);break;case"hann":case"hann_window":c=hanning(b);break;case"povey":c=hanning(b).map(m=>Math.pow(m,.85));break;default:throw new Error(`Unknown window type ${o}.`)}if(d&&(c=c.subarray(0,v)),l===null)return c;if(v>l)throw new Error(`Length of the window (${v}) may not be larger than frame_length (${l})`);return c}function center_to_corners_format([v,o,d,l]){return[v-d/2,o-l/2,v+d/2,o+l/2]}function post_process_object_detection(v,o=.5,d=null,l=!1){const p=v.logits,b=v.pred_boxes,[c,m,_]=p.dims;if(d!==null&&d.length!==c)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let f=[];for(let u=0;u<c;++u){let n=d!==null?d[u]:null,e={boxes:[],classes:[],scores:[]},a=p[u],s=b[u];for(let g=0;g<m;++g){let y=a[g],x=[],E;if(l){E=y.sigmoid().data;for(let S=0;S<E.length;++S)E[S]>o&&x.push(S)}else{let S=max(y.data)[1];if(S===_-1)continue;x.push(S),E=softmax(y.data)}for(const S of x){let P=s[g].data;P=center_to_corners_format(P),n!==null&&(P=P.map((O,k)=>O*n[(k+1)%2])),e.boxes.push(P),e.classes.push(S),e.scores.push(E[S])}}f.push(e)}return f}function validate_audio_inputs(v,o){var d;if(!(v instanceof Float32Array||v instanceof Float64Array))throw new Error(`${o} expects input to be a Float32Array or a Float64Array, but got ${((d=v==null?void 0:v.constructor)==null?void 0:d.name)??typeof v} 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.`)}function constraint_to_multiple_of(v,o,d=0,l=null){const p=v/o;let b=bankers_round(p)*o;return l!==null&&b>l&&(b=Math.floor(p)*o),b<d&&(b=Math.ceil(p)*o),b}function enforce_size_divisibility([v,o],d){return[Math.max(Math.floor(v/d),1)*d,Math.max(Math.floor(o/d),1)*d]}class FeatureExtractor extends Callable{constructor(o){super(),this.config=o}}class ImageFeatureExtractor extends FeatureExtractor{constructor(o){super(o),this.image_mean=this.config.image_mean??this.config.mean,this.image_std=this.config.image_std??this.config.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_divisibility=this.config.size_divisibility??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&&this.size.width!==void 0&&this.size.height!==void 0&&(this.pad_size=this.size),this.do_flip_channel_order=this.config.do_flip_channel_order??!1}async thumbnail(o,d,l=2){const p=o.height,b=o.width,c=d.height,m=d.width;let _=Math.min(p,c),f=Math.min(b,m);return _===p&&f===b?o:(p>b?f=Math.floor(b*_/p):b>p&&(_=Math.floor(p*f/b)),await o.resize(f,_,{resample:l}))}async crop_margin(o,d=200){const l=o.clone().grayscale(),p=min(l.data)[0],b=max(l.data)[0]-p;if(b===0)return o;const c=d/255;let m=l.width,_=l.height,f=0,u=0;for(let n=0;n<l.height;++n){const e=n*l.width;for(let a=0;a<l.width;++a)(l.data[e+a]-p)/b<c&&(m=Math.min(m,a),_=Math.min(_,n),f=Math.max(f,a),u=Math.max(u,n))}return o=await o.crop([m,_,f,u]),o}pad_image(o,d,l,{mode:p="constant",center:b=!1,constant_values:c=0}={}){const[m,_,f]=d;let u,n;if(typeof l=="number"?(u=l,n=l):(u=l.width,n=l.height),u!==_||n!==m){const e=new Float32Array(u*n*f);if(Array.isArray(c))for(let g=0;g<e.length;++g)e[g]=c[g%f];else c!==0&&e.fill(c);const[a,s]=b?[Math.floor((u-_)/2),Math.floor((n-m)/2)]:[0,0];for(let g=0;g<m;++g){const y=(g+s)*u,x=g*_;for(let E=0;E<_;++E){const S=(y+E+a)*f,P=(x+E)*f;for(let O=0;O<f;++O)e[S+O]=o[P+O]}}if(p==="symmetric"){if(b)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const g=m-1,y=_-1;for(let x=0;x<n;++x){const E=x*u,S=calculateReflectOffset(x,g)*_;for(let P=0;P<u;++P){if(x<m&&P<_)continue;const O=(E+P)*f,k=(S+calculateReflectOffset(P,y))*f;for(let D=0;D<f;++D)e[O+D]=o[k+D]}}}o=e,d=[n,u,f]}return[o,d]}rescale(o){for(let d=0;d<o.length;++d)o[d]=this.rescale_factor*o[d]}get_resize_output_image_size(o,d){const[l,p]=o.size;let b,c;if(this.do_thumbnail){const{height:m,width:_}=d;b=Math.min(m,_)}else Number.isInteger(d)?(b=d,c=this.config.max_size??b):d!==void 0&&(b=d.shortest_edge,c=d.longest_edge);if(b!==void 0||c!==void 0){const m=b===void 0?1:Math.max(b/l,b/p),_=l*m,f=p*m,u=c===void 0?1:Math.min(c/_,c/f);let n=Math.floor(Number((_*u).toFixed(2))),e=Math.floor(Number((f*u).toFixed(2)));return this.size_divisibility!==void 0&&([n,e]=enforce_size_divisibility([n,e],this.size_divisibility)),[n,e]}else if(d!==void 0&&d.width!==void 0&&d.height!==void 0){let m=d.width,_=d.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let f=_/p,u=m/l;Math.abs(1-u)<Math.abs(1-f)?f=u:u=f,_=constraint_to_multiple_of(f*p,this.config.ensure_multiple_of),m=constraint_to_multiple_of(u*l,this.config.ensure_multiple_of)}return[m,_]}else{if(this.size_divisibility!==void 0)return enforce_size_divisibility([l,p],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(d)}`)}}async resize(o){const[d,l]=this.get_resize_output_image_size(o,this.size);return await o.resize(d,l,{resample:this.resample})}async preprocess(o,{do_normalize:d=null,do_pad:l=null,do_convert_rgb:p=null,do_convert_grayscale:b=null,do_flip_channel_order:c=null}={}){this.do_crop_margin&&(o=await this.crop_margin(o));const[m,_]=o.size;if(p??this.do_convert_rgb?o=o.rgb():b&&(o=o.grayscale()),this.do_resize&&(o=await this.resize(o)),this.do_thumbnail&&(o=await this.thumbnail(o,this.size,this.resample)),this.do_center_crop){let a,s;Number.isInteger(this.crop_size)?