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For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");let n=await (await (0,h.hn)(e)).arrayBuffer(),i=new AudioContext({sampleRate:t});void 0===t&&console.warn(`No sampling rate provided, using default of ${i.sampleRate}Hz.`);let s=await i.decodeAudioData(n);if(2===s.numberOfChannels){let e=Math.sqrt(2),t=s.getChannelData(0),n=s.getChannelData(1);r=new Float32Array(t.length);for(let i=0;i<s.length;++i)r[i]=e*(t[i]+n[i])/2}else r=s.getChannelData(0);return r}function v(e){if(e<1)return new Float64Array;if(1===e)return new Float64Array([1]);let t=e-1,r=Math.PI/t,n=new Float64Array(e);for(let i=0;i<e;++i){let e=2*i-t;n[i]=.5+.5*Math.cos(r*e)}return n}let b={htk:e=>2595*Math.log10(1+e/700),kaldi:e=>1127*Math.log(1+e/700),slaney:(e,t=1e3,r=15,n=27/Math.log(6.4))=>e>=t?r+Math.log(e/t)*n:3*e/200};function x(e,t="htk"){let r=b[t];if(!r)throw Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof e?r(e):e.map(e=>r(e))}let E={htk:e=>700*(10**(e/2595)-1),kaldi:e=>700*(Math.exp(e/1127)-1),slaney:(e,t=1e3,r=15,n=Math.log(6.4)/27)=>e>=r?t*Math.exp(n*(e-r)):200*e/3};function k(e,t,r){let n=(t-e)/(r-1);return Float64Array.from({length:r},(t,r)=>e+n*r)}function A(e,t,r,n,i,s=null,a="htk",o=!1){let l;if(null!==s&&"slaney"!==s)throw Error('norm must be one of null or "slaney"');let h=k(x(r,a),x(n,a),t+2),u=function(e,t="htk"){let r=E[t];if(!r)throw Error('mel_scale should be one of "htk", "slaney" or "kaldi".');return"number"==typeof e?r(e):e.map(e=>r(e))}(h,a);if(o){let t=i/(2*e);l=x(Float64Array.from({length:e},(e,r)=>r*t),a),u=h}else l=k(0,Math.floor(i/2),e);let c=function(e,t){let r=Float64Array.from({length:t.length-1},(e,r)=>t[r+1]-t[r]),n=Array.from({length:e.length},()=>Array(t.length));for(let r=0;r<e.length;++r){let i=n[r];for(let n=0;n<t.length;++n)i[n]=t[n]-e[r]}let i=t.length-2,s=Array.from({length:i},()=>Array(e.length));for(let t=0;t<e.length;++t){let e=n[t];for(let n=0;n<i;++n){let i=-e[n]/r[n],a=e[n+2]/r[n+1];s[n][t]=Math.max(0,Math.min(i,a))}}return s}(l,u);if(null!==s&&"slaney"===s)for(let r=0;r<t;++r){let t=c[r],n=2/(u[r+2]-u[r]);for(let r=0;r<e;++r)t[r]*=n}return c}function z(e,t,r,n,i){if(r<=0)throw Error("reference must be greater than zero");if(n<=0)throw Error("min_value must be greater than zero");let s=Math.log10(r=Math.max(n,r));for(let r=0;r<e.length;++r)e[r]=t*Math.log10(Math.max(n,e[r])-s);if(null!==i){if(i<=0)throw Error("db_range must be greater than zero");let t=(0,u.Fp)(e)[0]-i;for(let r=0;r<e.length;++r)e[r]=Math.max(e[r],t)}return e}function C(e,t,r,n,{fft_length:i=null,power:s=1,center:a=!0,pad_mode:o="reflect",onesided:h=!0,preemphasis:c=null,mel_filters:f=null,mel_floor:d=1e-10,log_mel:p=null,reference:m=1,min_value:g=1e-10,db_range:_=null,remove_dc_offset:w=null,max_num_frames:y=null,do_pad:v=!0,transpose:b=!1}={}){let x=t.length;if(null===i&&(i=r),r>i)throw Error(`frame_length (${r}) may not be larger than fft_length (${i})`);if(x!==r)throw Error(`Length of the window (${x}) must equal frame_length (${r})`);if(n<=0)throw Error("hop_length must be greater than zero");if(null===s&&null!==f)throw Error("You have provided `mel_filters` but `power` is `None`. Mel spectrogram computation is not yet supported for complex-valued spectrogram. Specify `power` to fix this issue.");if(a){if("reflect"!==o)throw Error(`pad_mode="${o}" not implemented yet.`);let t=Math.floor((i-1)/2)+1;e=function(e,t,r){let n=new e.constructor(e.length+t+r),i=e.length-1;for(let r=0;r<e.length;++r)n[t+r]=e[r];for(let r=1;r<=t;++r)n[t-r]=e[(0,l.hs)(r,i)];for(let s=1;s<=r;++s)n[i+t+s]=e[(0,l.hs)(i-s,i)];return n}(e,t,t)}let E=Math.floor(1+Math.floor((e.length-r)/n)),k=h?Math.floor(i/2)+1:i,A=E,C=E;null!==y&&(y>E?v&&(C=y):C=A=y);let M=new u.vw(i),I=new Float64Array(i),O=new Float64Array(M.outputBufferSize),S=Array(A);for(let i=0;i<A;++i){let s=i*n;for(let t=0;t<r;++t)I[t]=e[s+t];if(w){let e=0;for(let t=0;t<r;++t)e+=I[t];let t=e/r;for(let e=0;e<r;++e)I[e]-=t}if(null!==c){for(let e=r-1;e>=1;--e)I[e]-=c*I[e-1];I[0]*=1-c}for(let e=0;e<t.length;++e)I[e]*=t[e];M.realTransform(O,I);let a=Array(k);for(let e=0;e<a.length;++e){let t=e<<1;a[e]=O[t]**2+O[t+1]**2}S[i]=a}if(null!==s&&2!==s){let e=2/s;for(let t=0;t<S.length;++t){let r=S[t];for(let t=0;t<r.length;++t)r[t]**=e}}let $=f.length,T=new Float32Array($*C),B=b?[C,$]:[$,C];for(let e=0;e<$;++e){let t=f[e];for(let r=0;r<A;++r){let n=S[r],i=0;for(let e=0;e<k;++e)i+=t[e]*n[e];T[b?r*$+e:e*A+r]=Math.max(d,i)}}if(null!==s&&null!==p){let e=Math.min(T.length,A*$);switch(p){case"log":for(let t=0;t<e;++t)T[t]=Math.log(T[t]);break;case"log10":for(let t=0;t<e;++t)T[t]=Math.log10(T[t]);break;case"dB":if(1===s)!function(e,t=1,r=1e-5,n=null){z(e,20,t,r,n)}(T,m,g,_);else if(2===s)!function(e,t=1,r=1e-10,n=null){z(e,10,t,r,n)}(T,m,g,_);else throw Error(`Cannot use log_mel option '${p}' with power ${s}`);break;default:throw Error(`log_mel must be one of null, 'log', 'log10' or 'dB'. Got '${p}'`)}}return{data:T,dims:B}}function M(e,t,{periodic:r=!0,frame_length:n=null,center:i=!0}={}){let s;let a=r?e+1:e;switch(t){case"boxcar":s=new Float64Array(a).fill(1);break;case"hann":case"hann_window":s=v(a);break;case"povey":s=v(a).map(e=>Math.pow(e,.85));break;default:throw Error(`Unknown window type ${t}.