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 * @author   Feross Aboukhadijeh <https://feross.org>
 * @license  MIT
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RawImage(e.data,e.dims[1],e.dims[0],e.dims[2]);default:throw Error(`Unsupported number of channels: ${e.dims[2]}`)}}grayscale(){if(1===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let t=0,n=0;t<this.data.length;t+=this.channels){let i=this.data[t],s=this.data[t+1],o=this.data[t+2];e[n++]=Math.round(.2989*i+.587*s+.114*o)}break;default:throw Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,1)}rgb(){if(3===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let t=0,n=0;t<this.data.length;++t)e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=this.data[t];break;case 4:for(let t=0,n=0;t<this.data.length;t+=4)e[n++]=this.data[t],e[n++]=this.data[t+1],e[n++]=this.data[t+2];break;default:throw Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,3)}rgba(){if(4===this.channels)return this;let e=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let t=0,n=0;t<this.data.length;++t)e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=this.data[t],e[n++]=255;break;case 3:for(let t=0,n=0;t<this.data.length;t+=3)e[n++]=this.data[t],e[n++]=this.data[t+1],e[n++]=this.data[t+2],e[n++]=255;break;default:throw Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(e,this.width,this.height,4)}async resize(e,t,{resample:n=2}={}){let s=b[n]??n;if(y){let n=this.channels,s=this.toCanvas(),o=i(e,t).getContext("2d");return o.drawImage(s,0,0,e,t),new RawImage(o.getImageData(0,0,e,t).data,e,t,4).convert(n)}{let n=this.toSharp();switch(s){case"box":case"hamming":("box"===s||"hamming"===s)&&(console.warn(`Resampling method ${s} is not yet supported. Using bilinear instead.`),s="bilinear");case"nearest":case"bilinear":case"bicubic":n=n.affine([e/this.width,0,0,t/this.height],{interpolator:s});break;case"lanczos":n=n.resize({width:e,height:t,fit:"fill",kernel:"lanczos3"});break;default:throw Error(`Resampling method ${s} is not supported.`)}return await o(n)}}async pad([e,t,n,s]){if(e=Math.max(e,0),t=Math.max(t,0),n=Math.max(n,0),s=Math.max(s,0),0===e&&0===t&&0===n&&0===s)return this;if(y){let o=this.channels,a=this.toCanvas(),u=this.width+e+t,c=this.height+n+s,f=i(u,c).getContext("2d");return f.drawImage(a,0,0,this.width,this.height,e,n,u,c),new RawImage(f.getImageData(0,0,u,c).data,u,c,4).convert(o)}{let i=this.toSharp().extend({left:e,right:t,top:n,bottom:s});return await o(i)}}async crop([e,t,n,s]){if(e=Math.max(e,0),t=Math.max(t,0),n=Math.min(n,this.width-1),s=Math.min(s,this.height-1),0===e&&0===t&&n===this.width-1&&s===this.height-1)return this;let a=n-e+1,u=s-t+1;if(y){let n=this.channels,s=this.toCanvas(),o=i(a,u).getContext("2d");o.drawImage(s,e,t,a,u,0,0,a,u);let c=new RawImage(o.getImageData(0,0,a,u).data,a,u,4);return c.convert(n)}{let n=this.toSharp().extract({left:e,top:t,width:a,height:u});return await o(n)}}async center_crop(e,t){if(this.width===e&&this.height===t)return this;let n=(this.width-e)/2,s=(this.height-t)/2;if(y){let o=this.channels,a=this.toCanvas(),u=i(e,t).getContext("2d"),c=0,f=0,p=0,m=0;return n>=0?c=n:p=-n,s>=0?f=s:m=-s,u.drawImage(a,c,f,e,t,p,m,e,t),new RawImage(u.getImageData(0,0,e,t).data,e,t,4).convert(o)}{let i=this.toSharp();if(n>=0&&s>=0)i=i.extract({left:Math.floor(n),top:Math.floor(s),width:e,height:t});else if(n<=0&&s<=0){let o=Math.floor(-s),a=Math.floor(-n);i=i.extend({top:o,left:a,right:e-this.width-a,bottom:t-this.height-o})}else{let o=[0,0],a=0;s<0?(o[0]=Math.floor(-s),o[1]=t-this.height-o[0]):a=Math.floor(s);let u=[0,0],c=0;n<0?(u[0]=Math.floor(-n),u[1]=e-this.width-u[0]):c=Math.floor(n),i=i.extend({top:o[0],bottom:o[1],left:u[0],right:u[1]}).extract({left:c,top:a,width:e,height:t})}return await o(i)}}async toBlob(e="image/png",t=1){if(!y)throw Error("toBlob() is only supported in browser environments.");let n=this.toCanvas();return await n.convertToBlob({type:e,quality:t})}toCanvas(){if(!y)throw Error("toCanvas() is only supported in browser environments.");let e=this.clone().rgba(),t=i(e.width,e.height),n=new s(e.data,e.width,e.height);return t.getContext("2d").putImageData(n,0,0),t}_update(e,t,n,i=null){return this.data=e,this.width=t,this.height=n,null!==i&&(this.channels=i),this}clone(){return new RawImage(this.data.slice(),this.width,this.height,this.channels)}convert(e){if(this.channels===e)return this;switch(e){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(e){if(y){if(w)throw Error("Unable to save an image from a Web Worker.");let t=e.split(".").pop().toLowerCase(),n=v.get(t)??"image/png",i=await this.toBlob(n),s=URL.createObjectURL(i),o=document.createElement("a");o.href=s,o.download=e,o.click(),o.remove()}else if(g.O.useFS){let t=this.toSharp();return await t.toFile(e)}else throw Error("Unable to save the image because filesystem is disabled in this environment.")}toSharp(){if(y)throw Error("toSharp() is only supported in server-side environments.");return _(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}};async function read_audio(e,t){let n;if("undefined"==typeof AudioContext)throw Error("Unable to load audio from path/URL since `AudioContext` is not available in your environment. Instead, audio data should be passed directly to the pipeline/processor. For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");let i=await (await (0,f.hn)(e)).arrayBuffer(),s=new AudioContext({sampleRate:t});void 0===t&&console.warn(`No sampling rate provided, using default of ${s.sampleRate}Hz.`);let o=await s.decodeAudioData(i);if(2===o.numberOfChannels){let e=Math.sqrt(2),t=o.getChannelData(0),i=o.getChannelData(1);n=new Float32Array(t.length);for(let s=0;s<o.length;++s)n[s]=e*(t[s]+i[s])/2}else n=o.getChannelData(0);return n}let x={htk:e=>2595*Math.log10(1+e/700),kaldi:e=>1127*Math.log(1+e/700),slaney:(e,t=1e3,n=15,i=27/Math.log(6.4))=>e>=t?n+Math.log(e/t)*i:3*e/200};function hertz_to_mel(e,t="htk"){let n=x[t];if(!n)throw Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof e?n(e):e.map(e=>n(e))}let E={htk:e=>700*(10**(e/2595)-1),kaldi:e=>700*(Math.exp(e/1127)-1),slaney:(e,t=1e3,n=15,i=Math.log(6.4)/27)=>e>=n?t*Math.exp(i*(e-n)):200*e/3};function linspace(e,t,n){let i=(t-e)/(n-1);return Float64Array.from({length:n},(t,n)=>e+i*n)}function mel_filter_bank(e,t,n,i,s,o=null,a="htk",u=!1){let c;if(null!==o&&"slaney"!==o)throw Error('norm must be one of null or "slaney"');let f=hertz_to_mel(n,a),p=hertz_to_mel(i,a),m=linspace(f,p,t+2),g=function(e,t="htk"){let n=E[t];if(!n)throw Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof e?n(e):e.map(e=>n(e))}(m,a);if(u){let t=s/(2*e);c=hertz_to_mel(Float64Array.from({length:e},(e,n)=>n*t),a),g=m}else c=linspace(0,Math.floor(s/2),e);let _=function(e,t){let n=Float64Array.from({length:t.length-1},(e,n)=>t[n+1]-t[n]),i=Array.from({length:e.length},()=>Array(t.length));for(let n=0;n<e.length;++n){let s=i[n];for(let i=0;i<t.length;++i)s[i]=t[i]-e[n]}let s=t.length-2,o=Array.from({length:s},()=>Array(e.length));for(let t=0;t<e.length;++t){let e=i[t];for(let i=0;i<s;++i){let s=-e[i]/n[i],a=e[i+2]/n[i+1];o[i][t]=Math.max(0,Math.min(s,a))}}return o}(c,g);if(null!==o&&"slaney"===o)for(let n=0;n<t;++n){let t=_[n],i=2/(g[n+2]-g[n]);for(let n=0;n<e;++n)t[n]*=i}return _}function _db_conversion_helper(e,t,n,i,s){if(n<=0)throw Error("reference must be greater than zero");if(i<=0)throw Error("min_value must be greater than zero");n=Math.max(i,n);let o=Math.log10(n);for(let n=0;n<e.length;++n)e[n]=t*Math.log10(Math.max(i,e[n])-o);if(null!==s){if(s<=0)throw Error("db_range must be greater than zero");let t=(0,p.Fp)(e)[0]-s;for(let n=0;n<e.length;++n)e[n]=Math.max(e[n],t)}return e}function spectrogram(e,t,n,i,{fft_length:s=null,power:o=1,center:a=!0,pad_mode:u="reflect",onesided:f=!0,preemphasis:m=null,mel_filters:g=null,mel_floor:_=1e-10,log_mel:y=null,reference:w=1,min_value:b=1e-10,db_range:v=null,remove_dc_offset:x=null,max_num_frames:E=null,do_pad:A=!0,transpose:k=!1}={}){let B=t.length;if(null===s&&(s=n),n>s)throw Error(`frame_length (${n}) may not be larger than fft_length (${s})`);if(B!==n)throw Error(`Length of the window (${B}) must equal frame_length (${n})`);if(i<=0)throw Error("hop_length must be greater than zero");if(a){if("reflect"!==u)throw Error(`pad_mode="${u}" not implemented yet.`);let t=Math.floor((s-1)/2)+1;e=function(e,t,n){let i=new e.constructor(e.length+t+n),s=e.length-1;for(let n=0;n<e.length;++n)i[t+n]=e[n];for(let n=1;n<=t;++n)i[t-n]=e[(0,c.hs)(n,s)];for(let o=1;o<=n;++o)i[s+t+o]=e[(0,c.hs)(s-o,s)];return i}(e,t,t)}let I=Math.floor(1+Math.floor((e.length-n)/i)),T=f?Math.floor(s/2)+1:s,z=I,S=I;null!