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r=new fa(this.bos_token_id??0,0,0,0,0),i=new fa(this.eos_token_id??0,1,this.len,0,0);this.nodes.push(r.clone()),this.nodes.push(i.clone()),this.begin_nodes[this.len].push(i),this.end_nodes[0].push(r)}insert(e,t,n,r){let i=this.nodes.length,a=new fa(r,i,e,t,n);this.begin_nodes[e].push(a),this.end_nodes[e+t].push(a),this.nodes.push(a)}viterbi(){let e=this.len,t=0;for(;t<=e;){if(this.begin_nodes[t].length==0)return[];for(let e of this.begin_nodes[t]){e.prev=null;let n=0,r=null;for(let i of this.end_nodes[t]){let t=i.backtrace_score+e.score;(r===null||t>n)&&(r=i.clone(),n=t)}if(r!==null)e.prev=r,e.backtrace_score=n;else return[]}++t}let n=[],r=this.begin_nodes[e][0].prev;if(r===null)return[];let i=r.clone();for(;i.prev!==null;)n.push(i.clone()),i=i.clone().prev.clone();return n.reverse(),n}piece(e){return this.chars.slice(e.pos,e.pos+e.length).join(``)}tokens(){return this.viterbi().map(e=>this.piece(e))}token_ids(){return this.viterbi().map(e=>e.token_id)}};function ma(e){if(e.length===0)throw Error(`Array must not be empty`);let t=e[0],n=0;for(let r=1;r<e.length;++r)e[r]<t&&(t=e[r],n=r);return[t,n]}var ha=class extends ca{constructor(e,t){super(e);let n=e.vocab.length;this.vocab=Array(n),this.scores=Array(n);for(let t=0;t<n;++t)[this.vocab[t],this.scores[t]]=e.vocab[t];this.unk_token_id=e.unk_id,this.unk_token=this.vocab[e.unk_id],this.tokens_to_ids=new Map(this.vocab.map((e,t)=>[e,t])),this.bos_token=` `,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.unk_token=this.vocab[this.unk_token_id],this.min_score=ma(this.scores)[0],this.unk_score=this.min_score-10,this.scores[this.unk_token_id]=this.unk_score,this.trie=new da,this.trie.extend(this.vocab),this.fuse_unk=!0}populate_nodes(e){let t=e.chars,n=0;for(;n<t.length;){let r=!1,i=[],a=t.slice(n).join(``),o=this.trie.common_prefix_search(a);for(let t of o){i.push(t);let a=this.tokens_to_ids.get(t),o=this.scores[a],s=Ei(t);e.insert(n,s,o,a),!r&&s===1&&(r=!0)}r||e.insert(n,1,this.unk_score,this.unk_token_id),n+=1}}tokenize(e){let t=new pa(e,this.bos_token_id,this.eos_token_id);return this.populate_nodes(t),t.tokens()}encode(e){let t=[];for(let n of e){let e=this.tokenize(n);t.push(...e)}return t}},ga=class{constructor(e=(e,t)=>e>t,t=1/0){this._heap=[],this._comparator=e,this._max_size=t}get size(){return this._heap.length}is_empty(){return this.size===0}peek(){return this._heap[0]}push(...e){return this.extend(e)}extend(e){for(let t of e)if(this.size<this._max_size)this._heap.push(t),this._sift_up();else{let e=this._smallest();this._comparator(t,this._heap[e])&&(this._heap[e]=t,this._sift_up_from(e))}return this.size}pop(){let e=this.peek(),t=this.size-1;return t>0&&this._swap(0,t),this._heap.pop(),this._sift_down(),e}replace(e){let t=this.peek();return this._heap[0]=e,this._sift_down(),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}_sift_up(){this._sift_up_from(this.size-1)}_sift_up_from(e){for(;e>0&&this._greater(e,this._parent(e));)this._swap(e,this._parent(e)),e=this._parent(e)}_sift_down(){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}}_smallest(){return 2**Math.floor(Math.log2(this.size))-1}},_a=class{constructor(e){this.capacity=e,this.cache=new Map}get(e){if(!this.cache.has(e))return;let t=this.cache.get(e);return this.cache.delete(e),this.cache.set(e,t),t}put(e,t){this.cache.has(e)&&this.cache.delete(e),this.cache.set(e,t),this.cache.size>this.capacity&&this.cache.delete(this.cache.keys().next().value)}clear(){this.cache.clear()}},va=class extends ca{constructor(e){super(e),this.tokens_to_ids=ki(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.vocab=Array(this.tokens_to_ids.size);for(let[e,t]of this.tokens_to_ids)this.vocab[t]=e;let t=Array.isArray(e.merges[0]);this.merges=t?e.merges:e.merges.map(e=>e.split(` `,2)),this.bpe_ranks=new Map(this.merges.map((e,t)=>[JSON.stringify(e),t])),this.end_of_word_suffix=e.end_of_word_suffix,this.continuing_subword_suffix=e.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.ignore_merges=this.config.ignore_merges??!1,this.max_length_to_cache=256,this.cache_capacity=1e4,this.cache=new _a(this.cache_capacity)}clear_cache(){this.cache.clear()}bpe(e){if(e.length===0)return[];let t=this.cache.get(e);if(t!==void 0)return t;let n=Array.from(e);this.end_of_word_suffix&&(n[n.length-1]+=this.end_of_word_suffix);let r=[];if(n.length>1){let e=new ga((e,t)=>e.score<t.score),t={token:n[0],bias:0,prev:null,next:null},i=t;for(let t=1;t<n.length;++t){let r={bias:t/n.length,token:n[t],prev:i,next:null};i.next=r,this.add_node(e,i),i=r}for(;!e.is_empty();){let n=e.pop();if(n.deleted||!n.next||n.next.deleted)continue;if(n.deleted=!0,n.next.deleted=!0,n.prev){let e={...n.prev};n.prev.deleted=!0,n.prev=e,e.prev?e.prev.next=e:t=e}let r={token:n.token+n.next.token,bias:n.bias,prev:n.prev,next:n.next.next};r.prev?(r.prev.next=r,this.add_node(e,r.prev)):t=r,r.next&&(r.next.prev=r,this.add_node(e,r))}for(let e=t;e!==null;e=e.next)r.push(e.token)}else r=n;if(this.continuing_subword_suffix)for(let e=0;e<r.length-1;++e)r[e]+=this.continuing_subword_suffix;return e.length<this.max_length_to_cache&&this.cache.put(e,r),r}add_node(e,t){let n=this.bpe_ranks.get(JSON.stringify([t.token,t.next.token]));n!==void 0&&(t.score=n+t.bias,e.push(t))}encode(e){let t=[];for(let n of e){if(this.ignore_merges&&this.tokens_to_ids.has(n)){t.push(n);continue}let e=this.bpe(n);for(let n of e)if(this.tokens_to_ids.has(n))t.push(n);else if(this.byte_fallback){let e=Array.from(this.text_encoder.encode(n)).map(e=>`<0x${e.toString(16).toUpperCase().padStart(2,`0`)}>`);e.every(e=>this.tokens_to_ids.has(e))?t.push(...e):this.unk_token!=null&&t.push(this.unk_token)}else this.unk_token!=null&&t.push(this.unk_token)}return t}},ya=class extends ca{constructor(e,t){super(e);let n=e.vocab;this.tokens_to_ids=ki(t.target_lang?n[t.target_lang]:n),this.bos_token=t.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=t.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=t.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=Array(this.tokens_to_ids.size);for(let[e,t]of this.tokens_to_ids)this.vocab[t]=e}encode(e){return e}};function ba(e,t){switch(e.type){case`WordPiece`:return new la(e);case`Unigram`:return new ha(e,t.eos_token);case`BPE`:return new va(e);default:if(e.vocab)return Array.isArray(e.vocab)?new ha(e,t.eos_token):Object.hasOwn(e,`continuing_subword_prefix`)&&Object.hasOwn(e,`unk_token`)?Object.hasOwn(e,`merges`)?new va(e):new la(e):new ya(e,{target_lang:t.target_lang,bos_token:t.bos_token,eos_token:t.eos_token,pad_token:t.pad_token,unk_token:t.unk_token});throw Error(`Unknown TokenizerModel type: ${e?.type}`)}}var xa=ba,Sa=class extends Pi{constructor(e){super(),this.config=e}_call(e,...t){return this.post_process(e,...t)}},Ca=class extends Sa{post_process(e,t=null,n=!0){let r=t===null?this.config.single:this.config.pair,i=[],a=[];for(let o of r)`SpecialToken`in o?n&&(i.push(o.SpecialToken.id),a.push(o.SpecialToken.type_id)):`Sequence`in o&&(o.Sequence.id===`A`?