(a=this.crop_size,s=this.crop_size):(a=this.crop_size.width,s=this.crop_size.height),o=await o.center_crop(a,s)}const f=[o.height,o.width];let u=Float32Array.from(o.data),n=[o.height,o.width,o.channels];if(this.do_rescale&&this.rescale(u),d??this.do_normalize){let a=this.image_mean;Array.isArray(this.image_mean)||(a=new Array(o.channels).fill(a));let s=this.image_std;if(Array.isArray(this.image_std)||(s=new Array(o.channels).fill(a)),a.length!==o.channels||s.length!==o.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${a.length}) and \`image_std\` (${s.length}) must match the number of channels in the image (${o.channels}).`);for(let g=0;g<u.length;g+=o.channels)for(let y=0;y<o.channels;++y)u[g+y]=(u[g+y]-a[y])/s[y]}if(l??this.do_pad){if(this.pad_size)[u,n]=this.pad_image(u,[o.height,o.width,o.channels],this.pad_size);else if(this.size_divisibility){const[a,s]=enforce_size_divisibility([n[1],n[0]],this.size_divisibility);[u,n]=this.pad_image(u,n,{width:a,height:s})}}if(c??this.do_flip_channel_order){if(n[2]!==3)throw new Error("Flipping channel order is only supported for RGB images.");for(let a=0;a<u.length;a+=3){const s=u[a];u[a]=u[a+2],u[a+2]=s}}const e=new Tensor("float32",u,n).permute(2,0,1);return{original_size:[_,m],reshaped_input_size:f,pixel_values:e}}async _call(o,...d){Array.isArray(o)||(o=[o]);const l=await Promise.all(o.map(p=>this.preprocess(p)));return{pixel_values:stack(l.map(p=>p.pixel_values),0),original_sizes:l.map(p=>p.original_size),reshaped_input_sizes:l.map(p=>p.reshaped_input_size)}}}class SegformerFeatureExtractor extends ImageFeatureExtractor{post_process_semantic_segmentation(o,d=null){const l=o.logits,p=l.dims[0];if(d!==null&&d.length!==p)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const b=[];for(let c=0;c<p;++c){const m=d!==null?d[c]:null;let _=l[c];m!==null&&(_=interpolate(_,m,"bilinear",!1));const[f,u]=m??_.dims.slice(-2),n=new Tensor("int32",new Int32Array(f*u),[f,u]),e=_[0].data;for(let y=1;y<_.dims[0];++y){const x=_[y].data;for(let E=0;E<x.length;++E)x[E]>e[E]&&(e[E]=x[E],n.data[E]=y)}const a=new Array(_.dims[0]),s=n.data;for(let y=0;y<s.length;++y){const x=s[y];a[x]=x}const g=a.filter(y=>y!==void 0);b.push({segmentation:n,labels:g})}return b}}class DPTFeatureExtractor extends ImageFeatureExtractor{}class DPTImageProcessor extends DPTFeatureExtractor{}class BitImageProcessor extends ImageFeatureExtractor{}class GLPNFeatureExtractor extends ImageFeatureExtractor{}class CLIPFeatureExtractor extends ImageFeatureExtractor{}class ChineseCLIPFeatureExtractor extends ImageFeatureExtractor{}class SiglipImageProcessor extends ImageFeatureExtractor{}class ConvNextFeatureExtractor extends ImageFeatureExtractor{constructor(o){super(o),this.crop_pct=this.config.crop_pct??224/256}async resize(o){var d;const l=(d=this.size)==null?void 0:d.shortest_edge;if(l===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(l<384){const p=Math.floor(l/this.crop_pct),[b,c]=this.get_resize_output_image_size(o,{shortest_edge:p});o=await o.resize(b,c,{resample:this.resample}),o=await o.center_crop(l,l)}else o=await o.resize(l,l,{resample:this.resample});return o}}class ConvNextImageProcessor extends ConvNextFeatureExtractor{}class ViTFeatureExtractor extends ImageFeatureExtractor{}class ViTImageProcessor extends ImageFeatureExtractor{}class EfficientNetImageProcessor extends ImageFeatureExtractor{constructor(o){super(o),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(d=>d*d))}}class MobileViTFeatureExtractor extends ImageFeatureExtractor{}class MobileViTImageProcessor extends MobileViTFeatureExtractor{}class OwlViTFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...o){return post_process_object_detection(...o)}}class Owlv2ImageProcessor extends OwlViTFeatureExtractor{}class DeiTFeatureExtractor extends ImageFeatureExtractor{}class BeitFeatureExtractor extends ImageFeatureExtractor{}class DonutFeatureExtractor extends ImageFeatureExtractor{pad_image(o,d,l,p={}){const[b,c,m]=d;let _=this.image_mean;Array.isArray(this.image_mean)||(_=new Array(m).fill(_));let f=this.image_std;Array.isArray(f)||(f=new Array(m).fill(_));const u=_.map((n,e)=>-n/f[e]);return super.pad_image(o,d,l,{center:!0,constant_values:u,...p})}}class NougatImageProcessor extends DonutFeatureExtractor{}class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(o){const d=await super._call(o),l=[d.pixel_values.dims[0],64,64],p=new Tensor("int64",new BigInt64Array(l.reduce((b,c)=>b*c)).fill(1n),l);return{...d,pixel_mask:p}}post_process_object_detection(...o){return post_process_object_detection(...o)}remove_low_and_no_objects(o,d,l,p){let b=[],c=[],m=[];for(let _=0;_<o.dims[0];++_){let f=o[_],u=d[_],n=max(f.data)[1];if(n===p)continue;let e=softmax(f.data)[n];e>l&&(b.push(u),c.push(e),m.push(n))}return[b,c,m]}check_segment_validity(o,d,l,p=.5,b=.8){let c=[],m=0,_=0;for(let u=0;u<o.length;++u)o[u]===l&&(c.push(u),++m),d[l].data[u]>=p&&++_;let f=m>0&&_>0;return f&&(f=m/_>b),[f,c]}compute_segments(o,d,l,p,b,c=null,m=null){let[_,f]=m??o[0].dims,u=new Tensor("int32",new Int32Array(_*f),[_,f]),n=[];if(m!