`)}if(r&&(s=s.subarray(0,e)),null===n)return s;if(e>n)throw Error(`Length of the window (${e}) may not be larger than frame_length (${n})`);return s}function I(e,t=.5,r=null,n=!1){let i=e.logits,s=e.pred_boxes,[a,o,l]=i.dims;if(null!==r&&r.length!==a)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let h=[];for(let e=0;e<a;++e){let a=null!==r?r[e]:null,c={boxes:[],classes:[],scores:[]},f=i[e],d=s[e];for(let e=0;e<o;++e){let r,i=f[e],s=[];if(n){r=i.sigmoid().data;for(let e=0;e<r.length;++e)r[e]>t&&s.push(e)}else{let e=(0,u.Fp)(i.data)[1];if(e===l-1)continue;s.push(e),r=(0,u.XA)(i.data)}for(let t of s){let n=d[e].data;n=function([e,t,r,n]){return[e-r/2,t-n/2,e+r/2,t+n/2]}(n),null!==a&&(n=n.map((e,t)=>e*a[(t+1)%2])),c.boxes.push(n),c.classes.push(t),c.scores.push(r[t])}}h.push(c)}return h}function O(e,t){if(!(e instanceof Float32Array||e instanceof Float64Array))throw Error(`${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.`)}function S(e,t,r=0,n=null){let i=e/t,s=(0,u.eT)(i)*t;return null!==n&&s>n&&(s=Math.floor(i)*t),s<r&&(s=Math.ceil(i)*t),s}function $([e,t],r){return[Math.max(Math.floor(e/r),1)*r,Math.max(Math.floor(t/r),1)*r]}class T extends l.Ag{constructor(e){super(),this.config=e}}class B extends T{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),this.do_flip_channel_order=this.config.do_flip_channel_order??!1}async thumbnail(e,t,r=2){let n=e.height,i=e.width,s=t.height,a=t.width,o=Math.min(n,s),l=Math.min(i,a);return o===n&&l===i?e:(n>i?l=Math.floor(i*o/n):i>n&&(o=Math.floor(n*l/i)),await e.resize(l,o,{resample:r}))}async crop_margin(e,t=200){let r=e.clone().grayscale(),n=(0,u.VV)(r.data)[0],i=(0,u.Fp)(r.data)[0]-n;if(0===i)return e;let s=t/255,a=r.width,o=r.height,l=0,h=0;for(let e=0;e<r.height;++e){let t=e*r.width;for(let u=0;u<r.width;++u)(r.data[t+u]-n)/i<s&&(a=Math.min(a,u),o=Math.min(o,e),l=Math.max(l,u),h=Math.max(h,e))}return e=await e.crop([a,o,l,h])}pad_image(e,t,r,{mode:n="constant",center:i=!1,constant_values:s=0}={}){let a,o;let[h,u,c]=t;if("number"==typeof r?(a=r,o=r):(a=r.width,o=r.height),a!==u||o!==h){let r=new Float32Array(a*o*c);if(Array.isArray(s))for(let e=0;e<r.length;++e)r[e]=s[e%c];else 0!==s&&r.fill(s);let[f,d]=i?[Math.floor((a-u)/2),Math.floor((o-h)/2)]:[0,0];for(let t=0;t<h;++t){let n=(t+d)*a,i=t*u;for(let t=0;t<u;++t){let s=(n+t+f)*c,a=(i+t)*c;for(let t=0;t<c;++t)r[s+t]=e[a+t]}}if("symmetric"===n){if(i)throw Error("`center` padding is not supported when `mode` is set to `symmetric`.");let t=h-1,n=u-1;for(let i=0;i<o;++i){let s=i*a,o=(0,l.hs)(i,t)*u;for(let t=0;t<a;++t){if(i<h&&t<u)continue;let a=(s+t)*c,f=(o+(0,l.hs)(t,n))*c;for(let t=0;t<c;++t)r[a+t]=e[f+t]}}}e=r,t=[o,a,c]}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 r,n;let[i,s]=e.size;if(this.do_thumbnail){let{height:e,width:n}=t;r=Math.min(e,n)}else Number.isInteger(t)?(r=t,n=this.config.max_size??r):void 0!==t&&(r=t.shortest_edge,n=t.longest_edge);if(void 0!==r||void 0!==n){let e=void 0===r?1:Math.max(r/i,r/s),t=i*e,a=s*e,o=void 0===n?1:Math.min(n/t,n/a),l=Math.floor(Number((t*o).toFixed(2))),h=Math.floor(Number((a*o).toFixed(2)));return void 0!==this.size_divisibility&&([l,h]=$([l,h],this.size_divisibility)),[l,h]}if(void 0!==t&&void 0!==t.width&&void 0!==t.height){let e=t.width,r=t.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let t=r/s,n=e/i;Math.abs(1-n)<Math.abs(1-t)?t=n:n=t,r=S(t*s,this.config.ensure_multiple_of),e=S(n*i,this.config.ensure_multiple_of)}return[e,r]}if(void 0!==this.size_divisibility)return $([i,s],this.size_divisibility);throw Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(t)}`)}async resize(e){let[t,r]=this.get_resize_output_image_size(e,this.size);return await e.resize(t,r,{resample:this.resample})}async preprocess(e,{do_normalize:t=null,do_pad:r=null,do_convert_rgb:n=null,do_convert_grayscale:i=null,do_flip_channel_order:s=null}={}){this.do_crop_margin&&(e=await this.crop_margin(e));let[a,o]=e.size;if(n??this.do_convert_rgb?e=e.rgb():i&&(e=e.grayscale()),this.do_resize&&(e=await this.resize(e)),this.do_thumbnail&&(e=await this.thumbnail(e,this.size,this.resample)),this.do_center_crop){let t,r;Number.isInteger(this.crop_size)?(t=this.crop_size,r=this.crop_size):(t=this.crop_size.width,r=this.crop_size.height),e=await e.center_crop(t,r)}let l=[e.height,e.width],h=Float32Array.from(e.data),u=[e.height,e.width,e.channels];if(this.do_rescale&&this.rescale(h),t??this.do_normalize){let t=this.image_mean;Array.isArray(this.image_mean)||(t=Array(e.channels).fill(t));let r=this.image_std;if(Array.isArray(this.image_std)||(r=Array(e.channels).fill(t)),t.length!==e.channels||r.length!==e.channels)throw Error(`When set to arrays, the length of \`image_mean\` (${t.length}) and \`image_std\` (${r.length}) must match the number of channels in the image (${e.channels}).`);for(let n=0;n<h.length;n+=e.channels)for(let i=0;i<e.channels;++i)h[n+i]=(h[n+i]-t[i])/r[i]}if(r??this.do_pad){if(this.pad_size){let t=this.pad_image(h,[e.height,e.width,e.channels],this.pad_size);[h,u]=t}else if(this.size_divisibility){let[e,t]=$([u[1],u[0]],this.size_divisibility);[h,u]=this.pad_image(h,u,{width:e,height:t})}}if(s??this.do_flip_channel_order){if(3!