(i=Oi(i,e),a=Oi(a,Array(e.length).fill(o.Sequence.type_id))):o.Sequence.id===`B`&&(i=Oi(i,t),a=Oi(a,Array(t.length).fill(o.Sequence.type_id))));return{tokens:i,token_type_ids:a}}},wa=class extends Sa{post_process(e,t=null){return{tokens:e,tokens_pair:t}}},Ta=class extends Sa{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t=null,n=!0){n&&(e=Oi([this.cls[0]],e,[this.sep[0]]));let r=Array(e.length).fill(0);if(t){let i=[],a=n?[this.sep[0]]:[];e=Oi(e,i,t,a),r=Oi(r,Array(t.length+i.length+a.length).fill(1))}return{tokens:e,token_type_ids:r}}},Ea=class extends Sa{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t,n=!0){n&&(e=Oi([this.cls[0]],e,[this.sep[0]]));let r=Array(e.length).fill(0);if(t){let i=n?[this.sep[0]]:[],a=n?[this.sep[0]]:[];e=Oi(e,i,t,a),r=Oi(r,Array(t.length+i.length+a.length).fill(1))}return{tokens:e,token_type_ids:r}}},Da=class extends Sa{constructor(e){super(e),this.processors=(e.processors??[]).map(e=>ka(e))}post_process(e,t=null,n=!0){let r={tokens:e,tokens_pair:t};for(let e of this.processors)r=e.post_process(r.tokens,r.tokens_pair,n);return r}};function Oa(e){if(e===null)return null;switch(e.type){case`TemplateProcessing`:return new Ca(e);case`ByteLevel`:return new wa(e);case`BertProcessing`:return new Ta(e);case`RobertaProcessing`:return new Ea(e);case`Sequence`:return new Da(e);default:throw Error(`Unknown PostProcessor type: ${e.type}`)}}var ka=Oa,Aa=class extends Pi{constructor(e){super(),this.config=e,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets=`trim_offsets`in e&&e.trim_offsets}_call(e){return this.decode(e)}decode(e){return this.decode_chain(e).join(``)}},ja=class extends Aa{constructor(e){super(e),this.byte_decoder=gi,this.text_decoder=new TextDecoder(`utf-8`,{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){let t=e.join(``),n=new Uint8Array([...t].map(e=>this.byte_decoder[e]));return this.text_decoder.decode(n)}decode_chain(e){let t=[],n=[];for(let r of e)this.added_tokens.find(e=>e.content===r)===void 0?n.push(r):(n.length>0&&(t.push(this.convert_tokens_to_string(n)),n=[]),t.push(r));return n.length>0&&t.push(this.convert_tokens_to_string(n)),t}},Ma=class extends Aa{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map((e,t)=>{if(t!==0){let t=this.config.prefix;e=t&&e.startsWith(t)?e.replace(t,``):` `+e}return this.cleanup&&(e=bi(e)),e})}},Na=class extends Aa{constructor(e){super(e),this.replacement=e.replacement??`▁`}decode_chain(e){let t=[];for(let n=0;n<e.length;++n){let r=e[n].replaceAll(this.replacement,` `);n==0&&r.startsWith(` `)&&(r=r.substring(1)),t.push(r)}return t}},Pa=class extends Aa{constructor(e){super(e),this.suffix=e.suffix??``}decode_chain(e){return e.map((t,n)=>t.replaceAll(this.suffix,n===e.length-1?``:` `))}},Fa=class extends Aa{constructor(e){super(e),this.pad_token=e.pad_token??``,this.word_delimiter_token=e.word_delimiter_token??``,this.cleanup=e.cleanup}convert_tokens_to_string(e){if(e.length===0)return``;let t=[e[0]];for(let n=1;n<e.length;++n)e[n]!==t.at(-1)&&t.push(e[n]);let n=t.filter(e=>e!==this.pad_token).join(``);return this.cleanup&&(n=bi(n).replaceAll(this.word_delimiter_token,` `).trim()),n}decode_chain(e){return[this.convert_tokens_to_string(e)]}},Ia=class extends Aa{constructor(e){super(e),this.decoders=(e.decoders??[]).map(e=>Ha(e))}decode_chain(e){return this.decoders.reduce((e,t)=>t.decode_chain(e),e)}},La=class extends Aa{decode_chain(e){let t=xi(this.config.pattern),n=this.config.content??``;return t===null?e:e.map(e=>e.replaceAll(t,n))}},Ra=class extends Aa{decode_chain(e){return[e.join(``)]}},za=class extends Aa{constructor(e){super(e),this.content=e.content??``,this.start=e.start??0,this.stop=e.stop??0}decode_chain(e){return e.map(e=>{let t=0;for(let n=0;n<this.start&&e[n]===this.content;++n)t=n+1;let n=e.length;for(let t=0;t<this.stop;++t){let r=e.length-t-1;if(e[r]===this.content){n=r;continue}else break}return e.slice(t,n)})}},Ba=class extends Aa{constructor(e){super(e),this.text_decoder=new TextDecoder}decode_chain(e){let t=[],n=[];for(let r of e){let e=null;if(r.length===6&&r.startsWith(`<0x`)&&r.endsWith(`>`)){let t=parseInt(r.slice(3,5),16);isNaN(t)||(e=t)}if(e!==null)n.push(e);else{if(n.length>0){let e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}t.push(r)}}if(n.length>0){let e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}return t}};function Va(e){if(e===null)return null;switch(e.type){case`ByteLevel`:return new ja(e);case`WordPiece`:return new Ma(e);case`Metaspace`:return new Na(e);case`BPEDecoder`:return new Pa(e);case`CTC`:return new Fa(e);case`Sequence`:return new Ia(e);case`Replace`:return new La(e);case`Fuse`:return new Ra(e);case`Strip`:return new za(e);case`ByteFallback`:return new Ba(e);default:throw Error(`Unknown Decoder type: ${e.type}`)}}var Ha=Va,Ua=class{constructor(e,t){let n=Mi(e,`Tokenizer`,[`model`,`decoder`,`post_processor`,`pre_tokenizer`,`normalizer`]);if(n)throw Error(n);let r=Mi(t,`Config`);if(r)throw Error(r);this.tokenizer=e,this.config=t,this.normalizer=Xi(this.tokenizer.normalizer),this.pre_tokenizer=I(this.tokenizer.pre_tokenizer),this.model=xa(this.tokenizer.model,this.config),this.post_processor=ka(this.tokenizer.post_processor),this.decoder=Ha(this.tokenizer.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];let i=[],a=[];this.added_tokens_map=new Map;for(let e of this.tokenizer.added_tokens){let t=new mi(e);if(this.added_tokens.push(t),this.model.tokens_to_ids.set(t.content,t.id),this.model.vocab[t.id]=t.content,t.special&&(this.special_tokens.push(t.content),this.all_special_ids.push(t.id)),this.added_tokens_map.set(t.content,t),t.normalized&&this.normalizer!==null){let e=this.normalizer(t.content);a.push(e),this.added_tokens_map.set(e,t)}else i.push(t.content)}(this.config.additional_special_tokens??[]).forEach(e=>{this.special_tokens.includes(e)||this.special_tokens.push(e)}),this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.splitter_unnormalized=new pi(i),this.splitter_normalized=new pi(a),this.remove_space=this.config.remove_space,this.clean_up_tokenization_spaces=this.config.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=this.config.do_lowercase_and_remove_accent??!1}encode(e,{text_pair:t=null,add_special_tokens:n=!0,return_token_type_ids:r=null}={}){let{tokens:i,token_type_ids:a}=this.tokenize_helper(e,{text_pair:t,add_special_tokens:n}),o=i.map(e=>this.added_tokens_map.get(e)?.id??this.model.tokens_to_ids.get(e)??this.model.unk_token_id),s={ids:o,tokens:i,attention_mask:Array(o.length).fill(1)};return r&&a&&(s.token_type_ids=a),s}decode(e,t={}){if(!Array.isArray(e)||e.length===0||!Ti(e[0]))throw Error(`token_ids must be a non-empty array of integers.