==null)for(let g=0;g<o.length;++g)o[g]=interpolate(o[g],m,"bilinear",!1);let e=new Int32Array(o[0].data.length),a=new Float32Array(o[0].data.length);for(let g=0;g<o.length;++g){let y=d[g];for(let x=0;x<o[g].data.length;++x)o[g].data[x]*=y,o[g].data[x]>a[x]&&(e[x]=g,a[x]=o[g].data[x])}let s=0;for(let g=0;g<l.length;++g){let y=l[g],[x,E]=this.check_segment_validity(e,o,g,p,b);if(x){++s;for(let S of E)u.data[S]=s;n.push({id:s,label_id:y,score:d[g]})}}return[u,n]}post_process_panoptic_segmentation(o,d=.5,l=.5,p=.8,b=null,c=null){b===null&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),b=new Set);const m=o.logits,_=o.pred_masks.sigmoid();let[f,u,n]=m.dims;if(n-=1,c!==null&&c.length!==f)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let e=[];for(let a=0;a<f;++a){let s=c!==null?c[a]:null,g=m[a],y=_[a],[x,E,S]=this.remove_low_and_no_objects(g,y,d,n);if(S.length===0){let[k,D]=s??y.dims.slice(-2),C=new Tensor("int32",new Int32Array(k*D).fill(-1),[k,D]);e.push({segmentation:C,segments_info:[]});continue}let[P,O]=this.compute_segments(x,E,S,l,p,b,s);e.push({segmentation:P,segments_info:O})}return e}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class YolosFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...o){return post_process_object_detection(...o)}}class SamImageProcessor extends ImageFeatureExtractor{reshape_input_points(o,d,l){o=structuredClone(o);let p=calculateDimensions(o);if(p.length===3)p=[1,...p],o=[o];else if(p.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 b=0;b<o.length;++b){let c=d[b],m=l[b],_=[m[0]/c[0],m[1]/c[1]];for(let f=0;f<o[b].length;++f)for(let u=0;u<o[b][f].length;++u)for(let n=0;n<o[b][f][u].length;++n)o[b][f][u][n]*=_[n]}return new Tensor("float32",Float32Array.from(o.flat(1/0)),p)}add_input_labels(o,d){let l=calculateDimensions(o);if(l.length===2)l=[1,...l],o=[o];else if(l.length!==3)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(l.some((p,b)=>p!==d.dims[b]))throw Error(`The first ${l.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new Tensor("int64",o.flat(1/0).map(BigInt),l)}async _call(o,d=null,l=null){const p=await super._call(o);if(d&&(p.input_points=this.reshape_input_points(d,p.original_sizes,p.reshaped_input_sizes)),l){if(!p.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");p.input_labels=this.add_input_labels(l,p.input_points)}return p}post_process_masks(o,d,l,{mask_threshold:p=0,binarize:b=!0,pad_size:c=null}={}){const m=[];c=c??this.pad_size;const _=[c.height,c.width];for(let f=0;f<d.length;++f){const u=d[f],n=l[f],e=o[f],a=[];for(let s=0;s<e.dims[0];++s){const g=e[s];let y=interpolate(g,_,"bilinear",!1);if(y=y.slice(null,[0,n[0]],[0,n[1]]),y=interpolate(y,u,"bilinear",!1),b){const x=new Uint8Array(y.data.length);for(let E=0;E<y.data.length;++E)y.data[E]>p&&(x[E]=1);y=new Tensor("bool",x,y.dims)}a.push(y)}m.push(stack(a))}return m}}class Swin2SRImageProcessor extends ImageFeatureExtractor{pad_image(o,d,l,p={}){const[b,c,m]=d;return super.pad_image(o,d,{width:c+(l-c%l)%l,height:b+(l-b%l)%l},{mode:"symmetric",center:!1,constant_values:-1,...p})}}class VitMatteImageProcessor extends ImageFeatureExtractor{async _call(o,d){Array.isArray(o)||(o=[o]),Array.isArray(d)||(d=[d]);const l=await Promise.all(o.map(b=>this.preprocess(b))),p=await Promise.all(d.map(b=>this.preprocess(b,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:stack(l.map((b,c)=>cat([b.pixel_values,p[c].pixel_values],0)),0),original_sizes:l.map(b=>b.original_size),reshaped_input_sizes:l.map(b=>b.reshaped_input_size)}}}class WhisperFeatureExtractor extends FeatureExtractor{constructor(o){var d;super(o),(d=this.config).mel_filters??(d.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(o){const{data:d,dims:l}=spectrogram(o,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}),p=max(d)[0];for(let b=0;b<d.length;++b)d[b]=(Math.max(d[b],p-8)+4)/4;return{data:d,dims:l}}async _call(o){validate_audio_inputs(o,"WhisperFeatureExtractor");let d;o.