transformers-fork
Version:
State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
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JavaScript
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b{type="NullLiteral"},F=class extends b{type="ArrayLiteral"},v=class extends b{type="TupleLiteral"},C=class extends b{type="ObjectLiteral"},S=class extends g{constructor(e,t,s){super(),this.operator=e,this.left=t,this.right=s}type="BinaryExpression"},A=class extends g{constructor(e,t){super(),this.operand=e,this.filter=t}type="FilterExpression"},E=class extends g{constructor(e,t){super(),this.iterable=e,this.test=t}type="SelectExpression"},L=class extends g{constructor(e,t,s){super(),this.operand=e,this.negate=t,this.test=s}type="TestExpression"},I=class extends g{constructor(e,t){super(),this.operator=e,this.argument=t}type="UnaryExpression"},z=class extends g{constructor(e=void 0,t=void 0,s=void 0){super(),this.start=e,this.stop=t,this.step=s}type="SliceExpression"},j=class extends g{constructor(e,t){super(),this.key=e,this.value=t}type="KeywordArgumentExpression"};function N(e){const t=new p([]);let s=0;function o(t,r){const o=e[s++];if(!o||o.type!==t)throw new Error(`Parser Error: 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s+t.length<=e.length&&t.every(((t,r)=>t===e[s+r].type))}function l(){const e=u();if(i(r.Equals)){++s;const t=l();return new h(e,t)}return e}function c(){const t=u();o(r.CloseStatement,"Expected closing statement token");const a=[],l=[];for(;e[s]?.type!==r.OpenStatement||e[s+1]?.type!==r.ElseIf&&e[s+1]?.type!==r.Else&&e[s+1]?.type!==r.EndIf;)a.push(n());if(e[s]?.type===r.OpenStatement&&e[s+1]?.type!==r.EndIf)if(++s,i(r.ElseIf))o(r.ElseIf,"Expected elseif token"),l.push(c());else for(o(r.Else,"Expected else token"),o(r.CloseStatement,"Expected closing statement token");e[s]?.type!==r.OpenStatement||e[s+1]?.type!==r.EndIf;)l.push(n());return new m(t,a,l)}function d(e=!1){const t=e?$:u,o=[t()],n=i(r.Comma);for(;n&&(++s,o.push(t()),i(r.Comma)););return n?new v(o):o[0]}function u(){return function(){const e=g();if(i(r.If)){++s;const t=g();if(i(r.Else)){++s;const r=g();return new m(t,[e],[r])}return new E(e,t)}return e}()}function g(){let t=b();for(;i(r.Or);){const r=e[s];++s;const o=b();t=new S(r,t,o)}return t}function b(){let t=N();for(;i(r.And);){const r=e[s];++s;const o=N();t=new S(r,t,o)}return t}function N(){let t;for(;i(r.Not);){const r=e[s];++s;const o=N();t=new I(r,o)}return t??function(){let t=V();for(;i(r.ComparisonBinaryOperator)||i(r.In)||i(r.NotIn);){const r=e[s];++s;const o=V();t=new S(r,t,o)}return t}()}function V(){let t=R();for(;i(r.AdditiveBinaryOperator);){const r=e[s];++s;const o=R();t=new S(r,t,o)}return t}function O(){const t=function(){let t=$();for(;i(r.Dot)||i(r.OpenSquareBracket);){const n=e[s];let a;++s;const i=n.type!==r.Dot;if(i)a=G(),o(r.CloseSquareBracket,"Expected closing square bracket");else if(a=$(),"Identifier"!==a.type)throw new SyntaxError("Expected identifier following dot operator");t=new M(t,a,i)}return t}();return i(r.OpenParen)?B(t):t}function B(e){let t=new w(e,D());return i(r.OpenParen)&&(t=B(t)),t}function D(){o(r.OpenParen,"Expected opening parenthesis for arguments list");const e=function(){const 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Map([["namespace",new X((e=>{if(0===e.length)return new $(new Map);if(1!==e.length||!