`);let n=e.map(e=>this.model.vocab[Number(e)]??this.model.unk_token);t.skip_special_tokens&&(n=n.filter(e=>!this.special_tokens.includes(e)));let r=this.decoder?this.decoder(n):n.join(` `);return this.decoder&&this.decoder.end_of_word_suffix&&(r=r.replaceAll(this.decoder.end_of_word_suffix,` 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r=this.added_tokens_map.get(e);r&&(r.lstrip&&t>0&&(n[t-1]=n[t-1].trimEnd()),r.rstrip&&t<n.length-1&&(n[t+1]=n[t+1].trimStart()))}),n.flatMap(e=>{if(e.length===0)return[];if(this.added_tokens_map.has(e))return[e];let n=this.pre_tokenizer===null?[e]:this.pre_tokenizer(e,{section_index:t});return this.model(n)})})}tokenize_helper(e,{text_pair:t=null,add_special_tokens:n=!0}){let r=this.encode_text(e),i=this.encode_text(t||null);return this.post_processor?this.post_processor(r,i,n):{tokens:Oi(r??[],i??[])}}token_to_id(e){return this.model.tokens_to_ids.get(e)}id_to_token(e){return this.model.vocab[e]}get_added_tokens_decoder(){let e=new Map;for(let t of this.added_tokens)e.set(t.id,t);return e}get_vocab(e=!0){let t=new Map;for(let n=0;n<this.model.vocab.length;++n){let r=this.model.vocab[n];(e||!this.added_tokens_map.has(r))&&t.set(r,n)}return 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t=e.length,n=e[0].length,r=[t+1,n+1],i=Array.from({length:r[0]},()=>Array(r[1]).fill(1/0));i[0][0]=0;let a=Array.from({length:r[0]},()=>Array(r[1]).fill(-1));for(let t=1;t<r[1];++t)for(let n=1;n<r[0];++n){let r=i[n-1][t-1],o=i[n-1][t],s=i[n][t-1],c,l;r<o&&r<s?(c=r,l=0):o<r&&o<s?(c=o,l=1):(c=s,l=2),i[n][t]=e[n-1][t-1]+c,a[n][t]=l}for(let e=0;e<r[1];++e)a[0][e]=2;for(let e=0;e<r[0];++e)a[e][0]=1;let o=t,s=n,c=[],l=[];for(;o>0||s>0;)switch(c.push(o-1),l.push(s-1),a[o][s]){case 0:--o,--s;break;case 1:--o;break;case 2:--s;break;default:throw Error(`Internal error in dynamic time warping. 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instanceof ServiceWorkerGlobalScope)&&Bc.versions?.web&&!Bc.wasm.wasmPaths){let e=`https://cdn.jsdelivr.net/npm/onnxruntime-web@${Bc.versions.web}/dist/`;Bc.wasm.wasmPaths=j.IS_SAFARI?{mjs:`${e}ort-wasm-simd-threaded.mjs`,wasm:`${e}ort-wasm-simd-threaded.wasm`}:{mjs:`${e}ort-wasm-simd-threaded.asyncify.mjs`,wasm:`${e}ort-wasm-simd-threaded.asyncify.wasm`}}Bc.wasm.proxy=!1}Bc.webgpu&&(Bc.webgpu.powerPreference=`high-performance`),e(M.logLevel??$r.WARNING),M.backends.onnx={...Bc,setLogLevel:e}}var Hc=async(e,t,n)=>{let r=await Ic(new Uint8Array(e),t);return(async e=>{let t=Vc(),i=Object.fromEntries(Object.entries(e).map(([e,n])=>[e,(t?n.clone():n).ort_tensor])),a=await Rc(r,i);return Array.isArray(n)?n.map(e=>new U(a[e])):new U(a[n])})},Uc=class{static session_options={};static get nearest_interpolate_4d(){return this._nearest_interpolate_4d||=Hc([8,10,18,0,58,129,1,10,41,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,18,10,4,109,111,100,101,34,7,110,101,97,114,101,115,116,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,21],this.session_options,`y`),this._nearest_interpolate_4d}static get bilinear_interpolate_4d(){return this._bilinear_interpolate_4d||=Hc([8,9,18,0,58,128,1,10,40,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,17,10,4,109,111,100,101,34,6,108,105,110,101,97,114,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,`y`),this._bilinear_interpolate_4d}static get bicubic_interpolate_4d(){return this._bicubic_interpolate_4d||=Hc([8,9,18,0,58,127,10,39,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,16,10,4,109,111,100,101,34,5,99,117,98,105,99,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,`y`),this._bicubic_interpolate_4d}static get matmul(){return this._matmul||=Hc([8,9,18,0,58,55,10,17,10,1,97,10,1,98,18,1,99,34,6,77,97,116,77,117,108,18,1,114,90,9,10,1,97,18,4,10,2,8,1,90,9,10,1,98,18,4,10,2,8,1,98,9,10,1,99,18,4,10,2,8,1,66,2,16,20],this.session_options,`c`),this._matmul}static get stft(){return this._stft||=Hc([8,7,18,0,58,148,1,10,38,10,1,115,10,1,106,10,1,119,10,1,108,18,1,111,34,4,83,84,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,115,90,26,10,1,115,18,21,10,19,8,1,18,15,10,3,18,1,98,10,3,18,1,115,10,3,18,1,99,90,11,10,1,106,18,6,10,4,8,7,18,0,90,16,10,1,119,18,11,10,9,8,1,18,5,10,3,18,1,119,90,11,10,1,108,18,6,10,4,8,7,18,0,98,31,10,1,111,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,102,10,3,18,1,100,10,3,18,1,99,66,2,16,17],this.session_options,`o`),this._stft}static get rfft(){return this._rfft||=Hc([8,9,18,0,58,97,10,33,10,1,120,10,0,10,1,97,18,1,121,34,3,68,70,84,42,15,10,8,111,110,101,115,105,100,101,100,24,1,160,1,2,18,1,100,90,21,10,1,120,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,90,11,10,1,97,18,6,10,4,8,7,18,0,98,21,10,1,121,18,16,10,14,8,1,18,10,10,3,18,1,115,10,3,18,1,99,66,2,16,20],this.session_options,`y`),this._rfft}static get top_k(){return this._top_k||=Hc([8,10,18,0,58,73,10,18,10,1,120,10,1,107,18,1,118,18,1,105,34,4,84,111,112,75,18,1,116,90,9,10,1,120,18,4,10,2,8,1,90,15,10,1,107,18,10,10,8,8,7,18,4,10,2,8,1,98,9,10,1,118,18,4,10,2,8,1,98,9,10,1,105,18,4,10,2,8,7,66,2,16,21],this.session_options,[`v`,`i`]),this._top_k}static get slice(){return this._slice||=Hc([8,7,18,0,58,96,10,25,10,1,120,10,1,115,10,1,101,10,1,97,10,1,116,18,1,121,34,5,83,108,105,99,101,18,1,114,90,9,10,1,120,18,4,10,2,8,1,90,9,10,1,115,18,4,10,2,8,7,90,9,10,1,101,18,4,10,2,8,7,90,9,10,1,97,18,4,10,2,8,7,90,9,10,1,116,18,4,10,2,8,7,98,9,10,1,121,18,4,10,2,8,1,66,2,16,13],this.session_options,`y`),this._slice}},Wc=Object.freeze({auto:`auto`,gpu:`gpu`,cpu:`cpu`,wasm:`wasm`,webgpu:`webgpu`,cuda:`cuda`,dml:`dml`,coreml:`coreml`,webnn:`webnn`,"webnn-npu":`webnn-npu`,"webnn-gpu":`webnn-gpu`,"webnn-cpu":`webnn-cpu`}),Gc=j.IS_NODE_ENV?`cpu`:`wasm`;function Kc(e,t,{warn:n}={}){return e?typeof e==`string`?e:e.hasOwnProperty(t)?e[t]:(n&&n(`device not 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Use `tokenizer.batch_decode(...)` for batched inputs.");return e.tolist()[0];default:throw Error(`Expected tensor to have 1-2 dimensions, got ${t.length}.`)}}var Al=[`bos_token`,`eos_token`,`unk_token`,`sep_token`,`pad_token`,`cls_token`,`mask_token`];function jl(e,t,n,r){for(let i of Object.keys(e)){let a=t-e[i].length,o=n(i),s=Array(a).fill(o);e[i]=r===`right`?ci(e[i],s):ci(s,e[i])}}function Ml(e,t){for(let n of Object.keys(e))e[n].length=t}function Nl(e,...t){for(let n of t){if(!Object.hasOwn(e,n))continue;let t=e[n];if(t)if(typeof t==`object`){if(t.__type===`AddedToken`)return t.content;throw Error(`Unknown token: ${t}`)}else return t}return null}function Pl(e){let t=[];for(let n of e.get_added_tokens_decoder().values())n.special&&t.push(n);return t}var W=class extends ni{return_token_type_ids=!1;padding_side=`right`;constructor(e,t){if(super(),this._tokenizerJSON=e,this._tokenizerConfig=t,this._tokenizer=new Ua(e,t),this.config=t,this.padding_side=t.padding_side??this.padding_side,this.mask_token=Nl(t,`mask_token`),this.mask_token_id=this._tokenizer.token_to_id(this.mask_token),this.pad_token=Nl(t,`pad_token`,`eos_token`),this.pad_token_id=this._tokenizer.token_to_id(this.pad_token),this.sep_token=Nl(t,`sep_token`),this.sep_token_id=this._tokenizer.token_to_id(this.sep_token),this.unk_token=Nl(t,`unk_token`),this.unk_token_id=this._tokenizer.token_to_id(this.unk_token),this.bos_token=Nl(t,`bos_token`),this.bos_token_id=this._tokenizer.token_to_id(this.bos_token),this.eos_token=Nl(t,`eos_token`),this.eos_token_id=this._tokenizer.token_to_id(this.eos_token),this.chat_template=t.chat_template??null,Array.isArray(this.chat_template)){let e=Object.create(null);for(let{name:t,template:n}of this.chat_template){if(typeof t!