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e=0;e32768*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;B(e,"SeamlessM4TFeatureExtractor");let a=this._extract_fbank_features(e,this.config.max_length);if(n){let[e,t]=a.dims;for(let r=0;r0){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;e0){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_.read(e)))}async function ev(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>"string"==typeof e||e instanceof URL?w(e,t):e instanceof Float64Array?new Float32Array(e):e))}function eb(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 ex 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 eE extends ex{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 ex{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[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{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 ez extends ex{_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 eM&&"_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 ez{_key="summary_text";constructor(e){super(e)}}class eM extends ez{_key="translation_text";constructor(e){super(e)}}function eB(e){return Array.isArray(e)&&e.every(e=>"role"in e&&"content"in e)}class eO extends ex{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(eB(e))e=[e];else if(Array.isArray(e)&&e.every(eB))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[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 eT extends ex{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;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 ex{constructor(e){super(e)}async _call(e,{pool:t=null}={}){let r;let n=await ew(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 e$ extends ex{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 ev(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 ex{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 ev(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 ex{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 ev(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,p=this.processor.feature_extractor.config.hop_length,d=this.processor.feature_extractor.config.sampling_rate,m=await ev(e,d),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=d*n,r=d*a,i=t-2*r,s=0;for(;s=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]/p);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/d),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 eF extends ex{constructor(e){super(e)}async _call(e,t={}){let r=Array.isArray(e),n=await ew(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 ex{constructor(e){super(e)}async _call(e,{topk:t=1}={}){let r=Array.isArray(e),n=await ew(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 eN extends ex{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 ew(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 p=this.model.config.id2label,d=[];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;rr.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 eq extends ex{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 ew(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:eb(t,!r)})));return n?c:c[0]}}class eX extends ex{constructor(e){super(e)}async _call(e,t,{threshold:r=.1,topk:n=null,percentage:i=!1}={}){let s=Array.isArray(e),a=await ew(e),o=this.tokenizer(t,{padding:!0,truncation:!0}),l=await this.processor(a),h=[];for(let e=0;e({score:p.scores[r],label:t[p.classes[r]],box:eb(e,!i)})).sort((e,t)=>t.score-e.score);null!==n&&(d=d.slice(0,n)),h.push(d)}return s?h:h[0]}}class eV extends ex{constructor(e){super(e)}async _call(e,t,r={}){let n=(await ew(e))[0],{pixel_values:i}=await this.processor(n),s=`${t}`,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>/),h=null;return l&&l.length>=2&&(h=l[1].trim()),[{answer:h}]}}class eD extends ex{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.$Sz.from_pretrained(this.DEFAULT_VOCODER_ID,{quantized:!1})),("string"==typeof t||t instanceof URL)&&(t=new Float32Array(await (await fetch(t)).arrayBuffer())),t instanceof Float32Array)t=new c.es("float32",t,[1,t.length]);else if(!(t instanceof c.es))throw Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");let{input_ids:r}=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:n}=await this.model.generate_speech(r,t,{vocoder:this.vocoder}),i=this.processor.feature_extractor.config.sampling_rate;return{audio:n.data,sampling_rate:i}}}class eG extends ex{constructor(e){super(e)}async _call(e){let t=await ew(e),r=await this.processor(t),n=await this.model(r),i=[];for(let e of n.reconstruction){let t=e.squeeze().clamp_(0,1).mul_(255).round_().to("uint8");i.push(_.fromTensor(t))}return i.length>1?i:i[0]}}class eH extends ex{constructor(e){super(e)}async _call(e){let t=await ew(e),r=await this.processor(t),{predicted_depth:n}=await this.model(r),i=[];for(let e=0;e1?i:i[0]}}let eW=Object.freeze({"text-classification":{tokenizer:a.t2,pipeline:eE,model:o.o$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:ek,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:eM,model:o.Kf0,default:{model:"Xenova/t5-small"},type:"text"},"text2text-generation":{tokenizer:a.t2,pipeline:ez,model:o.Kf0,default:{model:"Xenova/flan-t5-small"},type:"text"},"text-generation":{tokenizer:a.t2,pipeline:eO,model:o.Hqk,default:{model:"Xenova/gpt2"},type:"text"},"zero-shot-classification":{tokenizer:a.t2,pipeline:eS,model:o.o$X,default:{model:"Xenova/distilbert-base-uncased-mnli"},type:"text"},"audio-classification":{pipeline:e$,model:o.K2m,processor:e_,default:{model:"Xenova/wav2vec2-base-superb-ks"},type:"audio"},"zero-shot-audio-classification":{tokenizer:a.t2,pipeline:ej,model:o.$Sz,processor:e_,default:{model:"Xenova/clap-htsat-unfused"},type:"multimodal"},"automatic-speech-recognition":{tokenizer:a.t2,pipeline:eL,model:[o.hZO,o.ENH],processor:e_,default:{model:"Xenova/whisper-tiny.en"},type:"multimodal"},"text-to-audio":{tokenizer:a.t2,pipeline:eD,model:[o.z6E,o.lbf],processor:[e_,null],default:{model:"Xenova/speecht5_tts"},type:"text"},"image-to-text":{tokenizer:a.t2,pipeline:eF,model:o.tLj,processor:e_,default:{model:"Xenova/vit-gpt2-image-captioning"},type:"multimodal"},"image-classification":{pipeline:eR,model:o.En$,processor:e_,default:{model:"Xenova/vit-base-patch16-224"},type:"multimodal"},"image-segmentation":{pipeline:eN,model:[o.U$$,o.$Bv],processor:e_,default:{model:"Xenova/detr-resnet-50-panoptic"},type:"multimodal"},"zero-shot-image-classification":{tokenizer:a.t2,pipeline:eP,model:o.$Sz,processor:e_,default:{model:"Xenova/clip-vit-base-patch32"},type:"multimodal"},"object-detection":{pipeline:eq,model:o.Zn,processor:e_,default:{model:"Xenova/detr-resnet-50"},type:"multimodal"},"zero-shot-object-detection":{tokenizer:a.t2,pipeline:eX,model:o.LdW,processor:e_,default:{model:"Xenova/owlvit-base-patch32"},type:"multimodal"},"document-question-answering":{tokenizer:a.t2,pipeline:eV,model:o.DcG,processor:e_,default:{model:"Xenova/donut-base-finetuned-docvqa"},type:"multimodal"},"image-to-image":{pipeline:eG,model:o.S2d,processor:e_,default:{model:"Xenova/swin2SR-classical-sr-x2-64"},type:"image"},"depth-estimation":{pipeline:eH,model:o.hY6,processor:e_,default:{model:"Xenova/dpt-large"},type:"image"},"feature-extraction":{tokenizer:a.t2,pipeline:eT,model:o.$Sz,default:{model:"Xenova/all-MiniLM-L6-v2"},type:"text"},"image-feature-extraction":{processor:e_,pipeline:eU,model:[o.IFL,o.$Sz],default:{model:"Xenova/vit-base-patch16-224-in21k"},type:"image"}}),eK=Object.freeze({"sentiment-analysis":"text-classification",ner:"token-classification",asr:"automatic-speech-recognition","text-to-speech":"text-to-audio",embeddings:"feature-extraction"});async 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