(e[0]instanceof $))throw new Error("`namespace` expects either zero arguments or a single object argument");return e[0]}))]]);tests=new Map([["boolean",e=>"BooleanValue"===e.type],["callable",e=>e instanceof X],["odd",e=>{if("NumericValue"!==e.type)throw new Error(`Cannot apply test "odd" to type: ${e.type}`);return e.value%2!=0}],["even",e=>{if("NumericValue"!==e.type)throw new Error(`Cannot apply test "even" to type: ${e.type}`);return e.value%2==0}],["false",e=>"BooleanValue"===e.type&&!e.value],["true",e=>"BooleanValue"===e.type&&e.value],["none",e=>"NullValue"===e.type],["string",e=>"StringValue"===e.type],["number",e=>"NumericValue"===e.type],["integer",e=>"NumericValue"===e.type&&Number.isInteger(e.value)],["iterable",e=>"ArrayValue"===e.type||"StringValue"===e.type],["mapping",e=>"ObjectValue"===e.type],["lower",e=>{const t=e.value;return"StringValue"===e.type&&t===t.toLowerCase()}],["upper",e=>{const t=e.value;return"StringValue"===e.type&&t===t.toUpperCase()}],["none",e=>"NullValue"===e.type],["defined",e=>"UndefinedValue"!==e.type],["undefined",e=>"UndefinedValue"===e.type],["equalto",(e,t)=>e.value===t.value],["eq",(e,t)=>e.value===t.value]]);set(e,t){return this.declareVariable(e,Z(t))}declareVariable(e,t){if(this.variables.has(e))throw new SyntaxError(`Variable already declared: ${e}`);return this.variables.set(e,t),t}setVariable(e,t){return this.variables.set(e,t),t}resolve(e){if(this.variables.has(e))return this;if(this.parent)return this.parent.resolve(e);throw new Error(`Unknown variable: ${e}`)}lookupVariable(e){try{return this.resolve(e).variables.get(e)??new J}catch{return new J}}},K=class{global;constructor(e){this.global=e??new Y}run(e){return this.evaluate(e,this.global)}evaluateBinaryExpression(e,t){const s=this.evaluate(e.left,t);switch(e.operator.value){case"and":return 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0!==r.value.find((e=>e.value===s.value));switch(e.operator.value){case"in":return new q(t);case"not in":return new q(!t)}}if((s instanceof R||r instanceof R)&&"+"===e.operator.value)return new R(s.value.toString()+r.value.toString());if(s instanceof R&&r instanceof R)switch(e.operator.value){case"in":return new q(r.value.includes(s.value));case"not in":return new q(!r.value.includes(s.value))}if(s instanceof R&&r instanceof $)switch(e.operator.value){case"in":return new q(r.value.has(s.value));case"not in":return new q(!r.value.has(s.value))}throw new SyntaxError(`Unknown operator "${e.operator.value}" between ${s.type} and ${r.type}`)}evaluateArguments(e,t){const s=[],r=new Map;for(const o of e)if("KeywordArgumentExpression"===o.type){const e=o;r.set(e.key.value,this.evaluate(e.value,t))}else{if(r.size>0)throw new Error("Positional arguments must come before keyword arguments");s.push(this.evaluate(o,t))}return[s,r]}evaluateFilterExpression(e,t){const s=this.evaluate(e.operand,t);if("Identifier"===e.filter.type){const t=e.filter;if("tojson"===t.value)return new R(ee(s));if(s instanceof U)switch(t.value){case"list":return s;case"first":return s.value[0];case"last":return s.value[s.value.length-1];case"length":return new G(s.value.length);case"reverse":return new U(s.value.reverse());case"sort":return new U(s.value.sort(((e,t)=>{if(e.type!