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`."),d=o.slice(0,this.config.n_samples)):(d=new Float32Array(this.config.n_samples),d.set(o));const{data:l,dims:p}=this._extract_fbank_features(d);return{input_features:new Tensor("float32",l,[1,...p])}}}class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(o){const d=o.reduce((p,b)=>p+b,0)/o.length,l=o.reduce((p,b)=>p+(b-d)**2,0)/o.length;return o.map(p=>(p-d)/Math.sqrt(l+1e-7))}async _call(o){validate_audio_inputs(o,"Wav2Vec2FeatureExtractor"),o instanceof Float64Array&&(o=new Float32Array(o));let d=o;this.config.do_normalize&&(d=this._zero_mean_unit_var_norm(d));const l=[1,d.length];return{input_values:new Tensor("float32",d,l),attention_mask:new Tensor("int64",new BigInt64Array(d.length).fill(1n),l)}}}class SeamlessM4TFeatureExtractor extends FeatureExtractor{constructor(o){super(o);const d=this.config.sampling_rate,l=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(d/2),d,null,"kaldi",!0);for(let p=0;p<l.length;++p)l[p].push(0);this.mel_filters=l,this.window=window_function(400,"povey",{periodic:!1})}_extract_fbank_features(o,d){return o=o.map(l=>l*32768),spectrogram(o,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:d,transpose:!0})}async _call(o,{padding:d=!0,pad_to_multiple_of:l=2,do_normalize_per_mel_bins:p=!0,return_attention_mask:b=!0}={}){validate_audio_inputs(o,"SeamlessM4TFeatureExtractor");let c=this._extract_fbank_features(o,this.config.max_length);if(p){const[a,s]=c.dims;for(let g=0;g<s;++g){let y=0;for(let P=0;P<a;++P)y+=c.data[P*s+g];const x=y/a;let E=0;for(let P=0;P<a;++P)E+=(c.data[P*s+g]-x)**2;E/=a-1;const S=Math.sqrt(E+1e-7);for(let P=0;P<a;++P){const O=P*s+g;c.data[O]=(c.data[O]-x)/S}}}let m;if(d){const[a,s]=c.dims,g=a%l;if(g>0){const y=new Float32Array(s*(a+g));y.set(c.data),y.fill(this.config.padding_value,c.data.length);const x=a+g;c={data:y,dims:[x,s]},b&&(m=new Tensor("int64",new BigInt64Array(x),[1,x]),m.data.fill(1n,0,a))}}const[_,f]=c.dims,u=this.config.stride;if(_%u!==0)throw new Error(`The number of frames (${_}) must be a multiple of the stride (${u}).`);const n=new Tensor("float32",c.data,c.dims).view(1,Math.floor(_/u),f*u),e={input_features:n};if(b){const a=n.dims[1],s=new Tensor("int64",new BigInt64Array(a),[1,a]);if(m)for(let g=1,y=0;g<_;g+=u,++y)s.data[y]=m.data[g];else s.data.fill(1n);e.attention_mask=s}return e}}class ASTFeatureExtractor extends FeatureExtractor{constructor(o){super(o);const d=this.config.sampling_rate,l=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(d/2),d,null,"kaldi",!0);for(let p=0;p<l.length;++p)l[p].push(0);this.mel_filters=l,this.window=window_function(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(o,d){return spectrogram(o,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:d,transpose:!0})}async _call(o){validate_audio_inputs(o,"ASTFeatureExtractor");const d=this._extract_fbank_features(o,this.config.max_length);if(this.config.do_normalize){const l=this.std*2;for(let p=0;p<d.data.length;++p)d.data[p]=(d.data[p]-this.mean)/l}return{input_values:new Tensor("float32",d.data,[1,...d.dims])}}}class ClapFeatureExtractor extends FeatureExtractor{constructor(o){super(o),this.mel_filters=mel_filter_bank(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=mel_filter_bank(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=window_function(this.config.fft_window_size,"hann")}_get_input_mel(o,d,l,p){let b,c=!1;const m=o.length-d;if(m>0)if(l==="rand_trunc"){c=!0;const _=Math.floor(Math.random()*(m+1));o=o.subarray(_,_+d),b=this._extract_fbank_features(o,this.mel_filters_slaney,this.config.nb_max_samples),b.dims=[1,...b.dims]}else throw new Error(`Truncation strategy "${l}" not implemented`);else{if(m<0){let _=new Float64Array(d);if(_.set(o),p==="repeat")for(let f=o.length;f<d;f+=o.length)_.set(o.subarray(0,Math.min(o.length,d-f)),f);else if(p==="repeatpad")for(let f=o.length;f<-m;f+=o.length)_.set(o,f);o=_}if(l==="fusion")throw new Error(`Truncation strategy "${l}" not implemented`);b=this._extract_fbank_features(o,this.mel_filters_slaney,this.config.nb_max_samples),b.dims=[1,...b.dims]}return{...b,longer:c}}_extract_fbank_features(o,d,l=null){return spectrogram(o,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:d,log_mel:"dB",max_num_frames:l,do_pad:!1,transpose:!0})}async _call(o,{max_length:d=null}={}){validate_audio_inputs(o,"ClapFeatureExtractor");const l=this._get_input_mel(o,d??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new Tensor("float32",l.data,[1,...l.dims])}}}class SpeechT5FeatureExtractor extends FeatureExtractor{}class Processor extends Callable{constructor(o){super(),this.feature_extractor=o}async _call(o,...d){return await this.feature_extractor(o,...d)}}class SamProcessor extends Processor{async _call(...o){return await this.feature_extractor(...o)}post_process_masks(...o){return this.feature_extractor.post_process_masks(...o)}reshape_input_points(...o){return this.feature_extractor.reshape_input_points(...o)}}class WhisperProcessor extends Processor{async _call(o){return await this.feature_extractor(o)}}class Wav2Vec2ProcessorWithLM extends Processor{async _call(o){return await this.feature_extractor(o)}}class SpeechT5Processor extends Processor{async _call(o){return await this.feature_extractor(o)}}class OwlViTProcessor extends Processor{}class AutoProcessor{static async from_pretrained(o,{progress_callback:d=null,config:l=null,cache_dir:p=null,local_files_only:b=!1,revision:c="main"}={}){let m=l??await getModelJSON(o,"preprocessor_config.json",!0,{progress_callback:d,cache_dir:p,local_files_only:b,revision:c}),_=m.feature_extractor_type??m.image_processor_type,f=this.FEATURE_EXTRACTOR_CLASS_MAPPING[_];if(!f)if(m.size!