==u[2])throw Error("Flipping channel order is only supported for RGB images.");for(let e=0;e<h.length;e+=3){let t=h[e];h[e]=h[e+2],h[e+2]=t}}return{original_size:[o,a],reshaped_input_size:l,pixel_values:new c.es("float32",h,u).permute(2,0,1)}}async _call(e,...t){Array.isArray(e)||(e=[e]);let r=await Promise.all(e.map(e=>this.preprocess(e)));return{pixel_values:(0,c.kn)(r.map(e=>e.pixel_values),0),original_sizes:r.map(e=>e.original_size),reshaped_input_sizes:r.map(e=>e.reshaped_input_size)}}}class U extends B{post_process_semantic_segmentation(e,t=null){let r=e.logits,n=r.dims[0];if(null!==t&&t.length!==n)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let i=[];for(let e=0;e<n;++e){let n=null!==t?t[e]:null,s=r[e];null!==n&&(s=(0,c.sX)(s,n,"bilinear",!1));let[a,o]=n??s.dims.slice(-2),l=new c.es("int32",new Int32Array(a*o),[a,o]),h=s[0].data;for(let e=1;e<s.dims[0];++e){let t=s[e].data;for(let r=0;r<t.length;++r)t[r]>h[r]&&(h[r]=t[r],l.data[r]=e)}let u=Array(s.dims[0]),f=l.data;for(let e=0;e<f.length;++e){let t=f[e];u[t]=t}let d=u.filter(e=>void 0!==e);i.push({segmentation:l,labels:d})}return i}}class F extends B{}class j extends F{}class L extends B{}class N extends B{}class R extends B{}class P extends B{}class q extends B{}class X extends B{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 r=Math.floor(t/this.crop_pct),[n,i]=this.get_resize_output_image_size(e,{shortest_edge:r});e=await e.resize(n,i,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}}class V extends X{}class D extends B{}class G extends B{}class H extends B{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(e=>e*e))}}class W extends B{}class K extends W{}class J extends B{post_process_object_detection(...e){return I(...e)}}class Y extends J{}class Z extends B{}class Q extends B{}class ee extends B{pad_image(e,t,r,n={}){let[i,s,a]=t,o=this.image_mean;Array.isArray(this.image_mean)||(o=Array(a).fill(o));let l=this.image_std;Array.isArray(l)||(l=Array(a).fill(o));let h=o.map((e,t)=>-e/l[t]);return super.pad_image(e,t,r,{center:!0,constant_values:h,...n})}}class et extends ee{}class er extends B{async _call(e){let t=await super._call(e),r=[t.pixel_values.dims[0],64,64],n=new c.es("int64",new BigInt64Array(r.reduce((e,t)=>e*t)).fill(1n),r);return{...t,pixel_mask:n}}post_process_object_detection(...e){return I(...e)}remove_low_and_no_objects(e,t,r,n){let i=[],s=[],a=[];for(let o=0;o<e.dims[0];++o){let l=e[o],h=t[o],c=(0,u.Fp)(l.data)[1];if(c===n)continue;let f=(0,u.XA)(l.data)[c];f>r&&(i.push(h),s.push(f),a.push(c))}return[i,s,a]}check_segment_validity(e,t,r,n=.5,i=.8){let s=[],a=0,o=0;for(let i=0;i<e.length;++i)e[i]===r&&(s.push(i),++a),t[r].data[i]>=n&&++o;let l=a>0&&o>0;return l&&(l=a/o>i),[l,s]}compute_segments(e,t,r,n,i,s=null,a=null){let[o,l]=a??e[0].dims,h=new c.es("int32",new Int32Array(o*l),[o,l]),u=[];if(null!==a)for(let t=0;t<e.length;++t)e[t]=(0,c.sX)(e[t],a,"bilinear",!1);let f=new Int32Array(e[0].data.length),d=new Float32Array(e[0].data.length);for(let r=0;r<e.length;++r){let n=t[r];for(let t=0;t<e[r].data.length;++t)e[r].data[t]*=n,e[r].data[t]>d[t]&&(f[t]=r,d[t]=e[r].data[t])}let p=0;for(let s=0;s<r.length;++s){let a=r[s],[o,l]=this.check_segment_validity(f,e,s,n,i);if(o){for(let e of(++p,l))h.data[e]=p;u.push({id:p,label_id:a,score:t[s]})}}return[h,u]}post_process_panoptic_segmentation(e,t=.5,r=.5,n=.8,i=null,s=null){null===i&&(console.warn("`label_ids_to_fuse` unset. No instance will be fused."),i=new Set);let a=e.logits,o=e.pred_masks.sigmoid(),[l,h,u]=a.dims;if(u-=1,null!==s&&s.length!==l)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<l;++e){let l=null!==s?s[e]:null,h=a[e],d=o[e],[p,m,g]=this.remove_low_and_no_objects(h,d,t,u);if(0===g.length){let[e,t]=l??d.dims.slice(-2),r=new c.es("int32",new Int32Array(e*t).fill(-1),[e,t]);f.push({segmentation:r,segments_info:[]});continue}let[_,w]=this.compute_segments(p,m,g,r,n,i,l);f.push({segmentation:_,segments_info:w})}return f}post_process_instance_segmentation(){throw Error("Not implemented yet")}}class en extends B{post_process_object_detection(...e){return I(...e)}}class ei extends B{reshape_input_points(e,t,r){e=structuredClone(e);let n=(0,l.jg)(e);if(3===n.length)n=[1,...n],e=[e];else if(4!==n.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 n=0;n<e.length;++n){let i=t[n],s=r[n],a=[s[0]/i[0],s[1]/i[1]];for(let t=0;t<e[n].length;++t)for(let r=0;r<e[n][t].length;++r)for(let i=0;i<e[n][t][r].length;++i)e[n][t][r][i]*=a[i]}return new c.es("float32",Float32Array.from(e.flat(1/0)),n)}add_input_labels(e,t){let r=(0,l.jg)(e);if(2===r.length)r=[1,...r],e=[e];else if(3!==r.length)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(r.some((e,r)=>e!==t.dims[r]))throw Error(`The first ${r.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new c.es("int64",e.flat(1/0).map(BigInt),r)}async _call(e,t=null,r=null){let n=await super._call(e);if(t&&(n.input_points=this.reshape_input_points(t,n.original_sizes,n.reshaped_input_sizes)),r){if(!n.