=`string`||typeof n!=`string`)throw Error(`Chat template must be a list of objects with "name" and "template" properties`);e[t]=n}this.chat_template=e}this._compiled_template_cache=new Map;let n=Pl(this._tokenizer);this.all_special_ids=n.map(e=>e.id),this.all_special_tokens=n.map(e=>e.content)}static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:a=`main`}={}){let o=await Ol(e,{progress_callback:t,config:n,cache_dir:r,local_files_only:i,revision:a});return new this(...o)}get_vocab(){return this._tokenizer.get_vocab()}get model_max_length(){return this._tokenizerConfig.model_max_length??1/0}get add_eos_token(){return this._tokenizerConfig.add_eos_token}get add_bos_token(){return this._tokenizerConfig.add_bos_token}convert_tokens_to_ids(e){return typeof e==`string`?this._tokenizer.token_to_id(e):e.map(e=>this._tokenizer.token_to_id(e))}_call(e,t={}){let{text_pair:n=null,add_special_tokens:r=!0,padding:i=!1,return_token_type_ids:a=null}=t,{truncation:o=null,max_length:s=null}=t,c=t.return_tensor??!0,l=Array.isArray(e),u;if(l){if(e.length===0)throw Error(`text array must be non-empty`);if(n!==null){if(!Array.isArray(n))throw Error(`text_pair must also be an array`);if(e.length!==n.length)throw Error(`text and text_pair must have the same length`);u=e.map((e,t)=>this._encode_plus(e,{text_pair:n[t],add_special_tokens:r,return_token_type_ids:a}))}else u=e.map(e=>this._encode_plus(e,{add_special_tokens:r,return_token_type_ids:a}))}else{if(e==null)throw Error(`text may not be null or undefined`);if(Array.isArray(n))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");u=[this._encode_plus(e,{text_pair:n,add_special_tokens:r,return_token_type_ids:a})]}if(s===null?s=this.model_max_length:o===null&&(i===!0?(N.warn("`max_length` is ignored when `padding: true` and there is no truncation strategy. To pad to max length, use `padding: 'max_length'`."),s=this.model_max_length):i===!1&&(N.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation: true` to explicitly truncate examples to max length."),o=!0)),i===!0&&(s=Math.min(lc(u.map(e=>e.input_ids.length))[0],s??1/0)),s=Math.min(s,this.model_max_length??1/0),i||o)for(let e=0;e<u.length;++e)if(u[e].input_ids.length===s)continue;else u[e].input_ids.length>s?o&&Ml(u[e],s):i&&jl(u[e],s,e=>e===`input_ids`?this.pad_token_id:0,this.padding_side);let d={};if(c){if(!(i&&o)&&u.some(e=>{for(let t of Object.keys(e))if(e[t].length!==u[0][t]?.length)return!0;return!1}))throw Error(`Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.`);let e=[u.length,u[0].input_ids.length];for(let t of Object.keys(u[0]))d[t]=new U(`int64`,BigInt64Array.from(u.flatMap(e=>e[t]).map(BigInt)),e)}else{for(let e of Object.keys(u[0]))d[e]=u.map(t=>t[e]);if(!l)for(let e of Object.keys(d))d[e]=d[e][0]}return d}_encode_text(e){return e===null?null:this._tokenizer.encode(e).tokens}_encode_plus(e,{text_pair:t=null,add_special_tokens:n=!0,return_token_type_ids:r=null}={}){let{ids:i,attention_mask:a,token_type_ids:o}=this._tokenizer.encode(e,{text_pair:t,add_special_tokens:n,return_token_type_ids:r??this.return_token_type_ids});return{input_ids:i,attention_mask:a,...o?{token_type_ids:o}:{}}}tokenize(e,{pair:t=null,add_special_tokens:n=!1}={}){return this._tokenizer.tokenize(e,{text_pair:t,add_special_tokens:n})}encode(e,{text_pair:t=null,add_special_tokens:n=!0,return_token_type_ids:r=null}={}){return this._tokenizer.encode(e,{text_pair:t,add_special_tokens:n,return_token_type_ids:r}).ids}batch_decode(e,t={}){return e instanceof U&&(e=e.tolist()),e.map(e=>this.decode(e,t))}decode(e,t={}){if(e instanceof U&&(e=kl(e)),!Array.isArray(e)||e.length===0||!ai(e[0]))throw Error(`token_ids must be a non-empty array of integers.`);return this.decode_single(e,t)}decode_single(e,{skip_special_tokens:t=!1,clean_up_tokenization_spaces:n=null}){return this._tokenizer.decode(e,{skip_special_tokens:t,clean_up_tokenization_spaces:n})}get_chat_template({chat_template:e=null,tools:t=null}={}){if(this.chat_template&&typeof this.chat_template==`object`){let n=this.chat_template;if(e!==null&&Object.hasOwn(n,e))e=n[e];else if(e===null)if(t!==null&&`tool_use`in n)e=n.tool_use;else if(`default`in n)e=n.default;else throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(n).sort()}.`)}else if(e===null)if(this.chat_template)e=this.chat_template;else throw Error(`Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation at https://huggingface.co/docs/transformers/main/en/chat_templating`);return e}apply_chat_template(e,t={}){let{tools:n=null,documents:r=null,chat_template:i=null,add_generation_prompt:a=!1,tokenize:o=!0,padding:s=!1,truncation:c=!1,max_length:l=null,return_tensor:u=!0,return_dict:d=!0,tokenizer_kwargs:f={},...p}=t;if(i=this.get_chat_template({chat_template:i,tools:n}),typeof i!=`string`)throw Error(`chat_template must be a string, but got ${typeof i}`);let m=this._compiled_template_cache.get(i);m===void 0&&(m=new _s(i),this._compiled_template_cache.set(i,m));let h=Object.create(null);for(let e of Al){let t=Nl(this.config,e);t&&(h[e]=t)}let g=m.render({messages:e,add_generation_prompt:a,tools:n,documents:r,...h,...p});if(o){let e=this._call(g,{add_special_tokens:!1,padding:s,truncation:c,max_length:l,return_tensor:u,...f});return d?e:e.input_ids}return g}};function Fl(e,t,n,r){if(!(`language_codes`in e)||!Array.isArray(e.language_codes))throw Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!(`languageRegex`in e)||!(e.languageRegex instanceof RegExp))throw Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!(`lang_to_token`in e)||typeof e.lang_to_token!=`function`)throw Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");let i=r.src_lang,a=r.tgt_lang;if(!e.language_codes.includes(a))throw Error(`Target language code "${a}" is not valid. 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Therefore, you may experience slightly inaccurate results.')}_encode_text(e){if(e===null)return null;let[t,...n]=e.trim().split(this.languageRegex);if(n.length===0)return super._encode_text(t);if(n.length===2){let[e,t]=n;return this.supported_language_codes.includes(e)||N.warn(`Unsupported language code "${e}" detected, which may lead to unexpected behavior. 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Specify `power` to fix this issue.");if(!u)throw Error("`preemphasis_htk_flavor=false` is not currently supported.");if(o){let t=Math.floor(n/2);switch(s){case`reflect`:e=rd(e,t,t);break;case`constant`:{let n=new e.constructor(e.length+2*t);n.set(e,t),e=n;break}case`semicausal`:{let n=new e.constructor(e.length+t);n.set(e,t),e=n;break}default:throw Error(`pad_mode="${s}" not implemented yet.