==void 0)console.warn(`Feature extractor type "${_}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),f=ImageFeatureExtractor;else throw new Error(`Unknown Feature Extractor type: ${_}`);let u=this.PROCESSOR_CLASS_MAPPING[m.processor_class]??Processor,n=new f(m);return new u(n)}}Ht(AutoProcessor,"FEATURE_EXTRACTOR_CLASS_MAPPING",{ImageFeatureExtractor,WhisperFeatureExtractor,ViTFeatureExtractor,MobileViTFeatureExtractor,MobileViTImageProcessor,OwlViTFeatureExtractor,Owlv2ImageProcessor,CLIPFeatureExtractor,ChineseCLIPFeatureExtractor,SiglipImageProcessor,ConvNextFeatureExtractor,ConvNextImageProcessor,SegformerFeatureExtractor,BitImageProcessor,DPTImageProcessor,DPTFeatureExtractor,GLPNFeatureExtractor,BeitFeatureExtractor,DeiTFeatureExtractor,DetrFeatureExtractor,YolosFeatureExtractor,DonutFeatureExtractor,NougatImageProcessor,EfficientNetImageProcessor,ViTImageProcessor,VitMatteImageProcessor,SamImageProcessor,Swin2SRImageProcessor,Wav2Vec2FeatureExtractor,SeamlessM4TFeatureExtractor,SpeechT5FeatureExtractor,ASTFeatureExtractor,ClapFeatureExtractor}),Ht(AutoProcessor,"PROCESSOR_CLASS_MAPPING",{WhisperProcessor,Wav2Vec2ProcessorWithLM,SamProcessor,SpeechT5Processor,OwlViTProcessor});class CLAPProcessor{constructor(){this.model=null,this.processor=null,this.defaultLabels=["speech","music","singing","guitar","piano","drums","violin","trumpet","saxophone","flute","classical music","rock music","pop music","jazz","electronic music","ambient","nature sounds","rain","wind","ocean waves","birds chirping","dog barking","cat meowing","car engine","traffic","footsteps","door closing","applause","laughter","crying","coughing","sneezing","telephone ringing","alarm clock","typing","water running","fire crackling","thunder","helicopter","airplane","train","motorcycle","bell ringing","whistle","horn","siren","explosion","gunshot","silence","noise","distortion"]}async initialize(){if(!(this.model&&this.processor))try{this.processor=await AutoProcessor.from_pretrained("Xenova/clap-htsat-unfused"),this.model=await ClapAudioModelWithProjection.from_pretrained("Xenova/clap-htsat-unfused"),console.log("CLAP model loaded successfully")}catch(o){throw console.error("Failed to load CLAP model:",o),o}}async processAudio(o){(!this.model||!this.processor)&&await this.initialize();try{const d=await this.preprocessAudio(o),l=await this.processor(d),p=await this.model.get_audio_features(l),b=await this.processor.text(this.defaultLabels),c=await this.model.get_text_features(b),m=await this.calculateSimilarities(p,c);return this.getTopTags(m,5)}catch(d){throw console.error("Error processing audio:",d),d}}async preprocessAudio(o){let d;if(o.numberOfChannels>1){d=new Float32Array(o.length);for(let p=0;p<o.length;p++){let b=0;for(let c=0;c<o.numberOfChannels;c++)b+=o.getChannelData(c)[p];d[p]=b/o.numberOfChannels}}else d=o.getChannelData(0);const l=48e3;return o.sampleRate!==l&&(d=await this.resampleAudio(d,o.sampleRate,l)),d}async resampleAudio(o,d,l){const p=d/l,b=Math.round(o.length/p),c=new Float32Array(b);for(let m=0;m<b;m++){const _=m*p,f=Math.floor(_),u=Math.min(f+1,o.length-1),n=_-f;c[m]=o[f]*(1-n)+o[u]*n}return c}async calculateSimilarities(o,d){const l=o.data,p=[];for(let b=0;b<this.defaultLabels.length;b++){const c=d.data.slice(b*l.length,(b+1)*l.length),m=this.cosineSimilarity(l,c);p.push(m)}return p}cosineSimilarity(o,d){let l=0,p=0,b=0;for(let c=0;c<o.length;c++)l+=o[c]*d[c],p+=o[c]*o[c],b+=d[c]*d[c];return l/(Math.sqrt(p)*Math.sqrt(b))}getTopTags(o,d=5){return this.defaultLabels.map((l,p)=>({label:l,confidence:Math.max(0,o[p])})).sort((l,p)=>p.confidence-l.confidence).slice(0,d)}async fileToAudioBuffer(o){const d=await o.arrayBuffer();return await new(window.AudioContext||window.webkitAudioContext)().decodeAudioData(d)}}class UserFeedbackStore{constructor(){this.dbName="ClipTaggerDB",this.version=1,this.db=null}async initialize(){return new Promise((o,d)=>{const l=indexedDB.open(this.dbName,this.version);l.onerror=()=>d(l.error),l.onsuccess=()=>{this.db=l.result,o()},l.onupgradeneeded=p=>{const b=p.target.result;if(b.objectStoreNames.contains("audioFeedback")||b.createObjectStore("audioFeedback",{keyPath:"id",autoIncrement:!0}).createIndex("timestamp","timestamp",{unique:!1}),!b.objectStoreNames.contains("tagFeedback")){const c=b.createObjectStore("tagFeedback",{keyPath:"id",autoIncrement:!0});c.createIndex("tag","tag",{unique:!1}),c.createIndex("timestamp","timestamp",{unique:!1})}b.objectStoreNames.contains("customTags")||b.createObjectStore("customTags",{keyPath:"tag"}).createIndex("usage","usage",{unique:!1})}})}async saveAudioFeedback(o,d,l,p){this.db||await this.initialize();const