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");n.input_labels=this.add_input_labels(r,n.input_points)}return n}post_process_masks(e,t,r,{mask_threshold:n=0,binarize:i=!0,pad_size:s=null}={}){let a=[],o=[(s=s??this.pad_size).height,s.width];for(let s=0;s<t.length;++s){let l=t[s],h=r[s],u=e[s],f=[];for(let e=0;e<u.dims[0];++e){let t=u[e],r=(0,c.sX)(t,o,"bilinear",!1);if(r=r.slice(null,[0,h[0]],[0,h[1]]),r=(0,c.sX)(r,l,"bilinear",!1),i){let e=new Uint8Array(r.data.length);for(let t=0;t<r.data.length;++t)r.data[t]>n&&(e[t]=1);r=new c.es("bool",e,r.dims)}f.push(r)}a.push((0,c.kn)(f))}return a}}class es extends B{pad_image(e,t,r,n={}){let[i,s,a]=t;return super.pad_image(e,t,{width:s+(r-s%r)%r,height:i+(r-i%r)%r},{mode:"symmetric",center:!1,constant_values:-1,...n})}}class ea extends B{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);let r=await Promise.all(e.map(e=>this.preprocess(e))),n=await Promise.all(t.map(e=>this.preprocess(e,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:(0,c.kn)(r.map((e,t)=>(0,c.d3)([e.pixel_values,n[t].pixel_values],0)),0),original_sizes:r.map(e=>e.original_size),reshaped_input_sizes:r.map(e=>e.reshaped_input_size)}}}class eo extends T{constructor(e){super(e),this.config.mel_filters??=A(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney"),this.window=M(this.config.n_fft,"hann")}_extract_fbank_features(e){let{data:t,dims:r}=C(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}),n=(0,u.Fp)(t)[0];for(let e=0;e<t.length;++e)t[e]=(Math.max(t[e],n-8)+4)/4;return{data:t,dims:r}}async _call(e){let t;O(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:r,dims:n}=this._extract_fbank_features(t);return{input_features:new c.es("float32",r,[1,...n])}}}class el extends T{_zero_mean_unit_var_norm(e){let t=e.reduce((e,t)=>e+t,0)/e.length,r=e.reduce((e,r)=>e+(r-t)**2,0)/e.length;return e.map(e=>(e-t)/Math.sqrt(r+1e-7))}async _call(e){O(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 r=[1,t.length];return{input_values:new c.es("float32",t,r),attention_mask:new c.es("int64",new BigInt64Array(t.length).fill(1n),r)}}}class eh extends T{constructor(e){super(e);let t=this.config.sampling_rate,r=A(256,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);for(let e=0;e<r.length;++e)r[e].push(0);this.mel_filters=r,this.window=M(400,"povey",{periodic:!1})}_extract_fbank_features(e,t){return C(e=e.map(e=>32768*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,{padding:t=!0,pad_to_multiple_of:r=2,do_normalize_per_mel_bins:n=!0,return_attention_mask:i=!0}={}){let s;O(e,"SeamlessM4TFeatureExtractor");let a=this._extract_fbank_features(e,this.config.max_length);if(n){let[e,t]=a.dims;for(let r=0;r<t;++r){let n=0;for(let i=0;i<e;++i)n+=a.data[i*t+r];let i=n/e,s=0;for(let n=0;n<e;++n)s+=(a.data[n*t+r]-i)**2;let o=Math.sqrt((s/=e-1)+1e-7);for(let n=0;n<e;++n){let e=n*t+r;a.data[e]=(a.data[e]-i)/o}}}if(t){let[e,t]=a.dims,n=e%r;if(n>0){let r=new Float32Array(t*(e+n));r.set(a.data),r.fill(this.config.padding_value,a.data.length);let o=e+n;a={data:r,dims:[o,t]},i&&(s=new c.es("int64",new BigInt64Array(o),[1,o])).data.fill(1n,0,e)}}let[o,l]=a.dims,h=this.config.stride;if(0!=o%h)throw Error(`The number of frames (${o}) must be a multiple of the stride (${h}).`);let u=new c.es("float32",a.data,a.dims).view(1,Math.floor(o/h),l*h),f={input_features:u};if(i){let e=u.dims[1],t=new c.es("int64",new BigInt64Array(e),[1,e]);if(s)for(let e=1,r=0;e<o;e+=h,++r)t.data[r]=s.data[e];else t.data.fill(1n);f.attention_mask=t}return f}}class eu extends T{constructor(e){super(e);let t=this.config.sampling_rate,r=A(256,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);for(let e=0;e<r.length;++e)r[e].push(0);this.mel_filters=r,this.window=M(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}_extract_fbank_features(e,t){return C(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){O(e,"ASTFeatureExtractor");let t=this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){let e=2*this.std;for(let r=0;r<t.data.length;++r)t.data[r]=(t.data[r]-this.mean)/e}return{input_values:new c.es("float32",t.data,[1,...t.dims])}}}class ec extends T{constructor(e){super(e),this.mel_filters=A(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,null,"htk"),this.mel_filters_slaney=A(this.config.nb_frequency_bins,this.config.feature_size,this.config.frequency_min,this.config.frequency_max,this.config.sampling_rate,"slaney","slaney"),this.window=M(this.config.fft_window_size,"hann")}_get_input_mel(e,t,r,n){let i;let s=!1,a=e.length-t;if(a>0){if("rand_trunc"===r){s=!0;let r=Math.floor(Math.random()*(a+1));e=e.subarray(r,r+t),(i=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)).dims=[1,...i.dims]}else throw Error(`Truncation strategy "${r}" not implemented`)}else{if(a<0){let r=new Float64Array(t);if(r.set(e),"repeat"===n)for(let n=e.length;n<t;n+=e.length)r.set(e.subarray(0,Math.min(e.length,t-n)),n);else if("repeatpad"===n)for(let t=e.length;t<-a;t+=e.length)r.set(e,t);e=r}if("fusion"===r)throw Error(`Truncation strategy "${r}" not implemented`);(i=this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)).dims=[1,...i.dims]}return{...i,longer:s}}_extract_fbank_features(e,t,r=null){return