==t.type)throw new Error(`Cannot compare different types: ${e.type} and ${t.type}`);switch(e.type){case"NumericValue":return e.value-t.value;case"StringValue":return e.value.localeCompare(t.value);default:throw new Error(`Cannot compare type: ${e.type}`)}})));default:throw new Error(`Unknown ArrayValue filter: ${t.value}`)}else if(s instanceof R)switch(t.value){case"length":return new G(s.value.length);case"upper":return new R(s.value.toUpperCase());case"lower":return new R(s.value.toLowerCase());case"title":return new R(B(s.value));case"capitalize":return new 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Error("Tensor format doesn't match input tensor dims");const p=4;let m=0,_=1,h=2,f=3,g=0,M=u,w=2*u,T=-1;"RGBA"===i?(g=0,M=u,w=2*u,T=3*u):"RGB"===i?(g=0,M=u,w=2*u):"RBG"===i&&(g=0,w=u,M=2*u),r=s.createImageData(o,n);for(let t=0;t<n*o;m+=p,_+=p,h+=p,f+=p,t++)r.data[m]=(e.data[g++]-d[0])*c[0],r.data[_]=(e.data[M++]-d[1])*c[1],r.data[h]=(e.data[w++]-d[2])*c[2],r.data[f]=-1===T?255:(e.data[T++]-d[3])*c[3]}return r}},"./node_modules/onnxruntime-common/dist/esm/tensor-conversion.js":(e,t,s)=>{s.r(t)},"./node_modules/onnxruntime-common/dist/esm/tensor-factory-impl.js":(e,t,s)=>{s.r(t),s.d(t,{bufferToTensor:()=>o,tensorFromGpuBuffer:()=>i,tensorFromImage:()=>n,tensorFromMLTensor:()=>l,tensorFromPinnedBuffer:()=>c,tensorFromTexture:()=>a});var r=s("./node_modules/onnxruntime-common/dist/esm/tensor-impl.js");const o=(e,t)=>{if(void 0===e)throw new Error("Image buffer must be defined");if(void 0===t.height||void 0===t.width)throw new Error("Image height and width must be defined");if("NHWC"===t.tensorLayout)throw new Error("NHWC Tensor layout is not supported yet");const{height:s,width:o}=t,n=t.norm??{mean:255,bias:0};let a,i;a="number"==typeof n.mean?[n.mean,n.mean,n.mean,n.mean]:[n.mean[0],n.mean[1],n.mean[2],n.mean[3]??255],i="number"==typeof n.bias?[n.bias,n.bias,n.bias,n.bias]:[n.bias[0],n.bias[1],n.bias[2],n.bias[3]??0];const l=void 0!==t.format?t.format:"RGBA",c=void 0!==t.tensorFormat&&void 0!==t.tensorFormat?t.tensorFormat:"RGB",d=s*o,u="RGBA"===c?new Float32Array(4*d):new Float32Array(3*d);let p=4,m=0,_=1,h=2,f=3,g=0,M=d,w=2*d,T=-1;"RGB"===l&&(p=3,m=0,_=1,h=2,f=-1),"RGBA"===c?T=3*d:"RBG"===c?(g=0,w=d,M=2*d):"BGR"===c&&(w=0,M=d,g=2*d);for(let t=0;t<d;t++,m+=p,h+=p,_+=p,f+=p)u[g++]=(e[m]+i[0])/a[0],u[M++]=(e[_]+i[1])/a[1],u[w++]=(e[h]+i[2])/a[2],-1!==T&&-1!==f&&(u[T++]=(e[f]+i[3])/a[3]);return"RGBA"===c?new r.Tensor("float32",u,[1,4,s,o]):new r.Tensor("float32",u,[1,3,s,o])},n=async(e,t)=>{const s="undefined"!=typeof HTMLImageElement&&e instanceof HTMLImageElement,r="undefined"!=typeof ImageData&&e instanceof ImageData,n="undefined"!=typeof ImageBitmap&&e instanceof ImageBitmap,a="string"==typeof e;let i,l=t??{};const c=()=>{if("undefined"!=typeof document)return document.createElement("canvas");if("undefined"!=typeof OffscreenCanvas)return new OffscreenCanvas(1,1);throw new Error("Canvas is not supported")},d=e=>"undefined"!=typeof HTMLCanvasElement&&e instanceof HTMLCanvasElement||e instanceof OffscreenCanvas?e.getContext("2d"):null;if(s){const s=c();s.width=e.width,s.height=e.height;const r=d(s);if(null==r)throw new Error("Can not access image data");{let s=e.height,o=e.width;if(void 0!==t&&void 0!==t.resizedHeight&&void 0!==t.resizedWidth&&(s=t.resizedHeight,o=t.resizedWidth),void 0!==t){if(l=t,void 0!==t.tensorFormat)throw new Error("Image input config format must be RGBA for HTMLImageElement");l.tensorFormat="RGBA",l.height=s,l.width=o}else l.tensorFormat="RGBA",l.height=s,l.width=o;r.drawImage(e,0,0),i=r.getImageData(0,0,o,s).data}}else{if(!r){if(n){if(void 0===t)throw new Error("Please provide image config with format for Imagebitmap");const s=c();s.width=e.width,s.height=e.height;const r=d(s);if(null!