`)}}let w=Math.floor(1+Math.floor((e.length-n)/r));y!==null&&w<y&&(w=y);let ne=c?Math.floor(i/2)+1:i,re=w,T=w;b!==null&&(b>w?x&&(T=b):T=re=b);let E=new pc(i),ie=new Float64Array(i),ae=new Float64Array(E.outputBufferSize),D=new Float32Array(ne*T);for(let i=0;i<re;++i){let a=i*r,o=Math.min(e.length-a,n);o!==n&&ie.fill(0,0,n);for(let t=0;t<o;++t)ie[t]=e[a+t];if(v){let e=0;for(let t=0;t<o;++t)e+=ie[t];let t=e/o;for(let e=0;e<o;++e)ie[e]-=t}if(l!==null){for(let e=o-1;e>=1;--e)ie[e]-=l*ie[e-1];ie[0]*=1-l}for(let e=0;e<t.length;++e)ie[e]*=t[e];E.realTransform(ae,ie);for(let e=0;e<ne;++e){let t=e<<1;D[e*T+i]=ae[t]**2+ae[t+1]**2}}if(a!==null&&a!==2){let e=a/2;for(let t=0;t<D.length;++t)D[t]**=e}let oe=d.length,se=await il(new U(`float32`,d.flat(),[oe,ne]),new U(`float32`,D,[ne,T]));ee&&(se=se.transpose(1,0));let ce=se.data;if(te===`add`)for(let e=0;e<ce.length;++e)ce[e]=S+ce[e]+f;else for(let e=0;e<ce.length;++e)ce[e]=S+Math.max(f,ce[e]);if(a!==null&&p!==null){let e=Math.min(ce.length,re*oe);switch(p){case`log`:for(let t=0;t<e;++t)ce[t]=Math.log(ce[t]);break;case`log10`:for(let t=0;t<e;++t)ce[t]=Math.log10(ce[t]);break;case`log10_max_norm`:{for(let t=0;t<e;++t)ce[t]=Math.log10(ce[t]);let t=(m??lc(ce)[0])-8;for(let n=0;n<e;++n)ce[n]=(Math.max(ce[n],t)+4)/4;break}case`dB`:if(a===1)ad(ce,h,g,_);else if(a===2)od(ce,h,g,_);else throw Error(`Cannot use log_mel option '${p}' with power ${a}`);break;default:throw Error(`log_mel must be one of null, 'log', 'log10', 'log10_max_norm', or 'dB'. Got '${p}'`)}}return se}function cd(e,t,{periodic:n=!0,frame_length:r=null,center:i=!0}={}){let a=n?e+1:e,o;switch(t){case`boxcar`:o=new Float64Array(a).fill(1);break;case`hann`:case`hann_window`:o=Ju(a);break;case`hamming`:o=Yu(a);break;case`povey`:o=Ju(a).map(e=>e**.85);break;default:throw Error(`Unknown window type ${t}.`)}if(n&&(o=o.subarray(0,e)),r===null||e===r)return o;if(e>r)throw Error(`Length of the window (${e}) may not be larger than frame_length (${r})`);let s=new Float64Array(r),c=i?Math.floor((r-e)/2):0;return s.set(o,c),s}function ld(e,t){let n=e.reduce((e,t)=>e+t.length,0),r=new ArrayBuffer(44),i=new DataView(r);return ud(i,0,`RIFF`),i.setUint32(4,36+n*4,!0),ud(i,8,`WAVE`),ud(i,12,`fmt `),i.setUint32(16,16,!0),i.setUint16(20,3,!0),i.setUint16(22,1,!0),i.setUint32(24,t,!0),i.setUint32(28,t*4,!0),i.setUint16(32,4,!0),i.setUint16(34,32,!0),ud(i,36,`data`),i.setUint32(40,n*4,!0),new Blob([r,...e.map(e=>e.buffer)],{type:`audio/wav`})}function ud(e,t,n){for(let r=0;r<n.length;++r)e.setUint8(t+r,n.charCodeAt(r))}var dd=class{constructor(e,t){this.audio=e,this.sampling_rate=t}get data(){if(Array.isArray(this.audio)){if(this.audio.length===0)return new Float32Array;if(this.audio.length===1)return this.audio[0];let e=this.audio.reduce((e,t)=>e+t.length,0),t=new Float32Array(e),n=0;for(let e of this.audio)t.set(e,n),n+=e.length;return t}else return this.audio}toBlob(){let e=this.audio;return e instanceof Float32Array&&(e=[e]),ld(e,this.sampling_rate)}async save(e){return Wu(e,this.toBlob())}},fd=class extends Bu{constructor(e){super(e);let t=this.config.sampling_rate,n=nd(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0);this.mel_filters=n,this.window=cd(400,`hann`,{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(e,t){return sd(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){Vu(e,`ASTFeatureExtractor`);let t=await this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){let e=this.std*2,n=t.data;for(let t=0;t<n.length;++t)n[t]=(n[t]-this.mean)/e}return{input_values:t.unsqueeze_(0)}}},pd=class extends Bu{async _call(e){Vu(e,`EncodecFeatureExtractor`),e instanceof Float64Array&&(e=new Float32Array(e));let t=this.config.feature_size;if(e.length%t!==0)throw Error(`The length of the audio data must be a multiple of the number of channels (${t}).`);let n=[1,t,e.length/t];return{input_values:new U(`float32`,e,n)}}},md=class extends Bu{async _call(e){Vu(e,`ChatterboxFeatureExtractor`),e instanceof Float64Array&&(e=new Float32Array(e));let t=[1,e.length];return{input_values:new U(`float32`,e,t)}}},hd=class extends Bu{constructor(e){super(e),this.mel_filters=nd(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=nd(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=cd(this.config.fft_window_size,`hann`)}async _get_input_mel(e,t,n,r){let i,a=e.length-t;if(a>0)if(n===`rand_trunc`){let n=Math.floor(Cs.random()*(a+1));e=e.subarray(n,n+t),i=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}else throw Error(`Truncation strategy "${n}" not implemented`);else{if(a<0){let n=new Float64Array(t);if(n.set(e),r===`repeat`)for(let r=e.length;r<t;r+=e.length)n.set(e.subarray(0,Math.min(e.length,t-r)),r);else if(r===`repeatpad`)for(let t=e.length;t<-a;t+=e.length)n.set(e,t);e=n}if(n===`fusion`)throw Error(`Truncation strategy "${n}" not implemented`);i=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}return i.unsqueeze_(0)}async _extract_fbank_features(e,t,n=null){return sd(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}={}){return Vu(e,`ClapFeatureExtractor`),{input_features:(await this._get_input_mel(e,t??this.config.nb_max_samples,this.config.truncation,this.config.padding)).unsqueeze_(0)}}},gd=1e-5,_d=class extends Bu{constructor(e){super(e),this.config.mel_filters??=nd(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,this.config.sampling_rate/2,this.config.sampling_rate,`slaney`,`slaney`);let t=cd(this.config.win_length,`hann`,{periodic:!1});this.window=new Float64Array(this.config.n_fft);let n=Math.floor((this.config.n_fft-this.config.win_length)/2);this.window.set(t,n)}async _extract_fbank_features(e){let t=this.config.preemphasis;e=new Float64Array(e);for(let n=e.length-1;n>=1;--n)e[n]-=t*e[n-1];return await sd(e,this.window,this.window.length,this.config.hop_length,{fft_length:this.config.n_fft,power:2,mel_filters:this.config.mel_filters,log_mel:`log`,mel_floor:-1/0,pad_mode:`constant`,center:!0,transpose:!0,mel_offset:2**-24})}async _call(e){Vu(e,`ParakeetFeatureExtractor`);let t=await this._extract_fbank_features(e),n=Math.floor((e.length+Math.floor(this.config.n_fft/2)*2-this.config.n_fft)/this.config.hop_length),r=t.data;r.fill(0,n*t.dims[1]);let[i,a]=t.dims,o=new Float64Array(a),s=new Float64Array(a);for(let e=0;e<n;++e){let t=e*a;for(let e=0;e<a;++e){let n=r[t+e];o[e]+=n,s[e]+=n*n}}let c=n>1?n-1:1;for(let e=0;e<a;++e){let t=o[e]/n,i=(s[e]-n*t*t)/c,l=1/(Math.sqrt(i)+gd);for(let i=0;i<n;++i){let n=i*a+e;r[n]=(r[n]-t)*l}}let l=new BigInt64Array(i);return l.fill(1n,0,n),{input_features:t.unsqueeze_(0),attention_mask:new U(`int64`,l,[1,i])}}},vd=class extends _d{_apply_dither(e){let t=this.config.dither??0;if(t<=0)return e;let n=new bs(e.length);for(let r=0;r<e.length;++r)e[r]+=t*n.gauss();return e}split_audio(e){let t=this.config.max_audio_clip_s??35,n=this.config.overlap_chunk_second??5,r=this.config.min_energy_window_samples??1600,i=this.config.sampling_rate,a=Math.max(1,Math.round(t*i)),o=Math.max(1,Math.round(n*i));if(e.length<=a)return[e];let