==E&&(E>I?A&&(S=E):S=z=E);let C=new p.vw(s),O=new Float64Array(s),P=new Float64Array(C.outputBufferSize),F=Array(z);for(let s=0;s<z;++s){let o=s*i;for(let t=0;t<n;++t)O[t]=e[o+t];if(x){let e=0;for(let t=0;t<n;++t)e+=O[t];let t=e/n;for(let e=0;e<n;++e)O[e]-=t}if(null!==m){for(let e=n-1;e>=1;--e)O[e]-=m*O[e-1];O[0]*=1-m}for(let e=0;e<t.length;++e)O[e]*=t[e];C.realTransform(P,O);let a=Array(T);for(let e=0;e<a.length;++e){let t=e<<1;a[e]=P[t]**2+P[t+1]**2}F[s]=a}if(null!==o&&2!==o){let e=2/o;for(let t=0;t<F.length;++t){let n=F[t];for(let t=0;t<n.length;++t)n[t]**=e}}let M=g.length,L=new Float32Array(M*S),U=k?[S,M]:[M,S];for(let e=0;e<M;++e){let t=g[e];for(let n=0;n<z;++n){let i=F[n],s=0;for(let e=0;e<T;++e)s+=t[e]*i[e];L[k?n*M+e:e*z+n]=Math.max(_,s)}}if(null!==o&&null!==y){let e=Math.min(L.length,z*M);switch(y){case"log":for(let t=0;t<e;++t)L[t]=Math.log(L[t]);break;case"log10":for(let t=0;t<e;++t)L[t]=Math.log10(L[t]);break;case"dB":if(1===o)!function(e,t=1,n=1e-5,i=null){_db_conversion_helper(e,20,t,n,i)}(L,w,b,v);else if(2===o)!function(e,t=1,n=1e-10,i=null){_db_conversion_helper(e,10,t,n,i)}(L,w,b,v);else throw Error(`Cannot use log_mel option '${y}' with power ${o}`);break;default:throw Error(`log_mel must be one of null, 'log', 'log10' or 'dB'. Got '${y}'`)}}return{data:L,dims:U}}function window_function(e,t,{periodic:n=!0,frame_length:i=null,center:s=!0}={}){let o;let a=n?e+1:e;switch(t){case"boxcar":o=new Float64Array(a).fill(1);break;case"hann":case"hann_window":o=function(e){if(e<1)return new Float64Array;if(1===e)return new Float64Array([1]);let t=e-1,n=Math.PI/t,i=new Float64Array(e);for(let s=0;s<e;++s){let e=2*s-t;i[s]=.5+.5*Math.cos(n*e)}return i}(a);break;default:throw Error(`Unknown window type ${t}.`)}if(n&&(o=o.subarray(0,e)),null===i)return o;if(e>i)throw Error(`Length of the window (${e}) may not be larger than frame_length (${i})`);return o}function post_process_object_detection(e,t=.5,n=null,i=!1){let s=e.logits,o=e.pred_boxes,[a,u,c]=s.dims;if(null!==n&&n.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let f=[];for(let e=0;e<a;++e){let a=null!==n?n[e]:null,m={boxes:[],classes:[],scores:[]},g=s[e],_=o[e];for(let e=0;e<u;++e){let n,s=g[e],o=[];if(i){n=s.sigmoid().data;for(let e=0;e<n.length;++e)n[e]>t&&o.push(e)}else{let e=(0,p.Fp)(s.data)[1];if(e===c-1)continue;o.push(e),n=(0,p.XA)(s.data)}for(let t of o){let i=_[e].data;i=function([e,t,n,i]){return[e-n/2,t-i/2,e+n/2,t+i/2]}(i),null!==a&&(i=i.map((e,t)=>e*a[(t+1)%2])),m.boxes.push(i),m.classes.push(t),m.scores.push(n[t])}}f.push(m)}return f}function validate_audio_inputs(e,t){if(!(e instanceof Float32Array||e instanceof Float64Array))throw Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${e?.constructor?.name??typeof e} 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.`)}let FeatureExtractor=class FeatureExtractor extends c.Ag{constructor(e){super(),this.config=e}};let ImageFeatureExtractor=class ImageFeatureExtractor extends FeatureExtractor{constructor(e){super(e),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&&void 0!==this.size.width&&void 0!==this.size.height&&(this.pad_size=this.size)}async thumbnail(e,t,n=2){let i=e.height,s=e.width,o=t.height,a=t.width,u=Math.min(i,o),c=Math.min(s,a);return u===i&&c===s?e:(i>s?c=Math.floor(s*u/i):s>i&&(u=Math.floor(i*c/s)),await e.resize(c,u,{resample:n}))}async crop_margin(e,t=200){let n=e.clone().grayscale(),i=(0,p.VV)(n.data)[0],s=(0,p.Fp)(n.data)[0],o=s-i;if(0===o)return e;let a=t/255,u=n.width,c=n.height,f=0,m=0;for(let e=0;e<n.height;++e){let t=e*n.width;for(let s=0;s<n.width;++s)(n.data[t+s]-i)/o<a&&(u=Math.min(u,s),c=Math.min(c,e),f=Math.max(f,s),m=Math.max(m,e))}return e=await e.crop([u,c,f,m])}pad_image(e,t,n,{mode:i="constant",center:s=!1,constant_values:o=0}={}){let a,u;let[f,p,m]=t;if("number"==typeof n?(a=n,u=n):(a=n.width,u=n.height),a!==f||u!==p){let n=new Float32Array(a*u*m);if(Array.isArray(o))for(let e=0;e<n.length;++e)n[e]=o[e%m];else 0!==o&&n.fill(o);let[g,_]=s?[Math.floor((a-f)/2),Math.floor((u-p)/2)]:[0,0];for(let t=0;t<p;++t){let i=(t+_)*a,s=t*f;for(let t=0;t<f;++t){let o=(i+t+g)*m,a=(s+t)*m;for(let t=0;t<m;++t)n[o+t]=e[a+t]}}if("symmetric"===i){if(s)throw Error("`center` padding is not supported when `mode` is set to `symmetric`.");let t=p-1,i=f-1;for(let s=0;s<u;++s){let o=s*a,u=(0,c.hs)(s,t)*f;for(let t=0;t<a;++t){if(s<p&&t<f)continue;let a=(o+t)*m,g=(u+(0,c.hs)(t,i))*m;for(let t=0;t<m;++t)n[a+t]=e[g+t]}}}e=n,t=[u,a,m]}return[e,t]}rescale(e){for(let t=0;t<e.length;++t)e[t]=this.rescale_factor*e[t]}get_resize_output_image_size(e,t){let n,i;let[s,o]=e.size;if(this.do_thumbnail){let{height:e,width:i}=t;n=Math.min(e,i)}else Number.isInteger(t)?(n=t,i=this.config.max_size??n):void 0!==t&&(n=t.shortest_edge,i=t.longest_edge);if(void 0!==n||void 0!==i){let e=void 0===n?1:Math.max(n/s,n/o),t=s*e,a=o*e,u=void 0===i?1:Math.min(i/t,i/a),c=Math.floor(Number((t*u).toFixed(2))),f=Math.floor(Number((a*u).toFixed(2)));return[c,f]}if(void 0!==t&&void 0!==t.width&&void 0!==t.height)return[t.width,t.height];if(void 0!==this.size_divisibility){let e=Math.floor(s/this.size_divisibility)*this.size_divisibility,t=Math.floor(o/this.size_divisibility)*this.size_divisibility;return[e,t]}throw Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(t)}`)}async resize(e){let[t,n]=this.get_resize_output_image_size(e,this.size);return await e.resize(t,n,{resample:this.resample})}async preprocess(e,{do_normalize:t=null,do_pad:n=null,do_convert_rgb:i=null,do_convert_grayscale:s=null}={}){this.do_crop_margin&&(e=await this.crop_margin(e));let[o,a]=e.size;if(i??this.do_convert_rgb?e=e.rgb():s&&(e=e.grayscale()),this.do_resize&&(e=await this.resize(e)),this.do_thumbnail&&(e=await this.thumbnail(e,this.size,this.resample)),this.do_center_crop){let t,n;Number.isInteger(this.crop_size)?(t=this.crop_size,n=this.crop_size):(t=this.crop_size.width,n=this.crop_size.height),e=await e.center_crop(t,n)}let u=[e.height,e.width],c=Float32Array.from(e.data),f=[e.height,e.width,e.channels];if(this.do_rescale&&this.rescale(c),t??this.do_normalize){let t=this.image_mean;Array.isArray(this.image_mean)||(t=Array(e.channels).fill(t));let n=this.image_std;if(Array.isArray(this.image_std)||(n=Array(e.channels).fill(t)),t.length!==e.channels||n.length!==e.channels)throw Error(`When set to arrays, the length of \`image_mean\` (${t.length}) and \`image_std\` (${n.length}) must match the number of channels in the image (${e.channels}).`);for(let t=0;t<c.length;t+=e.channels)for(let n=0;n<e.channels;++n)c[t+n]=(c[t+n]-this.image_mean[n])/this.image_std[n]}if(n??(this.do_pad&&this.pad_size)){let t=this.pad_image(c,[e.width,e.height,e.channels],this.pad_size);[c,f]=t}let p=new m.es("float32",c,f),g=(0,m.p4)(p,[2,0,1]);return{original_size:[a,o],reshaped_input_size:u,pixel_values:g}}async _call(e,...t){Array.isArray(e)||(e=[e]);let n=await Promise.all(e.map(e=>this.preprocess(e))),i=(0,m.kn)(n.map(e=>e.pixel_values),0);return{pixel_values:i,original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}};let SegformerFeatureExtractor=class SegformerFeatureExtractor extends ImageFeatureExtractor{post_process_semantic_segmentation(e,t=null){let n=e.logits,i=n.dims[0];if(null!==t&&t.length!==i)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let s=[];for(let e=0;e<i;++e){let i=null!==t?t[e]:null,o=n[e];null!==i&&(o=(0,m.sX)(o,i,"bilinear",!1));let[a,u]=i??o.dims.slice(-2),c=new m.es("int32",new Int32Array(a*u),[a,u]),f=o[0].data;for(let e=1;e<o.dims[0];++e){let t=o[e].data;for(let n=0;n<t.length;++n)t[n]>f[n]&&(f[n]=t[n],c.data[n]=e)}let p=Array(o.dims[0]),g=c.data;for(let e=0;e<g.length;++e){let t=g[e];p[t]=t}let _=p.filter(e=>void 0!