C(e,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:t,log_mel:"dB",max_num_frames:r,do_pad:!1,transpose:!0})}async _call(e,{max_length:t=null}={}){O(e,"ClapFeatureExtractor");let r=this._get_input_mel(e,t??this.config.nb_max_samples,this.config.truncation,this.config.padding);return{input_features:new c.es("float32",r.data,[1,...r.dims])}}}class ef extends T{}class ed extends l.Ag{constructor(e){super(),this.feature_extractor=e}async _call(e,...t){return await this.feature_extractor(e,...t)}}class ep extends ed{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)}}class em extends ed{async _call(e){return await this.feature_extractor(e)}}class eg extends ed{async _call(e){return await this.feature_extractor(e)}}class e_ extends ed{async _call(e){return await this.feature_extractor(e)}}class ew extends ed{}class ey{static FEATURE_EXTRACTOR_CLASS_MAPPING={ImageFeatureExtractor:B,WhisperFeatureExtractor:eo,ViTFeatureExtractor:D,MobileViTFeatureExtractor:W,MobileViTImageProcessor:K,OwlViTFeatureExtractor:J,Owlv2ImageProcessor:Y,CLIPFeatureExtractor:R,ChineseCLIPFeatureExtractor:P,SiglipImageProcessor:q,ConvNextFeatureExtractor:X,ConvNextImageProcessor:V,SegformerFeatureExtractor:U,BitImageProcessor:L,DPTImageProcessor:j,DPTFeatureExtractor:F,GLPNFeatureExtractor:N,BeitFeatureExtractor:Q,DeiTFeatureExtractor:Z,DetrFeatureExtractor:er,YolosFeatureExtractor:en,DonutFeatureExtractor:ee,NougatImageProcessor:et,EfficientNetImageProcessor:H,ViTImageProcessor:G,VitMatteImageProcessor:ea,SamImageProcessor:ei,Swin2SRImageProcessor:es,Wav2Vec2FeatureExtractor:el,SeamlessM4TFeatureExtractor:eh,SpeechT5FeatureExtractor:ef,ASTFeatureExtractor:eu,ClapFeatureExtractor:ec};static PROCESSOR_CLASS_MAPPING={WhisperProcessor:em,Wav2Vec2ProcessorWithLM:eg,SamProcessor:ep,SpeechT5Processor:e_,OwlViTProcessor:ew};static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:n=null,local_files_only:i=!1,revision:s="main"}={}){let a=r??await (0,h.yM)(e,"preprocessor_config.json",!0,{progress_callback:t,config:r,cache_dir:n,local_files_only:i,revision:s}),o=a.feature_extractor_type??a.image_processor_type,l=this.FEATURE_EXTRACTOR_CLASS_MAPPING[o];if(!l){if(void 0!==a.size)console.warn(`Feature extractor type "${o}" not found, assuming ImageFeatureExtractor due to size parameter in config.`),l=B;else throw Error(`Unknown Feature Extractor type: ${o}`)}return new(this.PROCESSOR_CLASS_MAPPING[a.processor_class]??ed)(new l(a))}}async function ev(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>w.read(e)))}async function eb(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>"string"==typeof e||e instanceof URL?y(e,t):e instanceof Float64Array?new Float32Array(e):e))}function ex(e,t){t&&(e=e.map(e=>0|e));let[r,n,i,s]=e;return{xmin:r,ymin:n,xmax:i,ymax:s}}class eE extends l.Ag{constructor({task:e,model:t,tokenizer:r=null,processor:n=null}){super(),this.task=e,this.model=t,this.tokenizer=r,this.processor=n}async dispose(){await this.model.dispose()}}class ek extends eE{constructor(e){super(e)}async _call(e,{topk:t=1}={}){let r=this.tokenizer(e,{padding:!0,truncation:!0}),n=await this.model(r),i="multi_label_classification"===this.model.config.problem_type?e=>e.sigmoid().data:e=>(0,u.XA)(e.data),s=this.model.config.id2label,a=[];for(let e of n.logits){let r=i(e),n=(0,u.em)(r,t).map(e=>({label:s[e[0]],score:e[1]}));1===t?a.push(...n):a.push(n)}return Array.isArray(e)||1===t?a:a[0]}}class eA extends eE{constructor(e){super(e)}async _call(e,{ignore_labels:t=["O"]}={}){let r=Array.isArray(e),n=this.tokenizer(r?e:[e],{padding:!0,truncation:!0}),i=(await this.model(n)).logits,s=this.model.config.id2label,a=[];for(let e=0;e<i.dims[0];++e){let r=n.input_ids[e],o=i[e],l=[];for(let e=0;e<o.dims[0];++e){let n=o[e],i=(0,u.Fp)(n.data)[1],a=s?s[i]:`LABEL_${i}`;if(t.includes(a))continue;let h=this.tokenizer.decode([r[e].item()],{skip_special_tokens:!0});if(""===h)continue;let c=(0,u.XA)(n.data);l.push({entity:a,score:c[i],index:e,word:h,start:null,end:null})}a.push(l)}return r?a:a[0]}}class ez extends eE{constructor(e){super(e)}async _call(e,t,{topk:r=1}={}){let n=this.tokenizer(e,{text_pair:t,padding:!0,truncation:!0}),i=await this.model(n),s=[];for(let e=0;e<i.start_logits.dims[0];++e){let t=n.input_ids[e],a=t.indexOf(this.tokenizer.sep_token_id),o=Array.from((0,u.XA)(i.start_logits[e].data)).map((e,t)=>[e,t]).filter(e=>e[1]>a),h=Array.from((0,u.XA)(i.end_logits[e].data)).map((e,t)=>[e,t]).filter(e=>e[1]>a),c=(0,l.O7)(o,h).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(c.length,r);++e){let[r,n,i]=c[e],a=[...t].slice(r,n+1),o=this.tokenizer.decode(a,{skip_special_tokens:!0});s.push({answer:o,score:i})}}return 1===r?s[0]:s}}class eC extends eE{constructor(e){super(e)}async _call(e,{topk:t=5}={}){let r=this.tokenizer(e,{padding:!0,truncation:!0}),n=await this.model(r),i=[];for(let e=0;e<r.input_ids.dims[0];++e){let s=r.input_ids[e],a=s.indexOf(this.tokenizer.mask_token_id);if(-1===a)throw Error(`Mask token (${this.tokenizer.mask_token}) not found in text.