s=[],c=0,l=e.length;for(;c<l;){if(c+a>=l){s.push(e.slice(c,l));break}let t=Math.max(c,c+a-o),n=Math.min(c+a,l),i;i=n<=t?c+a:this._find_split_point_energy(e,t,n,r),i=Math.max(c+1,Math.min(i,l)),s.push(e.slice(c,i)),c=i}return s}_find_split_point_energy(e,t,n,r){let i=n-t;if(i<=r)return Math.floor((t+n)/2);let a=1/0,o=t,s=i-r;for(let n=0;n<=s;n+=r){let i=0;for(let a=0;a<r;++a){let r=e[t+n+a];i+=r*r}i=Math.sqrt(i/r),i<a&&(a=i,o=t+n)}return o}async _call(e){Vu(e,`CohereAsrFeatureExtractor`);let t=new Float64Array(e);return this._apply_dither(t),super._call(t)}},yd=class extends pd{},bd=class extends Bu{constructor(e){super(e);let{fft_length:t,feature_size:n,min_frequency:r,max_frequency:i,sampling_rate:a,frame_length:o}=this.config,s=nd(Math.floor(1+t/2),n,r,i,a,null,`htk`,!1);this.mel_filters=s,this.window=cd(o,`hann`)}async _extract_fbank_features(e,t){return sd(e,this.window,this.config.frame_length,this.config.hop_length,{fft_length:this.config.fft_length,center:!1,onesided:!0,preemphasis:this.config.preemphasis,preemphasis_htk_flavor:this.config.preemphasis_htk_flavor,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:this.config.mel_floor,remove_dc_offset:!1,transpose:!0})}async _call(e,{max_length:t=48e4,truncation:n=!0,padding:r=!0,pad_to_multiple_of:i=128}={}){if(Vu(e,`Gemma3nAudioFeatureExtractor`),n&&e.length>t&&(e=e.slice(0,t)),r&&e.length%i!==0){let t=i-e.length%i,n=new Float64Array(e.length+t);n.set(e),this.config.padding_value!==0&&n.fill(this.config.padding_value,e.length),e=n}let a=await this._extract_fbank_features(e,this.config.max_length),o=yl([1,a.dims[0]],!0);return{input_features:a.unsqueeze_(0),input_features_mask:o}}},xd=class extends bd{async _extract_fbank_features(e,t){let{frame_length:n,hop_length:r,fft_length:i}=this.config,a=Math.floor(n/2),o=Math.floor((e.length+a-(n+1))/r)+1;return sd(e,this.window,n,r,{fft_length:i,center:!0,pad_mode:`semicausal`,onesided:!0,preemphasis:this.config.preemphasis,preemphasis_htk_flavor:this.config.preemphasis_htk_flavor,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:this.config.mel_floor,mel_floor_mode:`add`,remove_dc_offset:!1,transpose:!0,max_num_frames:o})}async _call(e,t={}){Vu(e,`Gemma4AudioFeatureExtractor`);let n=e.length,r=await super._call(e,t),{input_features:i}=r,[,a,o]=i.dims,{frame_length:s,hop_length:c}=this.config,l=Math.floor(s/2),u=s+1,d=new Uint8Array(n+l+(t.pad_to_multiple_of??128));d.fill(1,l,l+n);let f=new Uint8Array(a);for(let e=0;e<a;++e)f[e]=+!!d[e*c+u-1];let p=i.data;for(let e=0;e<a;++e)f[e]||p.fill(0,e*o,(e+1)*o);return r.input_features_mask=new U(`bool`,f,[1,a]),r}},Sd=class extends Bu{constructor(e){super(e);let{n_fft:t,win_length:n,n_mels:r,sample_rate:i}=e.melspec_kwargs;this.mel_filters=nd(Math.floor(1+t/2),r,0,i/2,i,null,`htk`);let a=cd(n,`hann`);this.window=new Float64Array(t);let o=Math.floor((t-n)/2);this.window.set(a,o)}async _call(e){Vu(e,`GraniteSpeechFeatureExtractor`);let{n_fft:t,hop_length:n,n_mels:r}=this.config.melspec_kwargs,i=1+Math.floor((e.length-1)/n),a=i-i%2;return{input_features:(await sd(e,this.window,t,n,{power:2,mel_filters:this.mel_filters,log_mel:`log10_max_norm`,transpose:!0,max_num_frames:a,do_pad:!1})).view(-1,2*r).unsqueeze_(0)}}},Cd=class extends Bu{async _call(e){Vu(e,`MoonshineFeatureExtractor`),e instanceof Float64Array&&(e=new Float32Array(e));let t=[1,e.length];return{input_values:new U(`float32`,e,t)}}},wd=class extends Bu{async _call(e){Vu(e,`PyAnnoteFeatureExtractor`),e instanceof Float64Array&&(e=new Float32Array(e));let t=[1,1,e.length];return{input_values:new U(`float32`,e,t)}}samples_to_frames(e){return(e-this.config.offset)/this.config.step}post_process_speaker_diarization(e,t){let n=t/this.samples_to_frames(t)/this.config.sampling_rate,r=[];for(let t of e.tolist()){let e=[],i=-1;for(let n=0;n<t.length;++n){let[r,a]=lc(oc(t[n])),[o,s]=[n,n+1];a===i?(e.at(-1).end=s,e.at(-1).score+=r):(i=a,e.push({id:a,start:o,end:s,score:r}))}r.push(e.map(({id:e,start:t,end:r,score:i})=>({id:e,start:t*n,end:r*n,confidence:i/(r-t)})))}return r}},Td=class extends Bu{constructor(e){super(e);let t=this.config.sampling_rate,n=nd(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0);this.mel_filters=n,this.window=cd(400,`povey`,{periodic:!1})}async _extract_fbank_features(e,t){return e=e.map(e=>e*32768),sd(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e,{padding:t=!0,pad_to_multiple_of:n=2,do_normalize_per_mel_bins:r=!0,return_attention_mask:i=!0}={}){Vu(e,`SeamlessM4TFeatureExtractor`);let a=await this._extract_fbank_features(e,this.config.max_length);if(r){let[e,t]=a.dims,n=a.data;for(let r=0;r<t;++r){let i=0;for(let a=0;a<e;++a)i+=n[a*t+r];let a=i/e,o=0;for(let i=0;i<e;++i)o+=(n[i*t+r]-a)**2;o/=e-1;let s=Math.sqrt(o+1e-7);for(let i=0;i<e;++i){let e=i*t+r;n[e]=(n[e]-a)/s}}}let o;if(t){let[e,t]=a.dims,r=a.data,s=e%n;if(s>0){let n=new Float32Array(t*(e+s));n.set(r),n.fill(this.config.padding_value,r.length);let c=e+s;a=new U(a.type,n,[c,t]),i&&(o=new U(`int64`,new BigInt64Array(c),[1,c]),o.data.fill(1n,0,e))}}let[s,c]=a.dims,l=this.config.stride;if(s%l!==0)throw Error(`The number of frames (${s}) must be a multiple of the stride (${l}).`);let u=a.view(1,Math.floor(s/l),c*l),d={input_features:u};if(i){let e=u.dims[1],t=new BigInt64Array(e);if(o){let e=o.data;for(let n=1,r=0;n<s;n+=l,++r)t[r]=e[n]}else t.fill(1n);d.attention_mask=new U(`int64`,t,[1,e])}return d}},Ed=class extends yd{},Dd=class extends Bu{},Od=class extends Bu{_zero_mean_unit_var_norm(e){let t=e.reduce((e,t)=>e+t,0)/e.length,n=e.reduce((e,n)=>e+(n-t)**2,0)/e.length;return e.map(e=>(e-t)/Math.sqrt(n+1e-7))}async _call(e){Vu(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 U(`float32`,t,n),attention_mask:new U(`int64`,new BigInt64Array(t.length).fill(1n),n)}}},kd=class extends Bu{constructor(e){super(e);let t=this.config.sampling_rate,n=nd(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0);this.mel_filters=n,this.window=cd(400,`hamming`,{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(e){return e=e.map(e=>e*32768),sd(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(e){Vu(e,`WeSpeakerFeatureExtractor`);let t=(await this._extract_fbank_features(e)).unsqueeze_(0);if(this.config.fbank_centering_span===null){let e=t.mean(1).data,n=t.data,[r,i,a]=t.dims;for(let t=0;t<r;++t){let r=t*i*a,o=t*a;for(let t=0;t<i;++t){let i=r+t*a;for(let t=0;t<a;++t)n[i+t]-=e[o+t]}}}return{input_features:t}}},Ad=class extends Bu{constructor(e){super(e),this.config.mel_filters??=nd(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,`slaney`,`slaney`),this.window=cd(this.config.n_fft,`hann`)}async _extract_fbank_features(e,{center:t=!0}={}){let{n_fft:n,hop_length:r,mel_filters:i,global_log_mel_max:a}=this.config,o=Math.floor(t?e.length/r:(e.length-n)/r);return await sd(e,this.window,n,r,{power:2,mel_filters:i,log_mel:`log10_max_norm`,max_log_mel:a,center:t,max_num_frames:o,do_pad:!1})}async _call(e,{center:t=!0}={}){return Vu(e,`VoxtralRealtimeFeatureExtractor`),{input_features:(await this._extract_fbank_features(e,{center:t})).unsqueeze_(0)}}},jd=class extends Bu{constructor(e){super(e),this.config.mel_filters??