==e);s.push({segmentation:c,labels:_})}return s}};let BitImageProcessor=class BitImageProcessor extends ImageFeatureExtractor{};let DPTFeatureExtractor=class DPTFeatureExtractor extends ImageFeatureExtractor{};let GLPNFeatureExtractor=class GLPNFeatureExtractor extends ImageFeatureExtractor{};let CLIPFeatureExtractor=class CLIPFeatureExtractor extends ImageFeatureExtractor{};let ChineseCLIPFeatureExtractor=class ChineseCLIPFeatureExtractor extends ImageFeatureExtractor{};let SiglipImageProcessor=class SiglipImageProcessor extends ImageFeatureExtractor{};let ConvNextFeatureExtractor=class ConvNextFeatureExtractor extends ImageFeatureExtractor{constructor(e){super(e),this.crop_pct=this.config.crop_pct??.875}async resize(e){let t=this.size?.shortest_edge;if(void 0===t)throw Error("Size dictionary must contain 'shortest_edge' key.");if(t<384){let n=Math.floor(t/this.crop_pct),[i,s]=this.get_resize_output_image_size(e,{shortest_edge:n});e=await e.resize(i,s,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}};let ConvNextImageProcessor=class ConvNextImageProcessor extends ConvNextFeatureExtractor{};let ViTFeatureExtractor=class ViTFeatureExtractor extends ImageFeatureExtractor{};let ViTImageProcessor=class ViTImageProcessor extends ImageFeatureExtractor{};let MobileViTFeatureExtractor=class MobileViTFeatureExtractor extends ImageFeatureExtractor{};let OwlViTFeatureExtractor=class OwlViTFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...e){return post_process_object_detection(...e)}};let DeiTFeatureExtractor=class DeiTFeatureExtractor extends ImageFeatureExtractor{};let BeitFeatureExtractor=class BeitFeatureExtractor extends ImageFeatureExtractor{};let DonutFeatureExtractor=class DonutFeatureExtractor extends ImageFeatureExtractor{pad_image(e,t,n,i={}){let[s,o,a]=t,u=this.image_mean;Array.isArray(this.image_mean)||(u=Array(a).fill(u));let c=this.image_std;Array.isArray(c)||(c=Array(a).fill(u));let f=u.map((e,t)=>-e/this.image_std[t]);return super.pad_image(e,t,n,{center:!0,constant_values:f,...i})}};let NougatImageProcessor=class NougatImageProcessor extends DonutFeatureExtractor{};let DetrFeatureExtractor=class DetrFeatureExtractor extends ImageFeatureExtractor{async _call(e){let t=await super._call(e),n=[t.pixel_values.dims[0],64,64],i=new m.es("int64",new BigInt64Array(n.reduce((e,t)=>e*t)).fill(1n),n);return{...t,pixel_mask:i}}post_process_object_detection(...e){return post_process_object_detection(...e)}remove_low_and_no_objects(e,t,n,i){let s=[],o=[],a=[];for(let u=0;u<e.dims[0];++u){let c=e[u],f=t[u],m=(0,p.Fp)(c.data)[1];if(m===i)continue;let g=(0,p.XA)(c.data)[m];g>n&&(s.push(f),o.push(g),a.push(m))}return[s,o,a]}check_segment_validity(e,t,n,i=.5,s=.8){let o=[],a=0,u=0;for(let s=0;s<e.length;++s)e[s]===n&&(o.push(s),++a),t[n].data[s]>=i&&++u;let c=a>0&&u>0;return c&&(c=a/u>s),[c,o]}compute_segments(e,t,n,i,s,o=null,a=null){let[u,c]=a??e[0].dims,f=new m.es("int32",new Int32Array(u*c),[u,c]),p=[];if(null!==a)for(let t=0;t<e.length;++t)e[t]=(0,m.sX)(e[t],a,"bilinear",!1);let g=new Int32Array(e[0].data.length),_=new Float32Array(e[0].data.length);for(let n=0;n<e.length;++n){let i=t[n];for(let t=0;t<e[n].data.length;++t)e[n].data[t]*=i,e[n].data[t]>_[t]&&(g[t]=n,_[t]=e[n].data[t])}let y=0;for(let o=0;o<n.length;++o){let a=n[o],[u,c]=this.check_segment_validity(g,e,o,i,s);if(u){for(let e of(++y,c))f.data[e]=y;p.push({id:y,label_id:a,score:t[o]})}}return[f,p]}post_process_panoptic_segmentation(e,t=.5,n=.5,i=.8,s=null,o=null){null===s&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),s=new Set);let a=e.logits,u=e.pred_masks,c=u.sigmoid(),[f,p,g]=a.dims;if(g-=1,null!==o&&o.length!==f)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let _=[];for(let e=0;e<f;++e){let u=null!==o?o[e]:null,f=a[e],p=c[e],[y,w,b]=this.remove_low_and_no_objects(f,p,t,g);if(0===b.length){let[e,t]=u??p.dims.slice(-2),n=new m.es("int32",new Int32Array(e*t).fill(-1),[e,t]);_.push({segmentation:n,segments_info:[]});continue}let[v,x]=this.compute_segments(y,w,b,n,i,s,u);_.push({segmentation:v,segments_info:x})}return _}post_process_instance_segmentation(){throw Error("Not implemented yet")}};let YolosFeatureExtractor=class YolosFeatureExtractor extends ImageFeatureExtractor{post_process_object_detection(...e){return post_process_object_detection(...e)}};let SamImageProcessor=class SamImageProcessor extends ImageFeatureExtractor{reshape_input_points(e,t,n){e=structuredClone(e);let i=(0,c.jg)(e);if(3===i.length)i=[1,...i],e=[e];else if(4!==i.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let i=0;i<e.length;++i){let s=t[i],o=n[i],a=[o[0]/s[0],o[1]/s[1]];for(let t=0;t<e[i].length;++t)for(let n=0;n<e[i][t].length;++n)for(let s=0;s<e[i][t][n].length;++s)e[i][t][n][s]*=a[s]}return new m.es("float32",Float32Array.from(e.flat(1/0)),i)}add_input_labels(e,t){let n=(0,c.jg)(e);if(2===n.length)n=[1,...n],e=[e];else if(3!==n.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(n.some((e,n)=>e!==t.dims[n]))throw Error(`The first ${n.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new m.es("int64",e.flat(1/0).map(BigInt),n)}async _call(e,t=null,n=null){let i=await super._call(e);if(t&&(i.input_points=this.reshape_input_points(t,i.original_sizes,i.reshaped_input_sizes)),n){if(!i.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");i.input_labels=this.add_input_labels(n,i.input_points)}return i}post_process_masks(e,t,n,{mask_threshold:i=0,binarize:s=!0,pad_size:o=null}={}){let a=[];o=o??this.pad_size;let u=[o.height,o.width];for(let o=0;o<t.length;++o){let c=t[o],f=n[o],p=e[o],g=[];for(let e=0;e<p.dims[0];++e){let t=p[e],n=(0,m.sX)(t,u,"bilinear",!1);if(n=n.slice(null,[0,f[0]],[0,f[1]]),n=(0,m.sX)(n,c,"bilinear",!1),s){let e=new Uint8Array(n.data.length);for(let t=0;t<n.data.length;++t)n.data[t]>i&&(e[t]=1);n=new m.es("bool",e,n.dims)}g.push(n)}a.push((0,m.kn)(g))}return a}};let Swin2SRImageProcessor=class Swin2SRImageProcessor extends ImageFeatureExtractor{pad_image(e,t,n,i={}){let[s,o,a]=t;return super.pad_image(e,t,{width:s+(n-s%n)%n,height:o+(n-o%n)%n},{mode:"symmetric",center:!1,constant_values:-1,...i})}};let VitMatteImageProcessor=class VitMatteImageProcessor extends ImageFeatureExtractor{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);let n=await Promise.all(e.map(e=>this.preprocess(e))),i=await Promise.all(t.map(e=>this.preprocess(e,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0}))),s=(0,m.kn)(n.map((e,t)=>(0,m.d3)([e.pixel_values,i[t].pixel_values],0)),0);return{pixel_values:s,original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}};let WhisperFeatureExtractor=class WhisperFeatureExtractor extends FeatureExtractor{constructor(e){super(e),this.config.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(e){let{data:t,dims:n}=spectrogram(e,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}),i=(0,p.Fp)(t)[0];for(let e=0;e<t.length;++e)t[e]=(Math.max(t[e],i-8)+4)/4;return{data:t,dims:n}}async _call(e){let t;validate_audio_inputs(e,"WhisperFeatureExtractor"),e.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`."),t=e.slice(0,this.config.n_samples)):(t=new Float32Array(this.config.n_samples)).set(e);let{data:n,dims:i}=this._extract_fbank_features(t);return{input_features:new m.es("float32",n,[1,...i])}}};let Wav2Vec2FeatureExtractor=class Wav2Vec2FeatureExtractor extends FeatureExtractor{_zero_mean_unit_var_norm(e){let t=e.reduce((e,t)=>e+t,0),n=t/e.length,i=e.reduce((e,t)=>e+(t-n)**2,0)/e.length;return e.map(e=>(e-n)/Math.sqrt(i+1e-7))}async _call(e){validate_audio_inputs(e,"Wav2Vec2FeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));let t=e;this.config.do_normalize&&(t=this._zero_mean_unit_var_norm(t));let n=[1,t.length];return{input_values:new m.es("float32",t,n),attention_mask:new m.es("int64",new BigInt64Array(t.length).fill(1n),n)}}};let ASTFeatureExtractor=class ASTFeatureExtractor extends FeatureExtractor{constructor(e){super(e);let t=this.config.sampling_rate,n=mel_filter_bank(256,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);for(let e=0;e<n.length;++e)n[e].push(0);this.mel_filters=n,this.window=window_function(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(e,t){return spectrogram(e,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:t,transpose:!0})}async _call(e){validate_audio_inputs(e,"ASTFeatureExtractor");let t=this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){let e=2*this.std;for(let n=0;n<t.data.length;++n)t.data[n]=(t.data[n]-this.mean)/e}return{input_values:new m.es("float32",t.data,[1,...t.dims])}}};let ClapFeatureExtractor=class ClapFeatureExtractor extends FeatureExtractor{constructor(e){super(e),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(e,t,n,i){let s;let o=!1,a=e.length-t;if(a>0){if("rand_trunc"===n){o=!0;let n=Math.floor(Math.random()*(a+1));e=e.subarray(n,n+t),(s=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)).dims=[1,...s.dims]}else throw Error(`Truncation strategy "${n}" not implemented`)}else{if(a<0){let n=new Float64Array(t);if(n.set(e),"repeat"===i)for(let i=e.length;i<t;i+=e.length)n.set(e.subarray(0,Math.min(e.length,t-i)),i);else if("repeatpad"===i)for(let t=e.length;t<-a;t+=e.length)n.set(e,t);e=n}if("fusion"===n)throw Error(`Truncation strategy "${n}" not implemented`);(s=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)).dims=[1,...s.dims]}return{...s,longer:o}}_extract_fbank_features(e,t,n=null){return spectrogram(e,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:t,log_mel:"dB",max_num_frames:n,do_pad:!1,transpose:!0})}async _call(e,{max_length:t=null}={}){validate_audio_inputs(e,"ClapFeatureExtractor");let n=this._get_input_mel(e,t??