`);let o=n.logits[e][a],l=(0,u.em)((0,u.XA)(o.data),t);i.push(l.map(e=>{let t=[...s];return t[a]=e[0],{score:e[1],token:e[0],token_str:this.tokenizer.model.vocab[e[0]],sequence:this.tokenizer.decode(t,{skip_special_tokens:!0})}}))}return Array.isArray(e)?i:i[0]}}class eM extends eE{_key="generated_text";constructor(e){super(e)}async _call(e,t={}){let r;Array.isArray(e)||(e=[e]),this.model.config.prefix&&(e=e.map(e=>this.model.config.prefix+e));let n=this.model.config.task_specific_params;n&&n[this.task]&&n[this.task].prefix&&(e=e.map(e=>n[this.task].prefix+e));let i=this.tokenizer,s={padding:!0,truncation:!0};r=this instanceof eO&&"_build_translation_inputs"in i?i._build_translation_inputs(e,s,t).input_ids:i(e,s).input_ids;let a=await this.model.generate(r,t);return i.batch_decode(a,{skip_special_tokens:!0}).map(e=>({[this._key]:e}))}}class eI extends eM{_key="summary_text";constructor(e){super(e)}}class eO extends eM{_key="translation_text";constructor(e){super(e)}}function eS(e){return Array.isArray(e)&&e.every(e=>"role"in e&&"content"in e)}class e$ extends eE{constructor(e){super(e)}async _call(e,t={}){let r,n,i=!1,s=!1;if("string"==typeof e)r=e=[e];else if(Array.isArray(e)&&e.every(e=>"string"==typeof e))i=!0,r=e;else{if(eS(e))e=[e];else if(Array.isArray(e)&&e.every(eS))i=!0;else throw Error("Input must be a string, an array of strings, a Chat, or an array of Chats");s=!0,r=e.map(e=>this.tokenizer.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0}))}let a=t.add_special_tokens??!1,o=!s&&(t.return_full_text??!0);this.tokenizer.padding_side="left";let{input_ids:l,attention_mask:h}=this.tokenizer(r,{add_special_tokens:a,padding:!0,truncation:!0}),u=await this.model.generate(l,t,null,{inputs_attention_mask:h}),c=this.tokenizer.batch_decode(u,{skip_special_tokens:!0});!o&&l.dims.at(-1)>0&&(n=this.tokenizer.batch_decode(l,{skip_special_tokens:!0}).map(e=>e.length));let f=Array.from({length:e.length},e=>[]);for(let t=0;t<c.length;++t){let r=Math.floor(t/u.length*e.length);n&&(c[t]=c[t].slice(n[r])),f[r].push({generated_text:s?[...e[r],{role:"assistant",content:c[t]}]:c[t]})}return i||1!==f.length?f:f[0]}}class eT extends eE{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:r="This example is {}.",multi_label:n=!1}={}){let i=Array.isArray(e);i||(e=[e]),Array.isArray(t)||(t=[t]);let s=t.map(e=>r.replace("{}",e)),a=n||1===t.length,o=[];for(let r of e){let e=[];for(let t of s){let n=this.tokenizer(r,{text_pair:t,padding:!0,truncation:!0}),i=await this.model(n);a?e.push([i.logits.data[this.contradiction_id],i.logits.data[this.entailment_id]]):e.push(i.logits.data[this.entailment_id])}let n=(a?e.map(e=>(0,u.XA)(e)[1]):(0,u.XA)(e)).map((e,t)=>[e,t]).sort((e,t)=>t[0]-e[0]);o.push({sequence:r,labels:n.map(e=>t[e[1]]),scores:n.map(e=>e[0])})}return i?o:o[0]}}class eB extends eE{constructor(e){super(e)}async _call(e,{pooling:t="none",normalize:r=!1,quantize:n=!1,precision:i="binary"}={}){let s=this.tokenizer(e,{padding:!0,truncation:!0}),a=await this.model(s),o=a.last_hidden_state??a.logits??a.token_embeddings;if("none"===t);else if("mean"===t)o=(0,c.v6)(o,s.attention_mask);else if("cls"===t)o=o.slice(null,0);else throw Error(`Pooling method '${t}' not supported.`);return r&&(o=o.normalize(2,-1)),n&&(o=(0,c.e)(o,i)),o}}class eU extends eE{constructor(e){super(e)}async _call(e,{pool:t=null}={}){let r;let n=await ev(e),{pixel_values:i}=await this.processor(n),s=await this.model({pixel_values:i});if(t){if(!("pooler_output"in s))throw Error("No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.");r=s.pooler_output}else r=s.last_hidden_state??s.logits??s.image_embeds;return r}}class eF extends eE{constructor(e){super(e)}async _call(e,{topk:t=null}={}){let r=!Array.isArray(e),n=this.processor.feature_extractor.config.sampling_rate,i=await eb(e,n),s=this.model.config.id2label,a=[];for(let e of i){let r=await this.processor(e),n=(await this.model(r)).logits[0],i=(0,u.em)((0,u.XA)(n.data),t).map(e=>({label:s[e[0]],score:e[1]}));1===t?a.push(...i):a.push(i)}return r&&1!==t?a[0]:a}}class ej extends eE{constructor(e){super(e)}async _call(e,t,{hypothesis_template:r="This is a sound of {}."}={}){let n=!Array.isArray(e);n&&(e=[e]);let i=t.map(e=>r.replace("{}",e)),s=this.tokenizer(i,{padding:!0,truncation:!0}),a=this.processor.feature_extractor.config.sampling_rate,o=await eb(e,a),l=[];for(let e of o){let r=await this.processor(e),n=await this.model({...s,...r}),i=(0,u.XA)(n.logits_per_audio.data);l.push([...i].map((e,r)=>({score:e,label:t[r]})))}return n?l[0]:l}}class eL extends eE{constructor(e){super(e)}async _call(e,t={}){switch(this.model.config.model_type){case"whisper":return this._call_whisper(e,t);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":return this._call_wav2vec2(e,t);default:throw Error(`AutomaticSpeechRecognitionPipeline does not support model type '${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 r=!Array.isArray(e);r&&(e=[e]);let n=this.processor.feature_extractor.config.sampling_rate,i=await eb(e,n),s=[];for(let e of i){let t=await this.processor(e),r=(await this.model(t)).logits[0],n=[];for(let e of r)n.push((0,u.Fp)(e.data)[1]);let i=this.tokenizer.decode(n);s.push({text:i})}return