=nd(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,`slaney`,`slaney`),this.window=cd(this.config.n_fft,`hann`)}async _extract_fbank_features(e){return await sd(e,this.window,this.config.n_fft,this.config.hop_length,{power:2,mel_filters:this.config.mel_filters,log_mel:`log10_max_norm`,max_num_frames:Math.min(Math.floor(e.length/this.config.hop_length),this.config.nb_max_frames)})}async _call(e,{max_length:t=null}={}){Vu(e,`WhisperFeatureExtractor`);let n,r=t??this.config.n_samples;return e.length>r?(e.length>this.config.n_samples&&N.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`."),n=e.slice(0,r)):(n=new Float32Array(r),n.set(e)),{input_features:(await this._extract_fbank_features(n)).unsqueeze_(0)}}},Md=class{static async from_pretrained(e,t={}){let n=await rc(e,Iu,!0,t),r=n.feature_extractor_type,i=Hu[r];if(!i)throw Error(`Unknown feature_extractor_type: '${r}'. Please report this at ${Fu}.`);return new i(n)}},Nd=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e,t=null){let n=this.tokenizer(e),r=t?await this.feature_extractor(t):{};return{...n,...r}}},Pd=new Set([`ja`,`zh`]),Fd=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;static uses_processor_config=!0;get_decoder_prompt_ids(e=`en`){let t=[`▁`,`<|startofcontext|>`,`<|startoftranscript|>`,`<|emo:undefined|>`,`<|${e}|>`,`<|${e}|>`,`<|pnc|>`,`<|noitn|>`,`<|notimestamp|>`,`<|nodiarize|>`];return this.tokenizer.convert_tokens_to_ids(t)}static join_chunks(e,t=`en`){let n=e.filter(e=>e&&e.trim());if(n.length===0)return``;let r=Pd.has(t)?``:` `;return[n[0].trimEnd(),...n.slice(1).map(e=>e.trim())].join(r)}async _call(e){return await this.feature_extractor(e)}},Id={},Ld,Rd,zd;if(j.IS_WEB_ENV)Ld=(e,t)=>{if(!self.OffscreenCanvas)throw Error(`OffscreenCanvas not supported by this environment.`);return new self.OffscreenCanvas(e,t)},zd=self.createImageBitmap,Rd=self.ImageData;else if(Id)zd=async e=>{let t=(await e.metadata()).channels,{data:n,info:r}=await e.rotate().raw().toBuffer({resolveWithObject:!0}),i=new Hd(new Uint8ClampedArray(n),r.width,r.height,r.channels);return t!==void 0&&t!==r.channels&&i.convert(t),i};else throw Error(`Unable to load image processing library.`);var Bd={0:`nearest`,1:`lanczos`,2:`bilinear`,3:`bicubic`,4:`box`,5:`hamming`},Vd=new Map([[`png`,`image/png`],[`jpg`,`image/jpeg`],[`jpeg`,`image/jpeg`],[`gif`,`image/gif`]]),Hd=class e{constructor(e,t,n,r){this.data=e,this.width=t,this.height=n,this.channels=r}get size(){return[this.width,this.height]}static async read(t){if(t instanceof e)return t;if(typeof t==`string`||t instanceof URL)return await this.fromURL(t);if(t instanceof Blob)return await this.fromBlob(t);if(typeof HTMLCanvasElement<`u`&&t instanceof HTMLCanvasElement||typeof OffscreenCanvas<`u`&&t instanceof OffscreenCanvas)return this.fromCanvas(t);throw Error(`Unsupported input type: ${typeof t}`)}static fromCanvas(t){if(!j.IS_WEB_ENV)throw Error(`fromCanvas() is only supported in browser environments.`);let n=t.getContext(`2d`).getImageData(0,0,t.width,t.height).data;return new e(n,t.width,t.height,4)}static async fromURL(e){let t=await Js(e);if(t.status!==200)throw Error(`Unable to read image from "${e}" (${t.status} ${t.statusText})`);let n=await t.blob();return this.fromBlob(n)}static async fromBlob(e){if(j.IS_WEB_ENV){let t=await zd(e),n=Ld(t.width,t.height).getContext(`2d`);return n.drawImage(t,0,0),new this(n.getImageData(0,0,t.width,t.height).data,t.width,t.height,4)}else{let t=Id(await e.arrayBuffer());return await zd(t)}}static fromTensor(t,n=`CHW`){if(t.dims.length!==3)throw Error(`Tensor should have 3 dimensions, but has ${t.dims.length} dimensions.`);if(n===`CHW`)t=t.transpose(1,2,0);else if(n!==`HWC`)throw Error(`Unsupported channel format: ${n}`);if(!(t.data instanceof Uint8ClampedArray||t.data instanceof Uint8Array))throw Error(`Unsupported tensor type: ${t.type}`);switch(t.dims[2]){case 1:case 2:case 3:case 4:return new e(t.data,t.dims[1],t.dims[0],t.dims[2]);default:throw Error(`Unsupported number of channels: ${t.dims[2]}`)}}grayscale(){if(this.channels===1)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 r=this.data[t],i=this.data[t+1],a=this.data[t+2];e[n++]=Math.round(.2989*r+.587*i+.114*a)}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(this.channels===3)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(this.channels===4)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)}putAlpha(e){if(e.width!==this.width||e.height!==this.height)throw Error(`Expected mask size to be ${this.width}x${this.height}, but got ${e.width}x${e.height}`);if(e.channels!==1)throw Error(`Expected mask to have 1 channel, but got ${e.channels}`);let t=this.data,n=e.data,r=this.width*this.height;if(this.channels===3){let e=new Uint8ClampedArray(r*4);for(let i=0,a=0,o=0;i<r;++i)e[o++]=t[a++],e[o++]=t[a++],e[o++]=t[a++],e[o++]=n[i];return this._update(e,this.width,this.height,4)}else if(this.channels===4){for(let e=0;e<r;++e)t[4*e+3]=n[e];return this}throw Error(`Expected image to have 3 or 4 channels, but got ${this.channels}`)}async resize(t,n,{resample:r=2}={}){if(this.width===t&&this.height===n)return this;let i=Bd[r]??r,a=oi(t),o=oi(n);if(a&&o)return this;if(a?t=n/this.height*this.width:o&&(n=t/this.width*this.height),j.IS_WEB_ENV){let r=this.channels,i=this.toCanvas(),a=Ld(t,n).getContext(`2d`);return a.drawImage(i,0,0,t,n),new e(a.getImageData(0,0,t,n).data,t,n,4).convert(r)}else{let e=this.toSharp();switch(i){case`box`:case`hamming`:(i===`box`||i===`hamming`)&&(N.warn(`Resampling method ${i} is not yet supported. Using bilinear instead.`),i=`bilinear`);case`nearest`:case`bilinear`:case`bicubic`:e=e.affine([t/this.width,0,0,n/this.height],{interpolator:i});break;case`lanczos`:e=e.resize({width:t,height:n,fit:`fill`,kernel:`lanczos3`});break;default:throw Error(`Resampling method ${i} is not supported.`)}return await zd(e)}}async pad([t,n,r,i]){if(t=Math.max(t,0),n=Math.max(n,0),r=Math.max(r,0),i=Math.max(i,0),t===0&&n===0&&r===0&&i===0)return this;if(j.IS_WEB_ENV){let a=this.channels,o=this.toCanvas(),s=this.width+t+n,c=this.height+r+i,l=Ld(s,c).getContext(`2d`);return l.drawImage(o,0,0,this.width,this.height,t,r,this.width,this.height),new e(l.getImageData(0,0,s,c).data,s,c,4).convert(a)}else{let e=this.toSharp().extend({left:t,right:n,top:r,bottom:i});return await zd(e)}}async crop([t,n,r,i]){if(t=Math.max(t,0),n=Math.max(n,0),r=Math.min(r,this.width-1),i=Math.min(i,this.height-1),t===0&&n===0&&r===this.width-1&&i===this.height-1)return this;let a=r-t+1,o=i-n+1;if(j.IS_WEB_ENV){let r=this.channels,i=this.toCanvas(),s=Ld(a,o).getContext(`2d`);return s.drawImage(i,t,n,a,o,0,0,a,o),new e(s.getImageData(0,0,a,o).data,a,o,4).convert(r)}else{let e=this.toSharp().extract({left:t,top:n,width:a,height:o});return await zd(e)}}async center_crop(t,n){if(this.width===t&&this.height===n)return this;let r=(this.width-t)/2,i=(this.height-n)/2;if(j.IS_WEB_ENV){let a=this.channels,o=this.toCanvas(),s=Ld(t,n).getContext(`2d`),c=0,l=0,u=0,d=0;return r>=0?c=r:u=-r,i>=0?l=i:d=-i,s.drawImage(o,c,l,t,n,u,d,t,n),new e(s.getImageData(0,0,t,n).data,t,n,4).convert(a)}else{let e=this.toSharp();if(r>=0&&i>=0)e=e.extract({left:Math.floor(r),top:Math.floor(i),width:t,height:n});else if(r<=0&&i<=0){let a=Math.floor(-i),o=Math.floor(-r);e=e.extend({top:a,left:o,right:t-this.width-o,bottom:n-this.height-a})}else{let a=[0,0],o=0;i<0?