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new m.es("float32",n.data,[1,...n.dims])}}};let SpeechT5FeatureExtractor=class SpeechT5FeatureExtractor extends FeatureExtractor{};let Processor=class Processor extends c.Ag{constructor(e){super(),this.feature_extractor=e}async _call(e,...t){return await this.feature_extractor(e,...t)}};let SamProcessor=class SamProcessor extends Processor{async _call(...e){return await this.feature_extractor(...e)}post_process_masks(...e){return this.feature_extractor.post_process_masks(...e)}reshape_input_points(...e){return this.feature_extractor.reshape_input_points(...e)}};let WhisperProcessor=class WhisperProcessor extends Processor{async _call(e){return await this.feature_extractor(e)}};let Wav2Vec2ProcessorWithLM=class Wav2Vec2ProcessorWithLM extends Processor{async _call(e){return await this.feature_extractor(e)}};let SpeechT5Processor=class SpeechT5Processor extends Processor{async _call(e){return await this.feature_extractor(e)}};let OwlViTProcessor=class OwlViTProcessor extends Processor{};let AutoProcessor=class AutoProcessor{static FEATURE_EXTRACTOR_CLASS_MAPPING={WhisperFeatureExtractor,ViTFeatureExtractor,MobileViTFeatureExtractor,OwlViTFeatureExtractor,CLIPFeatureExtractor,ChineseCLIPFeatureExtractor,SiglipImageProcessor,ConvNextFeatureExtractor,ConvNextImageProcessor,SegformerFeatureExtractor,BitImageProcessor,DPTFeatureExtractor,GLPNFeatureExtractor,BeitFeatureExtractor,DeiTFeatureExtractor,DetrFeatureExtractor,YolosFeatureExtractor,DonutFeatureExtractor,NougatImageProcessor,ViTImageProcessor,VitMatteImageProcessor,SamImageProcessor,Swin2SRImageProcessor,Wav2Vec2FeatureExtractor,SpeechT5FeatureExtractor,ASTFeatureExtractor,ClapFeatureExtractor};static PROCESSOR_CLASS_MAPPING={WhisperProcessor,Wav2Vec2ProcessorWithLM,SamProcessor,SpeechT5Processor,OwlViTProcessor};static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:i=null,local_files_only:s=!1,revision:o="main"}={}){let a=n??await (0,f.yM)(e,"preprocessor_config.json",!0,{progress_callback:t,config:n,cache_dir:i,local_files_only:s,revision:o}),u=a.feature_extractor_type??a.image_processor_type,c=this.FEATURE_EXTRACTOR_CLASS_MAPPING[u];if(!c){if(void 0!==a.size)console.warn(`Feature extractor type "${u}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),c=ImageFeatureExtractor;else throw Error(`Unknown Feature Extractor type: ${u}`)}let p=this.PROCESSOR_CLASS_MAPPING[a.processor_class]??Processor,m=new c(a);return new p(m)}};async function prepareImages(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>RawImage.read(e)))}async function prepareAudios(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>"string"==typeof e||e instanceof URL?read_audio(e,t):e instanceof Float64Array?new Float32Array(e):e))}function get_bounding_box(e,t){t&&(e=e.map(e=>0|e));let[n,i,s,o]=e;return{xmin:n,ymin:i,xmax:s,ymax:o}}let Pipeline=class Pipeline extends c.Ag{constructor({task:e,model:t,tokenizer:n=null,processor:i=null}){super(),this.task=e,this.model=t,this.tokenizer=n,this.processor=i}async dispose(){await this.model.dispose()}};let Text2TextGenerationPipeline=class Text2TextGenerationPipeline extends Pipeline{_key="generated_text";constructor(e){super(e)}async _call(e,t={}){let n;Array.isArray(e)||(e=[e]),this.model.config.prefix&&(e=e.map(e=>this.model.config.prefix+e));let i=this.model.config.task_specific_params;i&&i[this.task]&&i[this.task].prefix&&(e=e.map(e=>i[this.task].prefix+e));let s=this.tokenizer,o={padding:!0,truncation:!0};n=this instanceof TranslationPipeline&&"_build_translation_inputs"in s?s._build_translation_inputs(e,o,t).input_ids:s(e,o).input_ids;let a=await this.model.generate(n,t);return s.batch_decode(a,{skip_special_tokens:!0}).map(e=>({[this._key]:e}))}};let TranslationPipeline=class TranslationPipeline extends Text2TextGenerationPipeline{_key="translation_text";constructor(e){super(e)}};Object.freeze({"text-classification":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,{topk:t=1}={}){let n=this.tokenizer(e,{padding:!0,truncation:!0}),i=await this.model(n),s="multi_label_classification"===this.model.config.problem_type?e=>e.sigmoid().data:e=>(0,p.XA)(e.data),o=this.model.config.id2label,a=[];for(let e of i.logits){let n=s(e),i=(0,p.em)(n,t),u=i.map(e=>({label:o[e[0]],score:e[1]}));1===t?a.push(...u):a.push(u)}return Array.isArray(e)||1===t?a:a[0]}},model:u.o$X,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,{ignore_labels:t=["O"]}={}){let n=Array.isArray(e),i=this.tokenizer(n?e:[e],{padding:!0,truncation:!0}),s=await this.model(i),o=s.logits,a=this.model.config.id2label,u=[];for(let e=0;e<o.dims[0];++e){let n=i.input_ids[e],s=o[e],c=[];for(let e=0;e<s.dims[0];++e){let i=s[e],o=(0,p.Fp)(i.data)[1],u=a?a[o]:`LABEL_${o}`;if(t.includes(u))continue;let f=this.tokenizer.decode([n[e].item()],{skip_special_tokens:!0});if(""===f)continue;let m=(0,p.XA)(i.data);c.push({entity:u,score:m[o],index:e,word:f,start:null,end:null})}u.push(c)}return n?u:u[0]}},model:u.OjJ,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,t,{topk:n=1}={}){let i=this.tokenizer(e,{text_pair:t,padding:!0,truncation:!0}),s=await this.model(i),o=[];for(let e=0;e<s.start_logits.dims[0];++e){let t=i.input_ids[e],a=t.indexOf(this.tokenizer.sep_token_id),u=Array.from((0,p.XA)(s.start_logits[e].data)).map((e,t)=>[e,t]).filter(e=>e[1]>a),f=Array.from((0,p.XA)(s.end_logits[e].data)).map((e,t)=>[e,t]).filter(e=>e[1]>a),m=(0,c.O7)(u,f).filter(e=>e[0][1]<=e[1][1]).map(e=>[e[0][1],e[1][1],e[0][0]*e[1][0]]).sort((e,t)=>t[2]-e[2]);for(let e=0;e<Math.min(m.length,n);++e){let[n,i,s]=m[e],a=[...t].slice(n,i+1),u=this.tokenizer.decode(a,{skip_special_tokens:!0});o.push({answer:u,score:s})}}return 1===n?o[0]:o}},model:u.wiU,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,{topk:t=5}={}){let n=this.tokenizer(e,{padding:!0,truncation:!0}),i=await this.model(n),s=[];for(let e=0;e<n.input_ids.dims[0];++e){let o=n.input_ids[e],a=o.indexOf(this.tokenizer.mask_token_id);if(-1===a)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);let u=i.logits[e],c=u[a],f=(0,p.em)((0,p.XA)(c.data),t);s.push(f.map(e=>{let t=[...o];return t[a]=e[0],{score:e[1],token:e[0],token_str:this.tokenizer.model.vocab[e[0]],sequence:this.tokenizer.decode(t,{skip_special_tokens:!0})}}))}return Array.isArray(e)?s:s[0]}},model:u.t78,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:a.t2,pipeline:class extends Text2TextGenerationPipeline{_key="summary_text";constructor(e){super(e)}},model:u.Kf0,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:a.t2,pipeline:TranslationPipeline,model:u.Kf0,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:a.t2,pipeline:Text2TextGenerationPipeline,model:u.Kf0,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,t={}){let n=Array.isArray(e);n||(e=[e]);let i=t.add_special_tokens??!1;this.tokenizer.padding_side="left";let{input_ids:s,attention_mask:o}=this.tokenizer(e,{add_special_tokens:i,padding:!0,truncation:!0}),a=await this.model.generate(s,t,null,{inputs_attention_mask:o}),u=this.tokenizer.batch_decode(a,{skip_special_tokens:!0}),c=Array.from({length:e.length},e=>[]);for(let t=0;t<u.length;++t){let n=Math.floor(t/a.length*e.length);c[n].push({generated_text:u[t]})}return n||1!==c.length?c:c[0]}},model:u.Hqk,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e),this.label2id=Object.fromEntries(Object.entries(this.model.config.label2id).map(([e,t])=>[e.toLowerCase(),t])),this.entailment_id=this.label2id.entailment,void 0===this.entailment_id&&(console.warn("Could not find 'entailment' in label2id mapping. Using 2 as entailment_id."),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,void 0===this.contradiction_id&&(console.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(e,t,{hypothesis_template:n="This example is {}.",multi_label:i=!1}={}){let s=Array.isArray(e);s||(e=[e]),Array.isArray(t)||(t=[t]);let o=t.map(e=>n.replace("{}",e)),a=i||1===t.length,u=[];for(let n of e){let e=[];for(let t of o){let i=this.tokenizer(n,{text_pair:t,padding:!0,truncation:!0}),s=await this.model(i);a?e.push([s.logits.data[this.contradiction_id],s.logits.data[this.entailment_id]]):e.push(s.logits.data[this.entailment_id])}let i=a?e.map(e=>(0,p.XA)(e)[1]):(0,p.XA)(e),s=i.map((e,t)=>[e,t]).sort((e,t)=>t[0]-e[0]);u.push({sequence:n,labels:s.map(e=>t[e[1]]),scores:s.map(e=>e[0])})}return s?u:u[0]}},model:u.o$X,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,{topk:t=null}={}){let n=!Array.isArray(e),i=this.processor.feature_extractor.config.sampling_rate,s=await prepareAudios(e,i),o=this.model.config.id2label,a=[];for(let e of s){let n=await this.processor(e),i=await this.model(n),s=i.logits[0],u=(0,p.em)((0,p.XA)(s.data),t),c=u.map(e=>({label:o[e[0]],score:e[1]}));1===t?a.push(...c):a.push(c)}return n&&1!==t?a[0]:a}},model:u.K2m,processor:AutoProcessor,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,t,{hypothesis_template:n="This is a sound of {}."