b=this.db.transaction(["audioFeedback"],"readwrite").objectStore("audioFeedback"),c={audioHash:o,originalTags:d,correctedTags:l,audioFeatures:p,timestamp:Date.now()};return new Promise((m,_)=>{const f=b.add(c);f.onsuccess=()=>m(f.result),f.onerror=()=>_(f.error)})}async saveTagFeedback(o,d,l){this.db||await this.initialize();const p=this.db.transaction(["tagFeedback"],"readwrite").objectStore("tagFeedback"),b={tag:o,feedback:d,audioHash:l,timestamp:Date.now()};return new Promise((c,m)=>{const _=p.add(b);_.onsuccess=()=>c(_.result),_.onerror=()=>m(_.error)})}async saveCustomTag(o){this.db||await this.initialize();const d=this.db.transaction(["customTags"],"readwrite").objectStore("customTags");return new Promise((l,p)=>{const b=d.get(o);b.onsuccess=()=>{const c=b.result,m=c?{...c,usage:c.usage+1}:{tag:o,usage:1,timestamp:Date.now()},_=d.put(m);_.onsuccess=()=>l(_.result),_.onerror=()=>p(_.error)},b.onerror=()=>p(b.error)})}async getCustomTags(o=20){this.db||await this.initialize();const d=this.db.transaction(["customTags"],"readonly").objectStore("customTags").index("usage");return new Promise((l,p)=>{const b=d.openCursor(null,"prev"),c=[];b.onsuccess=m=>{const _=m.target.result;_&&c.length<o?(c.push(_.value),_.continue()):l(c)},b.onerror=()=>p(b.error)})}async getTagFeedback(o=null){this.db||await this.initialize();const d=this.db.transaction(["tagFeedback"],"readonly").objectStore("tagFeedback");return new Promise((l,p)=>{let b;o?b=d.index("tag").getAll(o):b=d.getAll(),b.onsuccess=()=>l(b.result),b.onerror=()=>p(b.error)})}async getAudioFeedback(o=100){this.db||await this.initialize();const d=this.db.transaction(["audioFeedback"],"readonly").objectStore("audioFeedback").index("timestamp");return new Promise((l,p)=>{const b=d.openCursor(null,"prev"),c=[];b.onsuccess=m=>{const _=m.target.result;_&&c.length<o?(c.push(_.value),_.continue()):l(c)},b.onerror=()=>p(b.error)})}async hashAudioFile(o){const d=await o.arrayBuffer(),l=await crypto.subtle.digest("SHA-256",d);return Array.from(new Uint8Array(l)).map(p=>p.toString(16).padStart(2,"0")).join("").substring(0,16)}async clearAllData(){this.db||await this.initialize();const o=this.db.transaction(["audioFeedback","tagFeedback","customTags"],"readwrite");await Promise.all([new Promise((d,l)=>{const p=o.objectStore("audioFeedback").clear();p.onsuccess=()=>d(),p.onerror=()=>l(p.error)}),new Promise((d,l)=>{const p=o.objectStore("tagFeedback").clear();p.onsuccess=()=>d(),p.onerror=()=>l(p.error)}),new Promise((d,l)=>{const p=o.objectStore("customTags").clear();p.onsuccess=()=>d(),p.onerror=()=>l(p.error)})])}}class LocalClassifier{constructor(){this.weights=new Map,this.biases=new Map,this.learningRate=.01,this.featureDim=512,this.isInitialized=!1}initialize(o=512){this.featureDim=o,this.isInitialized=!0}trainOnFeedback(o,d,l){this.isInitialized||this.initialize();let p;switch(l){case"positive":p=1;break;case"negative":p=0;break;case"custom":p=1;break;default:return}this.weights.has(d)||(this.weights.set(d,new Array(this.featureDim).fill(0).map(()=>(Math.random()-.5)*.01)),this.biases.set(d,0));const b=this.weights.get(d),c=this.biases.get(d);let m=c;for(let f=0;f<o.length;f++)m+=b[f]*o[f];const _=1/(1+Math.exp(-m))-p;for(let f=0;f<o.length;f++)b[f]-=this.learningRate*_*o[f];this.biases.set(d,c-this.learningRate*_),this.weights.set(d,b)}predict(o,d){if(!this.weights.has(d))return null;const l=this.weights.get(d);let p=this.biases.get(d);for(let b=0;b<Math.min(o.length,l.length);b++)p+=l[b]*o[b];return 1/(1+Math.exp(-p))}predictAll(o,d){const l=[];for(const p of d){const b=this.predict(o,p);b!==null&&l.push({tag:p,confidence:b})}return l.sort((p,b)=>b.confidence-p.confidence)}retrainOnBatch(o){for(const d of o)if(d.audioFeatures&&d.correctedTags){const l=this.extractSimpleFeatures(d.audioFeatures);for(const p of d.correctedTags)this.trainOnFeedback(l,p.tag,p.feedback)}}extractSimpleFeatures(o){const d=new Array(this.featureDim).fill(0);if(o){d[0]=o.duration/60,d[1]=o.sampleRate/48e3,d[2]=o.numberOfChannels;const l=this.simpleHash(JSON.stringify(o));for(let p=3;p<this.featureDim;p++)d[p]=this.seededRandom(l+p)*.1}return d}simpleHash(o){let d=0;for(let l=0;l<o.length;l++){const p=o.charCodeAt(l);d=(d<<5)-d+p,d=d&d}return Math.abs(d)}seededRandom(o){const d=Math.sin(o)*1e4;return d-Math.floor(d)}saveModel(){const o={weights:Object.fromEntries(this.weights),biases:Object.fromEntries(this.biases),featureDim:this.featureDim,learningRate:this.learningRate};localStorage.setItem("clipTaggerModel",JSON.stringify(o))}loadModel(){const o=localStorage.getItem("clipTaggerModel");if(o)try{const d=JSON.parse(o);return this.weights=new Map(Object.entries(d.weights)),this.biases=new Map(Object.entries(d.biases)),this.featureDim=d.featureDim||512,this.learningRate=d.learningRate||.01,this.isInitialized=!0,!0}catch(d){console.error("Error loading