r?s[0]:s}async _call_whisper(e,t={}){let r=t.return_timestamps??!1,n=t.chunk_length_s??0,i=t.chunk_callback??null,s=t.force_full_sequences??!1,a=t.stride_length_s??null;"word"===r&&(t.return_token_timestamps=!0);let o=(0,l.Sw)(t,"language",null),h=(0,l.Sw)(t,"task",null);if(o||h||r){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:o,task:h,no_timestamps:!r});e.length>0&&(t.forced_decoder_ids=e)}let c=!Array.isArray(e);c&&(e=[e]);let f=this.processor.feature_extractor.config.chunk_length/this.model.config.max_source_positions,d=this.processor.feature_extractor.config.hop_length,p=this.processor.feature_extractor.config.sampling_rate,m=await eb(e,p),g=[];for(let e of m){let o=[];if(n>0){if(null===a)a=n/6;else if(n<=a)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");let t=p*n,r=p*a,i=t-2*r,s=0;for(;s<e.length;){let n=e.subarray(s,s+t),a=await this.processor(n),l=0===s,h=s+i>=e.length;o.push({stride:[n.length,l?0:r,h?0:r],input_features:a.input_features,is_last:h}),s+=i}}else o=[{stride:[e.length,0,0],input_features:(await this.processor(e)).input_features,is_last:!0}];for(let e of o){t.num_frames=Math.floor(e.stride[0]/d);let n=await this.model.generate(e.input_features,t);"word"===r?(e.tokens=n.sequences[0],e.token_timestamps=n.token_timestamps.tolist()[0].map(e=>(0,u.NM)(e,2))):e.tokens=n[0],e.stride=e.stride.map(e=>e/p),null!==i&&i(e)}let[l,h]=this.tokenizer._decode_asr(o,{time_precision:f,return_timestamps:r,force_full_sequences:s});g.push({text:l,...h})}return c?g[0]:g}}class eN extends eE{constructor(e){super(e)}async _call(e,t={}){let r=Array.isArray(e),n=await ev(e),{pixel_values:i}=await this.processor(n),s=[];for(let e of i){e.dims=[1,...e.dims];let r=await this.model.generate(e,t),n=this.tokenizer.batch_decode(r,{skip_special_tokens:!0}).map(e=>({generated_text:e.trim()}));s.push(n)}return r?s:s[0]}}class eR extends eE{constructor(e){super(e)}async _call(e,{topk:t=1}={}){let r=Array.isArray(e),n=await ev(e),{pixel_values:i}=await this.processor(n),s=await this.model({pixel_values:i}),a=this.model.config.id2label,o=[];for(let e of s.logits){let r=(0,u.em)((0,u.XA)(e.data),t).map(e=>({label:a[e[0]],score:e[1]}));1===t?o.push(...r):o.push(r)}return r||1===t?o:o[0]}}class eP extends eE{constructor(e){super(e),this.subtasks_mapping={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"}}async _call(e,{threshold:t=.5,mask_threshold:r=.5,overlap_mask_area_threshold:n=.8,label_ids_to_fuse:i=null,target_sizes:s=null,subtask:a=null}={}){if(Array.isArray(e)&&1!==e.length)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");let o=await ev(e),l=o.map(e=>[e.height,e.width]),{pixel_values:h,pixel_mask:u}=await this.processor(o),c=await this.model({pixel_values:h,pixel_mask:u}),f=null;if(null!==a)f=this.subtasks_mapping[a];else for(let[e,t]of Object.entries(this.subtasks_mapping))if(t in this.processor.feature_extractor){f=this.processor.feature_extractor[t].bind(this.processor.feature_extractor),a=e;break}let d=this.model.config.id2label,p=[];if("panoptic"===a||"instance"===a){let e=f(c,t,r,n,i,s??l)[0],a=e.segmentation;for(let t of e.segments_info){let e=new Uint8ClampedArray(a.data.length);for(let r=0;r<a.data.length;++r)a.data[r]===t.id&&(e[r]=255);let r=new w(e,a.dims[1],a.dims[0],1);p.push({score:t.score,label:d[t.label_id],mask:r})}}else if("semantic"===a){let{segmentation:e,labels:t}=f(c,s??l)[0];for(let r of t){let t=new Uint8ClampedArray(e.data.length);for(let n=0;n<e.data.length;++n)e.data[n]===r&&(t[n]=255);let n=new w(t,e.dims[1],e.dims[0],1);p.push({score:null,label:d[r],mask:n})}}else throw Error(`Subtask ${a} not supported.`);return p}}class eq extends eE{constructor(e){super(e)}async _call(e,t,{hypothesis_template:r="This is a photo of {}"}={}){let n=Array.isArray(e),i=await ev(e),s=t.map(e=>r.replace("{}",e)),a=this.tokenizer(s,{padding:"siglip"!==this.model.config.model_type||"max_length",truncation:!0}),{pixel_values:o}=await this.processor(i),l=await this.model({...a,pixel_values:o}),h="siglip"===this.model.config.model_type?e=>e.sigmoid().data:e=>(0,u.XA)(e.data),c=[];for(let e of l.logits_per_image){let r=[...h(e)].map((e,r)=>({score:e,label:t[r]}));r.sort((e,t)=>t.score-e.score),c.push(r)}return n?c:c[0]}}class eX extends eE{constructor(e){super(e)}async _call(e,{threshold:t=.9,percentage:r=!1}={}){let n=Array.isArray(e);if(n&&1!==e.length)throw Error("Object detection pipeline currently only supports a batch size of 1.");let i=await ev(e),s=r?null:i.map(e=>[e.height,e.width]),{pixel_values:a,pixel_mask:o}=await this.processor(i),l=await this.model({pixel_values:a,pixel_mask:o}),h=this.processor.feature_extractor.post_process_object_detection(l,t,s),u=this.model.config.id2label,c=h.map(e=>e.boxes.map((t,n)=>({score:e.scores[n],label:u[e.classes[n]],box:ex(t,!r)})));return n?c:c[0]}}class eV extends eE{constructor(e){super(e)}async _call(e,t,{threshold:r=.1,topk:n=null,percentage:i=!1}={}){let s=Array.isArray(e),a=await ev(e),o=this.tokenizer(t,{padding:!0,truncation:!0}),l=await this.processor(a),h=[];for(let e=0;e<a.length;++e){let s=a[e],u=i?null:[[s.height,s.width]],c=l.pixel_values[e].unsqueeze_(0),f=await this.model({...o,pixel_values:c}),d=this.processor.feature_extractor.post_process_object_detection(f,r,u,!0)[0],p=d.boxes.map((e,r)=>({score:d.scores[r],label:t[d.classes[r]],box:ex(e,!i)})).sort((e,t)=>t.score-e.score);null!