}={}){let i=!Array.isArray(e);i&&(e=[e]);let s=t.map(e=>n.replace("{}",e)),o=this.tokenizer(s,{padding:!0,truncation:!0}),a=this.processor.feature_extractor.config.sampling_rate,u=await prepareAudios(e,a),c=[];for(let e of u){let n=await this.processor(e),i=await this.model({...o,...n}),s=(0,p.XA)(i.logits_per_audio.data);c.push([...s].map((e,n)=>({score:e,label:t[n]})))}return i?c[0]:c}},model:u.$Sz,processor:AutoProcessor,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,t={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(e,t);case"wav2vec2":case"hubert":return this._call_wav2vec2(e,t);default:throw Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(e,t={}){t.language&&console.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),t.task&&console.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let n=!Array.isArray(e);n&&(e=[e]);let i=this.processor.feature_extractor.config.sampling_rate,s=await prepareAudios(e,i),o=[];for(let e of s){let t=await this.processor(e),n=await this.model(t),i=n.logits[0],s=[];for(let e of i)s.push((0,p.Fp)(e.data)[1]);let a=this.tokenizer.decode(s);o.push({text:a})}return n?o[0]:o}async _call_whisper(e,t={}){let n=t.return_timestamps??!1,i=t.chunk_length_s??0,s=t.chunk_callback??null,o=t.force_full_sequences??!1,a=t.stride_length_s??null;"word"===n&&(t.return_token_timestamps=!0);let u=(0,c.Sw)(t,"language",null),f=(0,c.Sw)(t,"task",null);if(u||f||n){if(t.forced_decoder_ids)throw Error("Cannot specify `language`/`task`/`return_timestamps` and `forced_decoder_ids` at the same time.");let e=this.tokenizer.get_decoder_prompt_ids({language:u,task:f,no_timestamps:!n});e.length>0&&(t.forced_decoder_ids=e)}let m=!Array.isArray(e);m&&(e=[e]);let g=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,_=this.processor.feature_extractor.config.hop_length,y=this.processor.feature_extractor.config.sampling_rate,w=await prepareAudios(e,y),b=[];for(let e of w){let u=[];if(i>0){if(null===a)a=i/6;else if(i<=a)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");let t=y*i,n=y*a,s=t-2*n,o=0;for(;o<e.length;){let i=e.subarray(o,o+t),a=await this.processor(i),c=0===o,f=o+s>=e.length;u.push({stride:[i.length,c?0:n,f?0:n],input_features:a.input_features,is_last:f}),o+=s}}else u=[{stride:[e.length,0,0],input_features:(await this.processor(e)).input_features,is_last:!0}];for(let e of u){t.num_frames=Math.floor(e.stride[0]/_);let i=await this.model.generate(e.input_features,t);"word"===n?(e.tokens=i.sequences[0],e.token_timestamps=i.token_timestamps.tolist()[0].map(e=>(0,p.NM)(e,2))):e.tokens=i[0],e.stride=e.stride.map(e=>e/y),null!==s&&s(e)}let[c,f]=this.tokenizer._decode_asr(u,{time_precision:g,return_timestamps:n,force_full_sequences:o});b.push({text:c,...f})}return m?b[0]:b}},model:[u.hZO,u.ENH],processor:AutoProcessor,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:a.t2,pipeline:class extends Pipeline{DEFAULT_VOCODER_ID="Xenova/speecht5_hifigan";constructor(e){super(e),this.vocoder=e.vocoder??null}async _call(e,{speaker_embeddings:t=null}={}){return this.processor?this._call_text_to_spectrogram(e,{speaker_embeddings:t}):this._call_text_to_waveform(e)}async _call_text_to_waveform(e){let t=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:n}=await this.model(t),i=this.model.config.sampling_rate;return{audio:n.data,sampling_rate:i}}async _call_text_to_spectrogram(e,{speaker_embeddings:t}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await u.$Sz.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),("string"==typeof t||t instanceof URL)&&(t=new Float32Array(await (await fetch(t)).arrayBuffer())),t instanceof Float32Array)t=new m.es("float32",t,[1,t.length]);else if(!(t instanceof m.es))throw Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");let{input_ids:n}=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:i}=await this.model.generate_speech(n,t,{vocoder:this.vocoder}),s=this.processor.feature_extractor.config.sampling_rate;return{audio:i.data,sampling_rate:s}}},model:[u.z6E,u.lbf],processor:[AutoProcessor,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:a.t2,pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,t={}){let n=Array.isArray(e),i=await prepareImages(e),{pixel_values:s}=await this.processor(i),o=[];for(let e of s){e.dims=[1,...e.dims];let n=await this.model.generate(e,t),i=this.tokenizer.batch_decode(n,{skip_special_tokens:!0}).map(e=>({generated_text:e.trim()}));o.push(i)}return n?o:o[0]}},model:u.tLj,processor:AutoProcessor,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:class extends Pipeline{constructor(e){super(e)}async _call(e,{topk:t=1}={}){let n=Array.isArray(e),i=await 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PriorityQueue=class PriorityQueue{constructor(e=(e,t)=>e>t){this._heap=[],this._comparator=e}get size(){return this._heap.length}isEmpty(){return 0===this.size}peek(){return this._heap[0]}push(...e){return this.extend(e)}extend(e){for(let t of e)this._heap.push(t),this._siftUp();return this.size}pop(){let e=this.peek(),t=this.size-1;return t>0&&this._swap(0,t),this._heap.pop(),this._siftDown(),e}replace(e){let t=this.peek();return this._heap[0]=e,this._siftDown(),t}_parent(e){return(e+1>>>1)-1}_left(e){return(e<<1)+1}_right(e){return e+1<<1}_greater(e,t){return this._comparator(this._heap[e],this._heap[t])}_swap(e,t){let n=this._heap[e];this._heap[e]=this._heap[t],this._heap[t]=n}_siftUp(){let e=this.size-1;for(;e>0&&this._greater(e,this._parent(e));)this._swap(e,this._parent(e)),e=this._parent(e)}_siftDown(){let e=0;for(;this._left(e)<this.size&&this._greater(this._left(e),e)||this._right(e)<this.size&&this._greater(this._right(e),e);){let t=this._right(e)<this.size&&this._greater(this._right(e),this._left(e))?this._right(e):this._left(e);this._swap(e,t),e=t}}};let CharTrie=class CharTrie{constructor(){this.root=CharTrieNode.default()}extend(e){for(let t of e)this.push(t)}push(e){let t=this.root;for(let n of e){let e=t.children.get(n);void 0===e&&(e=CharTrieNode.default(),t.children.set(n,e)),t=e}t.isLeaf=!0}*commonPrefixSearch(e){let t=this.root,n="";for(let i=0;i<e.length&&void 0!==t;++i){let s=e[i];n+=s,void 0!==(t=t.children.get(s))&&t.isLeaf&&(yield n)}}};let CharTrieNode=class CharTrieNode{constructor(e,t){this.isLeaf=e,this.children=t}static default(){return new CharTrieNode(!1,new Map)}};let TokenLattice=class TokenLattice{constructor(e,t,n){this.sentence=e,this.len=e.length,this.bosTokenId=t,this.eosTokenId=n,this.nodes=[],this.beginNodes=Array.from({length:this.len+1},()=>[]),this.endNodes=Array.from({length:this.len+1},()=>[]);let i=new TokenLatticeNode(this.bosTokenId,0,0,0,0),s=new TokenLatticeNode(this.eosTokenId,1,this.len,0,0);this.nodes.push(i.clone()),this.nodes.push(s.clone()),this.beginNodes[this.len].push(s),this.endNodes[0].push(i)}insert(e,t,n,i){let s=this.nodes.length,o=new TokenLatticeNode(i,s,e,t,n);this.beginNodes[e].push(o),this.endNodes[e+t].push(o),this.nodes.push(o)}viterbi(){let e=this.len,t=0;for(;t<=e;){if(0==this.beginNodes[t].length)return[];for(let e of this.beginNodes[t]){e.prev=null;let n=0,i=null;for(let s of this.endNodes[t]){let t=s.backtraceScore+e.score;(null===i||t>n)&&(i=s.clone(),n=t)}if(null===i)return[];e.prev=i,e.backtraceScore=n}++t}let n=[],i=this.beginNodes[e][0],s=i.prev;if(null===s)return[];let o=s.clone();for(;null!==o.prev;){n.push(o.clone());let e=o.clone();o=e.prev.clone()}return n.reverse(),n}piece(e){return this.sentence.slice(e.pos,e.pos+e.length)}tokens(){let e=this.viterbi();return e.map(e=>this.piece(e))}tokenIds(){let e=this.viterbi();return e.map(e=>e.tokenId)}};let TokenLatticeNode=class TokenLatticeNode{constructor(e,t,n,i,s){this.tokenId=e,this.nodeId=t,this.pos=n,this.length=i,this.score=s,this.prev=null,this.backtraceScore=0}clone(){let e=new TokenLatticeNode(this.tokenId,this.nodeId,this.pos,this.length,this.score);return e.prev=this.prev,e.backtraceScore=this.backtraceScore,e}}},2013:function(e,t,n){"use strict";n.d(t,{AE:function(){return NoBadWordsLogitsProcessor},C9:function(){return ForcedBOSTokenLogitsProcessor},CJ:function(){return MinNewTokensLengthLogitsProcessor},E:function(){return ForceTokensLogitsProcessor},GU:function(){return SuppressTokensAtBeginLogitsProcessor},Jj:function(){return RepetitionPenaltyLogitsProcessor},Jm:function(){return LogitsProcessorList},Pg:function(){return WhisperTimeStampLogitsProcessor},Z4:function(){return Sampler},aP:function(){return o},dZ:function(){return ForcedEOSTokenLogitsProcessor},ez:function(){return MinLengthLogitsProcessor},jF:function(){return NoRepeatNGramLogitsProcessor}}),n(6001);var i=n(1802),s=n(4297);let LogitsProcessorList=class LogitsProcessorList extends i.Ag{constructor(){super(),this.processors=[]}push(e){this.processors.push(e)}extend(e){this.processors.push(...e)}_call(e,t){for(let n of t)this.processors.forEach(t=>t(e,n))}[Symbol.iterator](){return this.processors.values()}};let LogitsProcessor=class LogitsProcessor extends i.Ag{_call(e,t){throw Error("`_call` should be implemented in a subclass")}};let ForceTokensLogitsProcessor=class ForceTokensLogitsProcessor extends LogitsProcessor{constructor(e){super(),this.force_token_map=Object.fromEntries(e??