=r){const t=e.height,s=e.width;return r.drawImage(e,0,0,s,t),i=r.getImageData(0,0,s,t).data,l.height=t,l.width=s,o(i,l)}throw new Error("Can not access image data")}if(a)return new Promise(((t,s)=>{const r=c(),n=d(r);if(!e||!n)return s();const a=new Image;a.crossOrigin="Anonymous",a.src=e,a.onload=()=>{r.width=a.width,r.height=a.height,n.drawImage(a,0,0,r.width,r.height);const e=n.getImageData(0,0,r.width,r.height);l.height=r.height,l.width=r.width,t(o(e.data,l))}}));throw new Error("Input data provided is not supported - aborted tensor creation")}{let s,r;if(void 0!==t&&void 0!==t.resizedWidth&&void 0!==t.resizedHeight?(s=t.resizedHeight,r=t.resizedWidth):(s=e.height,r=e.width),void 0!==t&&(l=t),l.format="RGBA",l.height=s,l.width=r,void 0!==t){const t=c();t.width=r,t.height=s;const o=d(t);if(null==o)throw new Error("Can not access image data");o.putImageData(e,0,0),i=o.getImageData(0,0,r,s).data}else i=e.data}}if(void 0!==i)return o(i,l);throw new Error("Input data provided is not supported - aborted tensor creation")},a=(e,t)=>{const{width:s,height:o,download:n,dispose:a}=t,i=[1,o,s,4];return new r.Tensor({location:"texture",type:"float32",texture:e,dims:i,download:n,dispose:a})},i=(e,t)=>{const{dataType:s,dims:o,download:n,dispose:a}=t;return new r.Tensor({location:"gpu-buffer",type:s??"float32",gpuBuffer:e,dims:o,download:n,dispose:a})},l=(e,t)=>{const{dataType:s,dims:o,download:n,dispose:a}=t;return new r.Tensor({location:"ml-tensor",type:s??"float32",mlTensor:e,dims:o,download:n,dispose:a})},c=(e,t,s)=>new r.Tensor({location:"cpu-pinned",type:e,data:t,dims:s??[t.length]})},"./node_modules/onnxruntime-common/dist/esm/tensor-factory.js":(e,t,s)=>{s.r(t)},"./node_modules/onnxruntime-common/dist/esm/tensor-impl-type-mapping.js":(e,t,s)=>{s.r(t),s.d(t,{NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP:()=>o,NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP:()=>r,checkTypedArray:()=>a});const r=new Map([["float32",Float32Array],["uint8",Uint8Array],["int8",Int8Array],["uint16",Uint16Array],["int16",Int16Array],["int32",Int32Array],["bool",Uint8Array],["float64",Float64Array],["uint32",Uint32Array],["int4",Uint8Array],["uint4",Uint8Array]]),o=new Map([[Float32Array,"float32"],[Uint8Array,"uint8"],[Int8Array,"int8"],[Uint16Array,"uint16"],[Int16Array,"int16"],[Int32Array,"int32"],[Float64Array,"float64"],[Uint32Array,"uint32"]]);let n=!1;const a=()=>{if(!n){n=!0;const e="undefined"!=typeof BigInt64Array&&BigInt64Array.from,t="undefined"!=typeof BigUint64Array&&BigUint64Array.from,s="undefined"!=typeof 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instanceof t))throw new TypeError(`buffer should be of type ${t.name}`);this.cpuData=e.data;break}case"texture":if("float32"!==r)throw new TypeError(`unsupported type "${r}" to create tensor from texture`);this.gpuTextureData=e.texture,this.downloader=e.download,this.disposer=e.dispose;break;case"gpu-buffer":if("float32"!==r&&"float16"!==r&&"int32"!==r&&"int64"!==r&&"uint32"!==r&&"uint8"!==r&&"bool"!==r&&"uint4"!==r&&"int4"!==r)throw new TypeError(`unsupported type "${r}" to create tensor from gpu buffer`);this.gpuBufferData=e.gpuBuffer,this.downloader=e.download,this.disposer=e.dispose;break;case"ml-tensor":if("float32"!