==n&&(p=p.slice(0,n)),h.push(p)}return s?h:h[0]}}class eD extends eE{constructor(e){super(e)}async _call(e,t,r={}){let n=(await ev(e))[0],{pixel_values:i}=await this.processor(n),s=`<s_docvqa><s_question>${t}</s_question><s_answer>`,a=this.tokenizer(s,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,o=await this.model.generate(i,{...r,decoder_input_ids:a,max_length:this.model.config.decoder.max_position_embeddings}),l=this.tokenizer.batch_decode(o)[0].match(/<s_answer>(.*?)<\/s_answer>/),h=null;return l&&l.length>=2&&(h=l[1].trim()),[{answer:h}]}}class eG extends eE{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:r}=await this.model(t),n=this.model.config.sampling_rate;return{audio:r.data,sampling_rate:n}}async _call_text_to_spectrogram(e,{speaker_embeddings:t}){if(this.vocoder||(console.log("No vocoder specified, using default HifiGan vocoder."),this.vocoder=await o.$Sz.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),("string"==typeof t||t instanceof URL)&&(t=new Float32Array(await (await fetch(t)).arrayBuffer())),t instanceof Float32Array)t=new c.es("float32",t,[1,t.length]);else if(!(t instanceof c.es))throw Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");let{input_ids:r}=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:n}=await this.model.generate_speech(r,t,{vocoder:this.vocoder}),i=this.processor.feature_extractor.config.sampling_rate;return{audio:n.data,sampling_rate:i}}}class eH extends eE{constructor(e){super(e)}async _call(e){let t=await ev(e),r=await this.processor(t),n=await this.model(r),i=[];for(let e of n.reconstruction){let t=e.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");i.push(w.fromTensor(t))}return i.length>1?i:i[0]}}class eW extends eE{constructor(e){super(e)}async _call(e){let t=await ev(e),r=await this.processor(t),{predicted_depth:n}=await this.model(r),i=[];for(let e=0;e<t.length;++e){let r=(0,c.sX)(n[e],t[e].size.reverse(),"bilinear",!1),s=r.mul_(255/(0,u.Fp)(r.data)[0]).to("uint8");i.push({predicted_depth:n[e],depth:w.fromTensor(s)})}return i.length>1?i:i[0]}}let eK=Object.freeze({"text-classification":{tokenizer:a.t2,pipeline:ek,model:o.o$X,default:{model:"Xenova/distilbert-base-uncased-finetuned-sst-2-english"},type:"text"},"token-classification":{tokenizer:a.t2,pipeline:eA,model:o.OjJ,default:{model:"Xenova/bert-base-multilingual-cased-ner-hrl"},type:"text"},"question-answering":{tokenizer:a.t2,pipeline:ez,model:o.wiU,default:{model:"Xenova/distilbert-base-cased-distilled-squad"},type:"text"},"fill-mask":{tokenizer:a.t2,pipeline:eC,model:o.t78,default:{model:"Xenova/bert-base-uncased"},type:"text"},summarization:{tokenizer:a.t2,pipeline:eI,model:o.Kf0,default:{model:"Xenova/distilbart-cnn-6-6"},type:"text"},translation:{tokenizer:a.t2,pipeline:eO,model:o.Kf0,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:a.t2,pipeline:eM,model:o.Kf0,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:a.t2,pipeline:e$,model:o.Hqk,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:a.t2,pipeline:eT,model:o.o$X,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:eF,model:o.K2m,processor:ey,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:a.t2,pipeline:ej,model:o.$Sz,processor:ey,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:a.t2,pipeline:eL,model:[o.hZO,o.ENH],processor:ey,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:a.t2,pipeline:eG,model:[o.z6E,o.lbf],processor:[ey,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:a.t2,pipeline:eN,model:o.tLj,processor:ey,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:eR,model:o.En$,processor:ey,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:eP,model:[o.U$$,o.$Bv],processor:ey,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:a.t2,pipeline:eq,model:o.$Sz,processor:ey,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:eX,model:o.Zn,processor:ey,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:a.t2,pipeline:eV,model:o.LdW,processor:ey,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:a.t2,pipeline:eD,model:o.DcG,processor:ey,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:eH,model:o.S2d,processor:ey,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:eW,model:o.hY6,processor:ey,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:a.t2,pipeline:eB,model:o.$Sz,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:ey,pipeline:eU,model:[o.IFL,o.$Sz],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),eJ=Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"});async function eY(e,t=null,{quantized:r=!0,progress_callback:n=null,config:i=null,cache_dir:s=null,local_files_only:a=!1,revision:o="main",model_file_name:h=null}={}){let u=eK[(e=eJ[e]??e).split("_",1)[0]];if(!u)throw Error(`Unsupported pipeline: ${e}. Must be one of [${Object.keys(eK)}]`);t||(t=u.default.model,console.log(`No model specified. 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