[])}_call(e,t){let n=this.force_token_map[e.length];return(0,i.Gg)(n)&&(t.data.fill(-1/0),t.data[n]=0),t}};let ForcedBOSTokenLogitsProcessor=class ForcedBOSTokenLogitsProcessor extends LogitsProcessor{constructor(e){super(),this.bos_token_id=e}_call(e,t){return 1===e.length&&(t.data.fill(-1/0),t.data[this.bos_token_id]=0),t}};let ForcedEOSTokenLogitsProcessor=class ForcedEOSTokenLogitsProcessor extends LogitsProcessor{constructor(e,t){super(),this.max_length=e,this.forced_eos_token_id=t}_call(e,t){}};let SuppressTokensAtBeginLogitsProcessor=class SuppressTokensAtBeginLogitsProcessor extends LogitsProcessor{constructor(e,t){super(),this.begin_suppress_tokens=e,this.begin_index=t}_call(e,t){if(e.length===this.begin_index)for(let e of this.begin_suppress_tokens)t.data[e]=-1/0;return t}};let WhisperTimeStampLogitsProcessor=class WhisperTimeStampLogitsProcessor extends LogitsProcessor{constructor(e){super(),this.eos_token_id=e.eos_token_id,this.no_timestamps_token_id=e.no_timestamps_token_id,this.timestamp_begin=this.no_timestamps_token_id+1,this.begin_index=(e.forced_decoder_ids||[]).length+2,e.forced_decoder_ids.slice(-1)[0][1]===this.no_timestamps_token_id&&(this.begin_index-=1),this.max_initial_timestamp_index=e.max_initial_timestamp_index}_call(e,t){let n=t.data;if(n[this.no_timestamps_token_id]=-1/0,e.length===this.begin_index-1)return n.fill(-1/0),n[this.timestamp_begin]=0,t;let i=e.slice(this.begin_index),o=i.length>=1&&i[i.length-1]>=this.timestamp_begin,a=i.length<2||i[i.length-2]>=this.timestamp_begin;if(o&&(a?n.subarray(this.timestamp_begin).fill(-1/0):n.subarray(0,this.eos_token_id).fill(-1/0)),e.length===this.begin_index&&null!==this.max_initial_timestamp_index){let e=this.timestamp_begin+this.max_initial_timestamp_index;n.subarray(e+1).fill(-1/0)}let u=(0,s.CI)(n),c=Math.log(u.subarray(this.timestamp_begin).map(Math.exp).reduce((e,t)=>e+t)),f=(0,s.Fp)(u.subarray(0,this.timestamp_begin))[0];return c>f&&n.subarray(0,this.timestamp_begin).fill(-1/0),t}};let NoRepeatNGramLogitsProcessor=class NoRepeatNGramLogitsProcessor extends LogitsProcessor{constructor(e){super(),this.no_repeat_ngram_size=e}getNgrams(e){let t=e.length,n=[];for(let i=0;i<t+1-this.no_repeat_ngram_size;++i){let t=[];for(let n=0;n<this.no_repeat_ngram_size;++n)t.push(e[i+n]);n.push(t)}let i=new Map;for(let e of n){let t=e.slice(0,e.length-1),n=JSON.stringify(t),s=i.get(n)??[];s.push(e[e.length-1]),i.set(n,s)}return i}getGeneratedNgrams(e,t){let n=t.slice(t.length+1-this.no_repeat_ngram_size,t.length),i=e.get(JSON.stringify(n))??[];return i}calcBannedNgramTokens(e){if(e.length+1<this.no_repeat_ngram_size)return[];{let t=this.getNgrams(e),n=this.getGeneratedNgrams(t,e);return n}}_call(e,t){let n=this.calcBannedNgramTokens(e);for(let e of n)t.data[e]=-1/0;return t}};let RepetitionPenaltyLogitsProcessor=class RepetitionPenaltyLogitsProcessor extends LogitsProcessor{constructor(e){super(),this.penalty=e}_call(e,t){for(let n of e)t.data[n]<0?t.data[n]*=this.penalty:t.data[n]/=this.penalty;return t}};let MinLengthLogitsProcessor=class MinLengthLogitsProcessor extends LogitsProcessor{constructor(e,t){super(),this.min_length=e,this.eos_token_id=Array.isArray(t)?t:[t]}_call(e,t){if(e.length<this.min_length)for(let e of this.eos_token_id)t.data[e]=-1/0;return t}};let MinNewTokensLengthLogitsProcessor=class MinNewTokensLengthLogitsProcessor extends LogitsProcessor{constructor(e,t,n){super(),this.prompt_length_to_skip=e,this.min_new_tokens=t,this.eos_token_id=Array.isArray(n)?n:[n]}_call(e,t){let n=e.length-this.prompt_length_to_skip;if(n<this.min_new_tokens)for(let e of this.eos_token_id)t.data[e]=-1/0;return t}};let NoBadWordsLogitsProcessor=class NoBadWordsLogitsProcessor extends LogitsProcessor{constructor(e,t){super(),this.bad_words_ids=e,this.eos_token_id=Array.isArray(t)?t:[t]}_call(e,t){for(let n of this.bad_words_ids){let i=!0;for(let t=1;t<=n.length-1&&n.length<e.length;++t)if(n.at(-t-1)!==e.at(-t)){i=!1;break}i&&(t.data[n.at(-1)]=-1/0)}return t}};let o=class{constructor(e={}){this.max_length=e.max_length??20,this.max_new_tokens=e.max_new_tokens??null,this.min_length=e.min_length??0,this.min_new_tokens=e.min_new_tokens??null,this.early_stopping=e.early_stopping??!1,this.max_time=e.max_time??null,this.do_sample=e.do_sample??!1,this.num_beams=e.num_beams??1,this.num_beam_groups=e.num_beam_groups??1,this.penalty_alpha=e.penalty_alpha??null,this.use_cache=e.use_cache??!0,this.temperature=e.temperature??1,this.top_k=e.top_k??50,this.top_p=e.top_p??1,this.typical_p=e.typical_p??1,this.epsilon_cutoff=e.epsilon_cutoff??0,this.eta_cutoff=e.eta_cutoff??0,this.diversity_penalty=e.diversity_penalty??0,this.repetition_penalty=e.repetition_penalty??1,this.encoder_repetition_penalty=e.encoder_repetition_penalty??1,this.length_penalty=e.length_penalty??1,this.no_repeat_ngram_size=e.no_repeat_ngram_size??0,this.bad_words_ids=e.bad_words_ids??null,this.force_words_ids=e.force_words_ids??null,this.renormalize_logits=e.renormalize_logits??!1,this.constraints=e.constraints??null,this.forced_bos_token_id=e.forced_bos_token_id??null,this.forced_eos_token_id=e.forced_eos_token_id??null,this.remove_invalid_values=e.remove_invalid_values??!1,this.exponential_decay_length_penalty=e.exponential_decay_length_penalty??null,this.suppress_tokens=e.suppress_tokens??null,this.begin_suppress_tokens=e.begin_suppress_tokens??null,this.forced_decoder_ids=e.forced_decoder_ids??null,this.num_return_sequences=e.num_return_sequences??1,this.output_attentions=e.output_attentions??!1,this.output_hidden_states=e.output_hidden_states??!1,this.output_scores=e.output_scores??!1,this.return_dict_in_generate=e.return_dict_in_generate??!1,this.pad_token_id=e.pad_token_id??null,this.bos_token_id=e.bos_token_id??null,this.eos_token_id=e.eos_token_id??null,this.encoder_no_repeat_ngram_size=e.encoder_no_repeat_ngram_size??0,this.decoder_start_token_id=e.decoder_start_token_id??null,this.generation_kwargs=e.generation_kwargs??{}}};let Sampler=class Sampler extends i.Ag{constructor(e){super(),this.generation_config=e}_call(e,t=-1){return this.sample(e,t)}sample(e,t){throw Error("sample should be implemented in subclasses.")}getLogits(e,t){let n=e.dims.at(-1),i=e.data;if(-1===t)i=i.slice(-n);else{let e=t*n;i=i.slice(e,e+n)}return this.generation_config.temperature>0&&(i=i.map(e=>e/this.generation_config.temperature)),i}randomSelect(e){let t=Math.random()*e.reduce((e,t)=>e+t,0);for(let n=0;n<e.length;++n)if((t-=e[n])<=0)return n;return 0}static getSampler(e){if(e.do_sample)return new MultinomialSampler(e);if(e.num_beams>1)return new BeamSearchSampler(e);if(e.num_return_sequences>1)throw Error(`num_return_sequences has to be 1 when doing greedy search, but is ${e.num_return_sequences}.`);return new GreedySampler(e)}};let GreedySampler=class GreedySampler extends Sampler{sample(e,t=-1){let n=this.getLogits(e,t);return[[(0,s.Fp)(n)[1],0]]}};let MultinomialSampler=class MultinomialSampler extends Sampler{sample(e,t=-1){let n=e.dims.at(-1);this.generation_config.top_k>0&&(n=Math.min(this.generation_config.top_k,n));let i=this.getLogits(e,t),o=(0,s.em)(i,n),a=(0,s.XA)(o.map(e=>e[1]));return Array.from({length:this.generation_config.num_beams},()=>{let e=this.randomSelect(a);return[o[e][0],Math.log(a[e])]})}};let BeamSearchSampler=class BeamSearchSampler extends Sampler{sample(e,t=-1){let n=e.dims.at(-1);this.generation_config.top_k>0&&(n=Math.min(this.generation_config.top_k,n));let i=this.getLogits(e,t),o=(0,s.em)(i,n),a=(0,s.XA)(o.map(e=>e[1]));return Array.from({length:this.generation_config.num_beams},(e,t)=>[o[t][0],Math.log(a[t])])}}},4320:function(e,t,n){"use strict";n.d(t,{hn:function(){return getFile},st:function(){return getModelFile},yM:function(){return getModelJSON}});var i=n(7147),s=n(1418),o=n(319),a=n(9721),u=n(1802),c=n(2601),f=n(7133).lW;globalThis.ReadableStream||(globalThis.ReadableStream=o.ReadableStream);let FileResponse=class FileResponse{_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"};constructor(e){if(this.filePath=e,this.headers=new Headers,this.exists=i.existsSync(e),this.exists){this.status=200,this.statusText="OK";let t=i.statSync(e);this.headers.set("content-length",t.size.toString()),this.updateContentType();let n=this;this.body=new ReadableStream({start(e){n.arrayBuffer().then(t=>{e.enqueue(new Uint8Array(t)),e.close()})}})}else this.status=404,this.statusText="Not Found",this.body=null}updateContentType(){let e=this.filePath.toString().split(".").pop().toLowerCase();this.headers.set("content-type",this._CONTENT_TYPE_MAP[e]??"application/octet-stream")}clone(){let e=new FileResponse(this.filePath);return e.exists=this.exists,e.status=this.status,e.statusText=this.statusText,e.headers=new Headers(this.headers),e}async arrayBuffer(){let e=await 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Fix by setting `env.allowLocalModels` or `env.allowRemoteModels` to `true`.")