model:",d)}return!1}getModelStats(){return{trainedTags:this.weights.size,featureDim:this.featureDim,learningRate:this.learningRate,tags:Array.from(this.weights.keys())}}clearModel(){this.weights.clear(),this.biases.clear(),localStorage.removeItem("clipTaggerModel")}}function App(){var v;const[o,d]=reactExports.useState(null),[l,p]=reactExports.useState(!1),[b,c]=reactExports.useState(!1),[m,_]=reactExports.useState([]),[f,u]=reactExports.useState(null),[n,e]=reactExports.useState([]),[a,s]=reactExports.useState(""),[g,y]=reactExports.useState(null),[x,E]=reactExports.useState(null),S=reactExports.useRef(null),P=reactExports.useRef(null),O=reactExports.useRef([]),k=reactExports.useRef(null),D=reactExports.useRef(null),C=reactExports.useRef(null);reactExports.useEffect(()=>{(async()=>(D.current=new UserFeedbackStore,await D.current.initialize(),C.current=new LocalClassifier,C.current.loadModel(),A()))()},[]);const A=async()=>{try{const re=await D.current.getCustomTags();e(re.map(ue=>ue.tag))}catch(re){console.error("Error loading custom tags:",re)}},$=re=>{const ue=re.target.files[0];ue&&ue.type.startsWith("audio/")&&(d(ue),se(ue))},W=re=>{re.preventDefault();const ue=re.dataTransfer.files[0];ue&&ue.type.startsWith("audio/")&&(d(ue),se(ue))},K=re=>{re.preventDefault()},Y=async()=>{try{const re=await navigator.mediaDevices.getUserMedia({audio:!0});P.current=new MediaRecorder(re),O.current=[],P.current.ondataavailable=ue=>{O.current.push(ue.data)},P.current.onstop=()=>{const ue=new Blob(O.current,{type:"audio/wav"}),_e=new File([ue],"recording.wav",{type:"audio/wav"});d(_e),se(_e),re.getTracks().forEach(ve=>ve.stop())},P.current.start(),p(!0)}catch(re){console.error("Error accessing microphone:",re)}},q=()=>{P.current&&l&&(P.current.stop(),p(!1))},se=async re=>{c(!0),_([]),u(null);try{k.current||(k.current=new CLAPProcessor);const ue=await D.current.hashAudioFile(re);y(ue);const _e=await k.current.fileToAudioBuffer(re),ve=await k.current.processAudio(_e),we={sampleRate:_e.sampleRate,duration:_e.duration,numberOfChannels:_e.numberOfChannels};E(we);let Ae=ve.map(Me=>({...Me,userFeedback:null}));if(C.current){const Me=C.current.extractSimpleFeatures(we),tt=[...ve.map(Ue=>Ue.label),...n],Ze=C.current.predictAll(Me,tt),ot=new Map;for(const Ue of ve)ot.set(Ue.label,{...Ue,source:"clap"});for(const Ue of Ze)if(ot.has(Ue.tag)){const Qe=ot.get(Ue.tag);Qe.confidence=(Qe.confidence+Ue.confidence)/2,Qe.source="blended"}else Ue.confidence>.6&&ot.set(Ue.tag,{label:Ue.tag,confidence:Ue.confidence,source:"local",userFeedback:null});Ae=Array.from(ot.values()).sort((Ue,Qe)=>Qe.confidence-Ue.confidence).slice(0,8)}_(Ae)}catch(ue){console.error("Error processing audio:",ue),u("Failed to process audio. Using fallback tags."),_([{label:"audio",confidence:.9,userFeedback:null},{label:"sound",confidence:.8,userFeedback:null},{label:"recording",confidence:.7,userFeedback:null}])}finally{c(!1)}},F=async(re,ue)=>{const _e=[...m];_e[re].userFeedback=ue,_(_e);try{if(await D.current.saveTagFeedback(_e[re].label,ue,g),C.current&&x){const ve=C.current.extractSimpleFeatures(x);C.current.trainOnFeedback(ve,_e[re].label,ue),C.current.saveModel()}}catch(ve){console.error("Error saving tag feedback:",ve)}},B=async()=>{if(!a.trim())return;const re={label:a.trim(),confidence:1,userFeedback:"custom",isCustom:!0,source:"custom"};_(ue=>[...ue,re]);try{if(await D.current.saveCustomTag(a.trim()),await D.current.saveTagFeedback(a.trim(),"custom",g),C.current&&x){const ue=C.current.extractSimpleFeatures(x);C.current.trainOnFeedback(ue,a.trim(),"custom"),C.current.saveModel()}A()}catch(ue){console.error("Error saving custom tag:",ue)}s("")},fe=re=>{re.key==="Enter"&&B()},ne=async()=>{var re;try{const ue=(re=C.current)==null?void 0:re.getModelStats(),_e=await D.current.getAudioFeedback(),ve=await D.current.getCustomTags(),we={modelStats:ue,feedbackData:_e.slice(0,50),customTags:ve,exportDate:new Date().toISOString(),version:"1.0"},Ae=new Blob([JSON.stringify(we,null,2)],{type:"application/json"}),Me=URL.createObjectURL(Ae),tt=document.createElement("a");tt.href=Me,tt.download=`clip-tagger-model-${Date.now()}.json`,document.body.appendChild(tt),tt.click(),document.body.removeChild(tt),URL.revokeObjectURL(Me)}catch(ue){console.error("Error exporting model:",ue),u("Failed to export model")}},z=()=>{if(m.length===0)return;const re={audioFile:(o==null?void 0:o.name)||"recorded-audio",audioHash:g,timestamp:new Date().toISOString(),tags:m.map(we=>({label:we.label,confidence:we.confidence,source:we.source||"clap",userFeedback:we.userFeedback}))},ue=new Blob([JSON.stringify(re,null,2)],{type:"application/json"}),_e=URL.createObjectURL(ue),ve=document.createElement("a");ve.href=_e,ve.download=`tags-${(o==null?void 0:o.name)||"audio"}-${Date.now()}.json`,document.body.appendChild(ve),ve.click(),document.body.removeChild(ve),URL.revokeObjectURL(_e)},Q=async()=>{var re;if(confirm("Are you sure you want to clear all training data? This