==r&&"float16"!==r&&"int32"!==r&&"int64"!==r&&"uint32"!==r&&"uint64"!==r&&"int8"!==r&&"uint8"!==r&&"bool"!==r)throw new TypeError(`unsupported type "${r}" to create tensor from MLTensor`);this.mlTensorData=e.mlTensor,this.downloader=e.download,this.disposer=e.dispose;break;default:throw new Error(`Tensor constructor: unsupported location '${this.dataLocation}'`)}else{let a,i;if("string"==typeof e)if(r=e,i=s,"string"===e){if(!Array.isArray(t))throw new TypeError("A string tensor's data must be a string array.");a=t}else{const s=n.NUMERIC_TENSOR_TYPE_TO_TYPEDARRAY_MAP.get(e);if(void 0===s)throw new TypeError(`Unsupported tensor type: ${e}.`);if(Array.isArray(t)){if("float16"===e&&s===Uint16Array||"uint4"===e||"int4"===e)throw new TypeError(`Creating a ${e} tensor from number array is not supported. Please use ${s.name} as data.`);a="uint64"===e||"int64"===e?s.from(t,BigInt):s.from(t)}else if(t instanceof s)a=t;else{if(!(t instanceof Uint8ClampedArray))throw new TypeError(`A ${r} tensor's data must be type of ${s}`);if("uint8"!==e)throw new TypeError("A Uint8ClampedArray tensor's data must be type of uint8");a=Uint8Array.from(t)}}else if(i=t,Array.isArray(e)){if(0===e.length)throw new TypeError("Tensor type cannot be inferred from an empty array.");const t=typeof e[0];if("string"===t)r="string",a=e;else{if("boolean"!==t)throw new TypeError(`Invalid element type of data array: ${t}.`);r="bool",a=Uint8Array.from(e)}}else if(e instanceof Uint8ClampedArray)r="uint8",a=Uint8Array.from(e);else{const t=n.NUMERIC_TENSOR_TYPEDARRAY_TO_TYPE_MAP.get(e.constructor);if(void 0===t)throw new TypeError(`Unsupported type for tensor data: ${e.constructor}.`);r=t,a=e}if(void 0===i)i=[a.length];else if(!Array.isArray(i))throw new TypeError("A tensor's dims must be a number array");o=i,this.cpuData=a,this.dataLocation="cpu"}const i=(0,a.calculateSize)(o);if(this.cpuData&&i!==this.cpuData.length&&("uint4"!==r&&"int4"!==r||Math.ceil(i/2)!==this.cpuData.length))throw new Error(`Tensor's size(${i}) does not match data length(${this.cpuData.length}).`);this.type=r,this.dims=o,this.size=i}static async fromImage(e,t){return(0,o.tensorFromImage)(e,t)}static fromTexture(e,t){return(0,o.tensorFromTexture)(e,t)}static fromGpuBuffer(e,t){return(0,o.tensorFromGpuBuffer)(e,t)}static fromMLTensor(e,t){return(0,o.tensorFromMLTensor)(e,t)}static fromPinnedBuffer(e,t,s){return(0,o.tensorFromPinnedBuffer)(e,t,s)}toDataURL(e){return(0,r.tensorToDataURL)(this,e)}toImageData(e){return(0,r.tensorToImageData)(this,e)}get data(){if(this.ensureValid(),!this.cpuData)throw new Error("The data is not on CPU. Use `getData()` to download GPU data to CPU, or use `texture` or `gpuBuffer` property to access the GPU data directly.");return this.cpuData}get location(){return this.dataLocation}get texture(){if(this.ensureValid(),!this.gpuTextureData)throw new Error("The data is not stored as a WebGL texture.");return this.gpuTextureData}get gpuBuffer(){if(this.ensureValid(),!this.gpuBufferData)throw new Error("The data is not stored as a WebGPU buffer.");return this.gpuBufferData}get mlTensor(){if(this.ensureValid(),!this.mlTensorData)throw new Error("The data is not stored as a WebNN MLTensor.");return this.mlTensorData}async getData(e){switch(this.ensureValid(),this.dataLocation){case"cpu":case"cpu-pinned":return this.data;case"texture":case"gpu-buffer":