}if((0,u.T2)(i.progress_callback,{status:"initiate",name:e,file:t}),!s&&a.O.useBrowserCache){if("undefined"==typeof caches)throw Error("Browser cache is not available in this environment.");try{s=await caches.open("transformers-cache")}catch(e){console.warn("An error occurred while opening the browser cache:",e)}}if(!s&&a.O.useFSCache&&(s=new FileCache(i.cache_dir??a.O.cacheDir)),!s&&a.O.useCustomCache){if(!a.O.customCache)throw Error("`env.useCustomCache=true`, but `env.customCache` is not defined.");if(!a.O.customCache.match||!a.O.customCache.put)throw Error("`env.customCache` must be an object which implements the `match` and `put` functions of the Web Cache API. 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Will expand buffer when needed.");let i=parseInt(n??"0"),s=new Uint8Array(i),o=0,a=e.body.getReader();async function read(){let{done:e,value:n}=await a.read();if(e)return;let u=o+n.length;if(u>i){i=u;let e=new Uint8Array(i);e.set(s),s=e}s.set(n,o),o=u;let c=o/i*100;return t({progress:c,loaded:o,total:i}),read()}return await read(),s}function pathJoin(...e){return(e=e.map((t,n)=>(n&&(t=t.replace(RegExp("^/"),"")),n!==e.length-1&&(t=t.replace(RegExp("/$"),"")),t))).join("/")}},4297:function(e,t,n){"use strict";function interpolate_data(e,[t,n,i],[s,o],a="bilinear",u=!1){let c=o/i,f=s/n,p=new e.constructor(s*o*t),m=n*i,g=s*o;for(let a=0;a<s;++a)for(let s=0;s<o;++s){let u=a*o+s,_=(s+.5)/c-.5,y=(a+.5)/f-.5,w=Math.floor(_),b=Math.floor(y),v=Math.min(w+1,i-1),x=Math.min(b+1,n-1);w=Math.max(w,0),b=Math.max(b,0);let E=_-w,A=y-b,k=(1-E)*(1-A),B=E*(1-A),I=(1-E)*A,T=E*A,z=b*i,S=x*i,C=z+w,O=z+v,P=S+w,F=S+v;for(let n=0;n<t;++n){let t=n*m;p[n*g+u]=k*e[t+C]+B*e[t+O]+I*e[t+P]+T*e[t+F]}}return p}function transpose_data(e,t,n){let i=Array(n.length),s=Array(n.length);for(let e=n.length-1,o=1;e>=0;--e)s[e]=o,i[e]=t[n[e]],o*=i[e];let o=n.map((e,t)=>s[n.indexOf(t)]),a=new e.constructor(e.length);for(let n=0;n<e.length;++n){let i=0;for(let e=t.length-1,s=n;e>=0;--e)i+=s%t[e]*o[e],s=Math.floor(s/t[e]);a[i]=e[n]}return[a,i]}function softmax(e){let t=max(e)[0],n=e.map(e=>Math.exp(e-t)),i=n.reduce((e,t)=>e+t,0),s=n.map(e=>e/i);return s}function log_softmax(e){let t=softmax(e),n=t.map(e=>Math.log(e));return n}function getTopItems(e,t=0){return e=Array.from(e).map((e,t)=>[t,e]).sort((e,t)=>t[1]-e[1]),null!==t&&t>0&&(e=e.slice(0,t)),e}function min(e){if(0===e.length)throw Error("Array must not be empty");let t=e[0],n=0;for(let i=1;i<e.length;++i)e[i]<t&&(t=e[i],n=i);return[t,n]}function max(e){if(0===e.length)throw Error("Array must not be empty");let t=e[0],n=0;for(let i=1;i<e.length;++i)e[i]>t&&(t=e[i],n=i);return[Number(t),n]}function isPowerOfTwo(e){return e>0&&(e&e-1)==0}n.d(t,{CI:function(){return log_softmax},Fp:function(){return max},K0:function(){return transpose_data},NM:function(){return round},Nq:function(){return interpolate_data},VV:function(){return min},XA:function(){return softmax},em:function(){return getTopItems},qC:function(){return medianFilter},vw:function(){return FFT}});let P2FFT=class P2FFT{constructor(e){if(this.size=0|e,this.size<=1||!isPowerOfTwo(this.size))throw Error("FFT size must be a power of two larger than 1");this._csize=e<<1,this.table=new Float64Array(2*this.size);for(let e=0;e<this.table.length;e+=2){let t=Math.PI*e/this.size;this.table[e]=Math.cos(t),this.table[e+1]=-Math.sin(t)}let t=0;for(let e=1;this.size>e;e<<=1)++t;this._width=t%2==0?t-1:t,this._bitrev=new Int32Array(1<<this._width);for(let e=0;e<this._bitrev.length;++e){this._bitrev[e]=0;for(let t=0;t<this._width;t+=2){let n=this._width-t-2;this._bitrev[e]|=(e>>>t&3)<<n}}}createComplexArray(){return new Float64Array(this._csize)}fromComplexArray(e,t){let n=t||Array(e.length>>>1);for(let t=0;t<e.length;t+=2)n[t>>>1]=e[t];return n}toComplexArray(e,t){let n=t||this.createComplexArray();for(let t=0;t<n.length;t+=2)n[t]=e[t>>>1],n[t+1]=0;return n}completeSpectrum(e){let t=this._csize,n=t>>>1;for(let i=2;i<n;i+=2)e[t-i]=e[i],e[t-i+1]=-e[i+1]}transform(e,t){if(e===t)throw Error("Input and output buffers must be different");this._transform4(e,t,1)}realTransform(e,t){if(e===t)throw Error("Input and output buffers must be different");this._realTransform4(e,t,1)}inverseTransform(e,t){if(e===t)throw Error("Input and output buffers must be different");this._transform4(e,t,-1);for(let t=0;t<e.length;++t)e[t]/=this.size}_transform4(e,t,n){let i,s;let o=this._csize,a=this._width,u=1<<a,c=o/u<<1,f=this._bitrev;if(4===c)for(i=0,s=0;i<o;i+=c,++s){let n=f[s];this._singleTransform2(t,e,i,n,u)}else for(i=0,s=0;i<o;i+=c,++s){let o=f[s];this._singleTransform4(t,e,i,o,u,n)}for(u>>=2;u>=2;u>>=2){c=o/u<<1;let t=c>>>2;for(i=0;i<o;i+=c){let s=i+t-1;for(let o=i,a=0;o<s;o+=2,a+=u){let i=o,s=i+t,u=s+t,c=u+t,f=e[i],p=e[i+1],m=e[s],g=e[s+1],_=e[u],y=e[u+1],w=e[c],b=e[c+1],v=this.table[a],x=n*this.table[a+1],E=m*v-g*x,A=m*x+g*v,k=this.table[2*a],B=n*this.table[2*a+1],I=_*k-y*B,T=_*B+y*k,z=this.table[3*a],S=n*this.table[3*a+1],C=w*z-b*S,O=w*S+b*z,P=f+I,F=p+T,M=f-I,L=p-T,U=E+C,R=A+O,N=n*(E-C),$=n*(A-O);e[i]=P+U,e[i+1]=F+R,e[s]=M+$,e[s+1]=L-N,e[u]=P-U,e[u+1]=F-R,e[c]=M-$,e[c+1]=L+N}}}}_singleTransform2(e,t,n,i,s){let o=e[i],a=e[i+1],u=e[i+s],c=e[i+s+1];t[n]=o+u,t[n+1]=a+c,t[n+2]=o-u,t[n+3]=a-c}_singleTransform4(e,t,n,i,s,o){let a=2*s,u=3*s,c=e[i],f=e[i+1],p=e[i+s],m=e[i+s+1],g=e[i+a],_=e[i+a+1],y=e[i+u],w=e[i+u+1],b=c+g,v=f+_,x=c-g,E=f-_,A=p+y,k=m+w,B=o*(p-y),I=o*(m-w);t[n]=b+A,t[n+1]=v+k,t[n+2]=x+I,t[n+3]=E-B,t[n+4]=b-A,t[n+5]=v-k,t[n+6]=x-I,t[n+7]=E+B}_realTransform4(e,t,n){let i,s;let o=this._csize,a=this._width,u=1<<a,c=o/u<<1,f=this._bitrev;if(4===c)for(i=0,s=0;i<o;i+=c,++s){let n=f[s];this._singleRealTransform2(t,e,i,n>>>1,u>>>1)}else for(i=0,s=0;i<o;i+=c,++s){let o=f[s];this._singleRealTransform4(t,e,i,o>>>1,u>>>1,n)}for(u>>=2;u>=2;u>>=2){c=o/u<<1;let t=c>>>2;for(i=0;i<o;i+=c){let s=i+t-1;for(let o=i,a=0;o<s;o+=2,a+=u){let i=o,s=i+t,u=s+t,c=u+t,f=e[i],p=e[i+1],m=e[s],g=e[s+1],_=e[u],y=e[u+1],w=e[c],b=e[c+1],v=this.table[a],x=n*this.table[a+1],E=m*v-g*x,A=m*x+g*v,k=this.table[2*a],B=n*this.table[2*a+1],I=_*k-y*B,T=_*B+y*k,z=this.table[3*a],S=n*this.table[3*a+1],C=w*z-b*S,O=w*S+b*z,P=f+I,F=p+T,M=f-I,L=p-T,U=E+C,R=A+O,N=n*(E-C),$=n*(A-O);e[i]=P+U,e[i+1]=F+R,e[s]=M+$,e[s+1]=L-N,e[u]=P-U,e[u+1]=F-R,e[c]=M-$,e[c+1]=L+N}}}}_singleRealTransform2(e,t,n,i,s){let o=e[i],a=e[i+s];t[n]=o+a,t[n+1]=0,t[n+2]=o-a,t[n+3]=0}_singleRealTransform4(e,t,n,i,s,o){let a=e[i],u=e[i+s],c=e[i+2*s],f=e[i+3*s],p=a+c,m=a-c,g=u+f,_=o*(u-f);t[n]=p+g,t[n+1]=0,t[n+2]=m,t[n+3]=-_,t[n+4]=p-g,t[n+5]=0,t[n+6]=m,t[n+7]=_}};let NP2FFT=class NP2FFT{constructor(e){let t=2*(e-1),n=2*(2*e-1),i=2**Math.ceil(Math.log2(n));this.bufferSize=i,this._a=t;let s=new Float64Array(n),o=new Float64Array(i);this._chirpBuffer=new Float64Array(i),this._buffer1=new Float64Array(i),this._buffer2=new Float64Array(i),this._outBuffer1=new Float64Array(i),this._outBuffer2=new Float64Array(i);let a=-2*Math.PI/e,u=Math.cos(a),c=Math.sin(a);for(let t=0;t<n>>1;++t){let n=(t+1-e)**2/2,i=Math.sqrt(u**2+c**2)**n,a=n*Math.atan2(c,u),f=2*t;s[f]=i*Math.cos(a),s[f+1]=i*Math.sin(a),o[f]=s[f],o[f+1]=-s[f+1]}this._slicedChirpBuffer=s.subarray(t,n),this._f=new P2FFT(i>>1),this._f.transform(this._chirpBuffer,o)}_transform(e,t,n){let i=this._buffer1,s=this._buffer2,o=this._outBuffer1,a=this._outBuffer2,u=this._chirpBuffer,c=this._slicedChirpBuffer,f=this._a;if(n)for(let e=0;e<c.length;e+=2){let n=e+1,s=e>>1,o=t[s];i[e]=o*c[e],i[n]=o*c[n]}else for(let e=0;e<c.length;e+=2){let n=e+1;i[e]=t[e]*c[e]-t[n]*c[n],i[n]=t[e]*c[n]+t[n]*c[e]}this._f.transform(o,i);for(let e=0;e<u.length;e+=2){let t=e+1;s[e]=o[e]*u[e]-o[t]*u[t],s[t]=o[e]*u[t]+o[t]*u[e]}this._f.inverseTransform(a,s);for(let t=0;t<a.length;t+=2){let n=a[t+f],i=a[t+f+1],s=c[t],o=c[t+1];e[t]=n*s-i*o,e[t+1]=n*o+i*s}}transform(e,t){this._transform(e,t,!1)}realTransform(e,t){this._transform(e,t,!0)}};let FFT=class FFT{constructor(e){this.fft_length=e,this.isPowerOfTwo=isPowerOfTwo(e),this.isPowerOfTwo?