cannot be undone."))try{await D.current.clearAllData(),(re=C.current)==null||re.clearModel(),e([]),_([]),d(null),u(null)}catch(ue){console.error("Error clearing data:",ue),u("Failed to clear data")}};return jsxRuntimeExports.jsxs("div",{className:"app",children:[jsxRuntimeExports.jsxs("header",{children:[jsxRuntimeExports.jsx("h1",{children:"🎵 clip-tagger"}),jsxRuntimeExports.jsx("p",{children:"Custom audio tagging in the browser"})]}),jsxRuntimeExports.jsxs("main",{children:[jsxRuntimeExports.jsxs("div",{className:"upload-area",onDrop:W,onDragOver:K,onClick:()=>{var re;return(re=S.current)==null?void 0:re.click()},children:[jsxRuntimeExports.jsx("input",{ref:S,type:"file",accept:"audio/*",onChange:$,hidden:!0}),jsxRuntimeExports.jsx("div",{className:"upload-content",children:o?jsxRuntimeExports.jsxs("div",{children:[jsxRuntimeExports.jsxs("p",{children:["📁 ",o.name]}),jsxRuntimeExports.jsx("audio",{controls:!0,src:URL.createObjectURL(o)})]}):jsxRuntimeExports.jsxs("div",{children:[jsxRuntimeExports.jsx("p",{children:"🎵 Drop an audio file here or click to upload"}),jsxRuntimeExports.jsx("p",{children:"Supports WAV, MP3, and other audio formats"})]})})]}),jsxRuntimeExports.jsx("div",{className:"controls",children:jsxRuntimeExports.jsx("button",{onClick:l?q:Y,className:l?"recording":"",children:l?"⏹️ Stop Recording":"🎤 Record Audio"})}),b&&jsxRuntimeExports.jsx("div",{className:"loading",children:jsxRuntimeExports.jsx("p",{children:"🧠 Analyzing audio with CLAP model..."})}),f&&jsxRuntimeExports.jsx("div",{className:"error",children:jsxRuntimeExports.jsxs("p",{children:["⚠️ ",f]})}),m.length>0&&jsxRuntimeExports.jsxs("div",{className:"tags-section",children:[jsxRuntimeExports.jsx("h3",{children:"Generated Tags"}),jsxRuntimeExports.jsx("div",{className:"tags",children:m.map((re,ue)=>jsxRuntimeExports.jsxs("div",{className:`tag-item ${re.userFeedback?"has-feedback":""}`,children:[jsxRuntimeExports.jsxs("span",{className:`tag ${re.isCustom?"custom":""} ${re.userFeedback==="negative"?"negative":""} ${re.source||"clap"}`,children:[re.label," (",Math.round(re.confidence*100),"%)",re.source==="local"&&jsxRuntimeExports.jsx("span",{className:"source-indicator",children:"🧠"}),re.source==="blended"&&jsxRuntimeExports.jsx("span",{className:"source-indicator",children:"⚡"}),re.source==="custom"&&jsxRuntimeExports.jsx("span",{className:"source-indicator",children:"✨"})]}),!re.isCustom&&jsxRuntimeExports.jsxs("div",{className:"tag-controls",children:[jsxRuntimeExports.jsx("button",{onClick:()=>F(ue,"positive"),className:`feedback-btn ${re.userFeedback==="positive"?"active":""}`,title:"Good tag",children:"✓"}),jsxRuntimeExports.jsx("button",{onClick:()=>F(ue,"negative"),className:`feedback-btn ${re.userFeedback==="negative"?"active":""}`,title:"Bad tag",children:"✗"})]})]},ue))}),jsxRuntimeExports.jsxs("div",{className:"add-tag",children:[jsxRuntimeExports.jsx("input",{type:"text",value:a,onChange:re=>s(re.target.value),onKeyPress:fe,placeholder:"Add custom tag...",className:"tag-input"}),jsxRuntimeExports.jsx("button",{onClick:B,className:"add-tag-btn",children:"Add Tag"})]}),n.length>0&&jsxRuntimeExports.jsxs("div",{className:"frequent-tags",children:[jsxRuntimeExports.jsx("h4",{children:"Frequent Tags:"}),jsxRuntimeExports.jsx("div",{className:"frequent-tag-list",children:n.slice(0,10).map((re,ue)=>jsxRuntimeExports.jsx("button",{onClick:()=>s(re),className:"frequent-tag",children:re},ue))})]})]}),(m.length>0||n.length>0)&&jsxRuntimeExports.jsxs("div",{className:"export-section",children:[jsxRuntimeExports.jsx("h3",{children:"Export & Management"}),jsxRuntimeExports.jsxs("div",{className:"export-controls",children:[m.length>0&&jsxRuntimeExports.jsx("button",{onClick:z,className:"export-btn",children:"📁 Export Current Tags"}),((v=C.current)==null?void 0:v.getModelStats().trainedTags)>0&&jsxRuntimeExports.jsx("button",{onClick:ne,className:"export-btn",children:"🧠 Export Trained Model"}),jsxRuntimeExports.jsx("button",{onClick:Q,className:"clear-btn",children:"🗑️ Clear All Data"})]}),C.current&&jsxRuntimeExports.jsxs("div",{className:"model-stats",children:[jsxRuntimeExports.jsxs("p",{children:["Trained tags: ",C.current.getModelStats().trainedTags]}),jsxRuntimeExports.jsxs("p",{children:["Custom tags: ",n.length]})]})]})]}),jsxRuntimeExports.jsx("footer",{children:jsxRuntimeExports.jsxs("p",{children:["Powered by ",jsxRuntimeExports.jsx("a",{href:"https://github.com/xenova/transformers.js",target:"_blank",rel:"noopener",children:"Transformers.js"})," "," • CLAP model: ",jsxRuntimeExports.jsx("a",{href:"https://huggingface.co/Xenova/clap-htsat-unfused",target:"_blank",rel:"noopener",children:"Xenova/clap-htsat-unfused"})," "," • Everything runs locally in your browser"]})})]})}clientExports.createRoot(document.getElementById("root")).render(jsxRuntimeExports.jsx(reactExports.StrictMode,{children:jsxRuntimeExports.jsx(App,{})}));