(this.fft=new P2FFT(e),this.outputBufferSize=2*e):(this.fft=new NP2FFT(e),this.outputBufferSize=this.fft.bufferSize)}realTransform(e,t){this.fft.realTransform(e,t)}transform(e,t){this.fft.transform(e,t)}};function medianFilter(e,t){if(t%2==0||t<=0)throw Error("Window size must be a positive odd number");let n=new e.constructor(e.length),i=new e.constructor(t),s=Math.floor(t/2);for(let t=0;t<e.length;++t){let o=0;for(let n=-s;n<=s;++n){let s=t+n;s<0?s=Math.abs(s):s>=e.length&&(s=2*(e.length-1)-s),i[o++]=e[s]}i.sort(),n[t]=i[s]}return n}function round(e,t){let n=Math.pow(10,t);return Math.round(e*n)/n}},6001:function(e,t,n){"use strict";n.d(t,{J6:function(){return mean},Ks:function(){return dynamicTimeWarping},d3:function(){return cat},es:function(){return Tensor},f3:function(){return std_mean},kn:function(){return stack},p4:function(){return transpose},r6:function(){return ones_like},sX:function(){return interpolate},v6:function(){return mean_pooling}});var i=n(6577),s=n(4297);let o=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}),a=i.ONNX.Tensor;let Tensor=class Tensor{dims;type;data;size;constructor(...e){return e[0]instanceof a?Object.assign(this,e[0]):Object.assign(this,new a(e[0],e[1],e[2])),new Proxy(this,{get:(e,t)=>{if("string"==typeof t){let n=Number(t);if(Number.isInteger(n))return e._getitem(n)}return e[t]},set:(e,t,n)=>e[t]=n})}*[Symbol.iterator](){let[e,...t]=this.dims;if(t.length>0){let n=t.reduce((e,t)=>e*t);for(let i=0;i<e;++i)yield this._subarray(i,n,t)}else yield*this.data}_getitem(e){let[t,...n]=this.dims;if(e=safeIndex(e,t),!(n.length>0))return new Tensor(this.type,[this.data[e]],n);{let t=n.reduce((e,t)=>e*t);return this._subarray(e,t,n)}}indexOf(e){for(let t=0;t<this.data.length;++t)if(this.data[t]==e)return t;return -1}_subarray(e,t,n){let i=e*t,s=(e+1)*t,o="subarray"in this.data?this.data.subarray(i,s):this.data.slice(i,s);return new Tensor(this.type,o,n)}item(){if(1!==this.data.length)throw Error(`a Tensor with ${this.data.length} elements cannot be converted to Scalar`);return this.data[0]}tolist(){return function(e,t){let n=e.length,i=t.reduce((e,t)=>e*t);if(n!==i)throw Error(`cannot reshape array of size ${n} into shape (${t})`);let s=e;for(let e=t.length-1;e>=0;e--)s=s.reduce((n,i)=>{let s=n[n.length-1];return s.length<t[e]?s.push(i):n.push([i]),n},[[]]);return s[0]}(this.data,this.dims)}sigmoid(){return this.clone().sigmoid_()}sigmoid_(){for(let e=0;e<this.data.length;++e)this.data[e]=1/(1+Math.exp(-this.data[e]));return this}mul(e){return this.clone().mul_(e)}mul_(e){for(let t=0;t<this.data.length;++t)this.data[t]*=e;return this}add(e){return this.clone().add_(e)}add_(e){for(let t=0;t<this.data.length;++t)this.data[t]+=e;return this}clone(){return new Tensor(this.type,this.data.slice(),this.dims.slice())}slice(...e){let t=[],n=[];for(let i=0;i<this.dims.length;++i){let s=e[i];if(null==s)n.push([0,this.dims[i]]),t.push(this.dims[i]);else if("number"==typeof s)s=safeIndex(s,this.dims[i],i),n.push([s,s+1]);else if(Array.isArray(s)&&2===s.length){if(s[0]>s[1])throw Error(`Invalid slice: ${s}`);let e=[Math.max(s[0],0),Math.min(s[1],this.dims[i])];n.push(e),t.push(e[1]-e[0])}else throw Error(`Invalid slice: ${s}`)}let i=n.map(([e,t])=>t-e),s=i.reduce((e,t)=>e*t),o=new this.data.constructor(s),a=this.stride();for(let e=0;e<s;++e){let t=0;for(let s=i.length-1,o=e;s>=0;--s){let e=i[s];t+=(o%e+n[s][0])*a[s],o=Math.floor(o/e)}o[e]=this.data[t]}return new Tensor(this.type,o,t)}transpose(...e){return transpose(this,e)}sum(e=null,t=!1){return this.norm(1,e,t)}norm(e="fro",t=null,n=!1){if("fro"===e)e=2;else if("string"==typeof e)throw Error(`Unsupported norm: ${e}`);if(null===t){let t=this.data.reduce((t,n)=>t+n**e,0)**(1/e);return new Tensor(this.type,[t],[])}t=safeIndex(t,this.dims.length);let i=this.dims.slice();i[t]=1;let s=new this.data.constructor(this.data.length/this.dims[t]);for(let n=0;n<this.data.length;++n){let o=0;for(let e=this.dims.length-1,s=n,a=1;e>=0;--e){let n=this.dims[e];if(e!==t){let t=s%n;o+=t*a,a*=i[e]}s=Math.floor(s/n)}s[o]+=this.data[n]**e}if(1!==e)for(let t=0;t<s.length;++t)s[t]=s[t]**(1/e);return n||i.splice(t,1),new Tensor(this.type,s,i)}normalize_(e=2,t=1){t=safeIndex(t,this.dims.length);let n=this.norm(e,t,!0);for(let e=0;e<this.data.length;++e){let i=0;for(let n=this.dims.length-1,s=e,o=1;n>=0;--n){let e=this.dims[n];if(n!==t){let t=s%e;i+=t*o,o*=this.dims[n]}s=Math.floor(s/e)}this.data[e]/=n.data[i]}return this}normalize(e=2,t=1){return this.clone().normalize_(e,t)}stride(){return function(e){let t=Array(e.length);for(let n=e.length-1,i=1;n>=0;--n)t[n]=i,i*=e[n];return t}(this.dims)}squeeze(e=null){return new Tensor(this.type,this.data,calc_squeeze_dims(this.dims,e))}squeeze_(e=null){return this.dims=calc_squeeze_dims(this.dims,e),this}unsqueeze(e=null){return new Tensor(this.type,this.data,calc_unsqueeze_dims(this.dims,e))}unsqueeze_(e=null){return this.dims=calc_unsqueeze_dims(this.dims,e),this}flatten_(e=0,t=-1){t=(t+this.dims.length)%this.dims.length;let n=this.dims.slice(0,e),i=this.dims.slice(e,t+1),s=this.dims.slice(t+1);return this.dims=[...n,i.reduce((e,t)=>e*t,1),...s],this}flatten(e=0,t=-1){return this.clone().flatten_(e,t)}view(...e){let t=-1;for(let n=0;n<e.length;++n)if(-1===e[n]){if(-1!==t)throw Error("Only one dimension can be inferred");t=n}if(-1!==t){let 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e.data.constructor(n[0]*n[1]),[s,o,a]=e.dims,u=0;for(let n=0;n<s;++n){let s=n*a*o;for(let c=0;c<a;++c){let f=0,p=0,m=n*o,g=s+c;for(let n=0;n<o;++n){let i=Number(t.data[m+n]);p+=i,f+=e.data[g+n*a]*i}let _=f/p;i[u++]=_}}return new Tensor(e.type,i,n)}function calc_squeeze_dims(e,t){return e=e.slice(),null===t?e=e.filter(e=>1!==e):"number"==typeof t?1===e[t]&&e.splice(t,1):Array.isArray(t)&&(e=e.filter((e,n)=>1!==e||!t.includes(n))),e}function calc_unsqueeze_dims(e,t){return t=safeIndex(t,e.length+1),(e=e.slice()).splice(t,0,1),e}function safeIndex(e,t,n=null){if(e<-t||e>=t)throw Error(`IndexError: index ${e} is out of bounds for dimension${null===n?"":" "+n} with size ${t}`);return e<0&&(e=(e%t+t)%t),e}function cat(e,t=0){t=safeIndex(t,e[0].dims.length);let n=e[0].dims.slice();n[t]=e.reduce((e,n)=>e+n.dims[t],0);let i=n.reduce((e,t)=>e*t,1),s=new e[0].data.constructor(i),o=e[0].type;if(0===t){let t=0;for(let n of e)s.set(n.data,t),t+=n.data.length}else{let i=0;for(let o=0;o<e.length;++o){let a=e[o];for(let e=0;e<a.data.length;++e){let o=0;for(let s=a.dims.length-1,u=e,c=1;s>=0;--s){let e=a.dims[s],f=u%e;s===t&&(f+=i),o+=f*c,c*=n[s],u=Math.floor(u/e)}s[o]=a.data[e]}i+=a.dims[t]}}return new Tensor(o,s,n)}function stack(e,t=0){return cat(e.map(e=>e.unsqueeze(t)),t)}function std_mean(e,t=null,n=1,i=!1){if(null===t){let t=e.data.reduce((e,t)=>e+t,0),i=t/e.data.length,s=Math.sqrt(e.data.reduce((e,t)=>e+(t-i)**2,0)/(e.data.length-n)),o=new Tensor(e.type,[i],[]),a=new Tensor(e.type,[s],[]);return[a,o]}t=safeIndex(t,e.dims.length);let s=mean(e,t,i),o=e.dims.slice();o[t]=1;let a=new e.data.constructor(e.data.length/e.dims[t]);for(let n=0;n<e.data.length;++n){let i=0;for(let s=e.dims.length-1,a=n,u=1;s>=0;--s){let n=e.dims[s];if(s!==t){let e=a%n;i+=e*u,u*=o[s]}a=Math.floor(a/n)}a[i]+=(e.data[n]-s.data[i])**2}for(let i=0;i<a.length;++i)a[i]=Math.sqrt(a[i]/(e.dims[t]-n));i||o.splice(t,1);let u=new Tensor(e.type,a,o);return[u,s]}function mean(e,t=null,n=!1){if(null===t){let t=e.data.reduce((e,t)=>e+t,0);return new Tensor(e.type,[t/e.data.length],[])}t=safeIndex(t,e.dims.length);let i=e.dims.slice();i[t]=1;let s=new e.data.constructor(e.data.length/e.dims[t]);for(let n=0;n<e.data.length;++n){let o=0;for(let s=e.dims.length-1,a=n,u=1;s>=0;--s){let n=e.dims[s];if(s!==t){let e=a%n;o+=e*u,u*=i[s]}a=Math.floor(a/n)}s[o]+=e.data[n]}if(1!==e.dims[t])for(let n=0;n<s.length;++n)s[n]=s[n]/e.dims[t];return n||i.splice(t,1),new Tensor(e.type,s,i)}function dynamicTimeWarping(e){let[t,n]=e.dims,i=[t+1,n+1],s=new Tensor("float32",new Float32Array(i[0]*i[1]).fill(1/0),i),o=new Tensor("float32",new Float32Array(i[0]*i[1]).fill(-1),i);s[0].data[0]=0;for(let i=1;i<n+1;++i)for(let n=1;n<t+1;++n){let t,a;let u=s[n-1][i-1].item(),c=s[n-1][i].item(),f=s[n][i-1].item();u<c&&u<f?(t=u,a=0):c<u&&c<f?(t=c,a=1):(t=f,a=2),s[n].data[i]=e[n-1][i-1].item()+t,o[n].data[i]=a}let a=t,u=n;o.data.fill(2,0,i[1]);for(let e=0;e<i[0];++e)o[e].data[0]=1;let c=[],f=[];for(;a>0||u>0;){c.push(a-1),f.push(u-1);let e=o[a][u].item();switch(e){case 0:--a,--u;break;case 1:--a;break;case 2:--u;break;default:throw Error(`Internal error in dynamic time warping. Unexpected trace[${a}, ${u}]. Please file a bug report.`)}}return c.reverse(),f.reverse(),[c,f]}function ones_like(e){return function(e){let t=e.reduce((e,t)=>e*t,1);return new Tensor("int64",new BigInt64Array(t).fill(1n),e)}(e.dims)}}}]);