(a[0]=Math.floor(-i),a[1]=n-this.height-a[0]):o=Math.floor(i);let s=[0,0],c=0;r<0?(s[0]=Math.floor(-r),s[1]=t-this.width-s[0]):c=Math.floor(r),e=e.extend({top:a[0],bottom:a[1],left:s[0],right:s[1]}).extract({left:c,top:o,width:t,height:n})}return await zd(e)}}async toBlob(e=`image/png`,t=1){if(!j.IS_WEB_ENV)throw Error(`toBlob() is only supported in browser environments.`);return await this.toCanvas().convertToBlob({type:e,quality:t})}toTensor(e=`CHW`){let t=new U(`uint8`,new Uint8Array(this.data),[this.height,this.width,this.channels]);if(e!==`HWC`)if(e===`CHW`)t=t.permute(2,0,1);else throw Error(`Unsupported channel format: ${e}`);return t}toCanvas(){if(!j.IS_WEB_ENV)throw Error(`toCanvas() is only supported in browser environments.`);let e=this.clone().rgba(),t=Ld(e.width,e.height),n=new Rd(e.data,e.width,e.height);return t.getContext(`2d`).putImageData(n,0,0),t}split(){let{data:t,width:n,height:r,channels:i}=this,a=t.constructor,o=t.length/i,s=Array.from({length:i},()=>new a(o));for(let e=0;e<o;++e){let n=i*e;for(let r=0;r<i;++r)s[r][e]=t[n+r]}return s.map(t=>new e(t,n,r,1))}_update(e,t,n,r=null){return this.data=e,this.width=t,this.height=n,r!==null&&(this.channels=r),this}clone(){return new e(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(j.IS_WEB_ENV){if(j.IS_WEBWORKER_ENV)throw Error(`Unable to save an image from a Web Worker.`);let t=e.split(`.`).pop().toLowerCase(),n=Vd.get(t)??`image/png`;return Wu(e,await this.toBlob(n))}else if(j.IS_FS_AVAILABLE)await this.toSharp().toFile(e);else throw Error(`Unable to save the image because filesystem is disabled in this environment.`)}toSharp(){if(j.IS_WEB_ENV)throw Error(`toSharp() is only supported in server-side environments.`);return Id(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}};Hd.read.bind(Hd);function Ud(e,t,n=0,r=null){let i=e/t,a=gc(i)*t;return r!==null&&a>r&&(a=Math.floor(i)*t),a<n&&(a=Math.ceil(i)*t),a}function Wd([e,t],n){return[Math.max(Math.floor(e/n),1)*n,Math.max(Math.floor(t/n),1)*n]}function Gd([e,t,n,r]){return[e-n/2,t-r/2,e+n/2,t+r/2]}function Kd(e,t=.5,n=null,r=!1){let i=e.logits,a=e.pred_boxes,[o,s,c]=i.dims;if(n!==null&&n.length!==o)throw Error(`Make sure that you pass in as many target sizes as the batch dimension of the logits`);let l=[];for(let e=0;e<o;++e){let o=n===null?null:n[e],u={boxes:[],classes:[],scores:[]},d=i[e],f=a[e];for(let e=0;e<s;++e){let n=d[e],i=[],a;if(r){a=n.sigmoid().data;for(let e=0;e<a.length;++e)a[e]>t&&i.push(e)}else{let e=lc(n.data)[1];if(e===c-1||(a=oc(n.data),a[e]<t))continue;i.push(e)}for(let t of i){let n=f[e].data;n=Gd(n),o!==null&&(n=n.map((e,t)=>e*o[(t+1)%2])),u.boxes.push(n),u.classes.push(t),u.scores.push(a[t])}}l.push(u)}return l}function qd(e,t=null){let n=e.logits,r=n.dims[0];if(t!==null&&t.length!==r)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<r;++e){let r=t===null?null:t[e],a=n[e];r!==null&&(a=nl(a,r,`bilinear`,!1));let[o,s]=r??a.dims.slice(-2),c=new U(`int32`,new Int32Array(o*s),[o,s]),l=a[0].data,u=c.data;for(let e=1;e<a.dims[0];++e){let t=a[e].data;for(let n=0;n<t.length;++n)t[n]>l[n]&&(l[n]=t[n],u[n]=e)}let d=Array(a.dims[0]);for(let e=0;e<u.length;++e){let t=u[e];d[t]=t}let f=d.filter(e=>e!==void 0);i.push({segmentation:c,labels:f})}return i}function Jd(e,t,n,r){let i=[],a=[],o=[];for(let s=0;s<e.dims[0];++s){let c=e[s],l=t[s],u=lc(c.data)[1];if(u===r)continue;let d=oc(c.data)[u];d>n&&(i.push(l),a.push(d),o.push(u))}return[i,a,o]}function Yd(e,t,n,r=.5,i=.8){let a=[],o=0,s=0,c=t[n].data;for(let t=0;t<e.length;++t)e[t]===n&&(a.push(t),++o),c[t]>=r&&++s;let l=o>0&&s>0;return l&&=o/s>i,[l,a]}function Xd(e,t,n,r,i,a=null,o=null){let[s,c]=o??e[0].dims,l=new U(`int32`,new Int32Array(s*c),[s,c]),u=[];if(o!==null)for(let t=0;t<e.length;++t)e[t]=nl(e[t],o,`bilinear`,!1);let d=new Int32Array(e[0].data.length),f=new Float32Array(e[0].data.length);for(let n=0;n<e.length;++n){let r=t[n],i=e[n].data;for(let e=0;e<i.length;++e)i[e]*=r,i[e]>f[e]&&(d[e]=n,f[e]=i[e])}let p=0,m=l.data;for(let a=0;a<n.length;++a){let o=n[a],[s,c]=Yd(d,e,a,r,i);if(s){++p;for(let e of c)m[e]=p;u.push({id:p,label_id:o,score:t[a]})}}return[l,u]}function Zd(e,t,n=28,r=3136,i=784*1280,a=1){if(e<n||t<n){let r=Math.max(n/e,n/t);e=Math.round(e*r),t=Math.round(t*r)}if(Math.max(e,t)/Math.min(e,t)>200)throw Error(`absolute aspect ratio must be smaller than 200, got ${Math.max(e,t)/Math.min(e,t)}`);let o=Math.round(e/n)*n,s=Math.round(t/n)*n;if(a*o*s>i){let r=Math.sqrt(a*e*t/i);o=Math.max(n,Math.floor(e/r/n)*n),s=Math.max(n,Math.floor(t/r/n)*n)}else if(a*o*s<r){let i=Math.sqrt(r/(a*e*t));o=Math.ceil(e*i/n)*n,s=Math.ceil(t*i/n)*n}return[s,o]}function Qd(e,t=.5,n=.5,r=.8,i=null,a=null){i===null&&(N.warn("`label_ids_to_fuse` unset. No instance will be fused."),i=new Set);let o=e.class_queries_logits??e.logits,s=(e.masks_queries_logits??e.pred_masks).sigmoid(),[c,l,u]=o.dims;if(--u,a!==null&&a.length!==c)throw Error(`Make sure that you pass in as many target sizes as the batch dimension of the logits`);let d=[];for(let e=0;e<c;++e){let c=a===null?null:a[e],l=o[e],f=s[e],[p,m,h]=Jd(l,f,t,u);if(h.length===0){let[e,t]=c??f.dims.slice(-2),n=new U(`int32`,new Int32Array(e*t).fill(-1),[e,t]);d.push({segmentation:n,segments_info:[]});continue}let[g,_]=Xd(p,m,h,n,r,i,c);d.push({segmentation:g,segments_info:_})}return d}function $d(e,t=.5,n=null){throw Error("`post_process_instance_segmentation` is not yet implemented.")}var q=class extends ni{constructor(e){super(),this.image_mean=e.image_mean??e.mean,this.image_std=e.image_std??e.std,this.resample=e.resample??2,this.do_rescale=e.do_rescale??!0,this.rescale_factor=e.rescale_factor??1/255,this.do_normalize=e.do_normalize,this.do_thumbnail=e.do_thumbnail,this.size=e.size??e.image_size,this.do_resize=e.do_resize??this.size!==void 0,this.size_divisibility=e.size_divisibility??e.size_divisor,this.do_center_crop=e.do_center_crop,this.crop_size=e.crop_size,this.do_convert_rgb=e.do_convert_rgb??!0,this.do_crop_margin=e.do_crop_margin,this.pad_size=e.pad_size,this.do_pad=e.do_pad,this.min_pixels=e.min_pixels,this.max_pixels=e.max_pixels,this.do_pad&&!this.pad_size&&!this.size_divisibility&&this.size&&this.size.width!==void 0&&this.size.height!==void 0&&(this.pad_size=this.size),this.do_flip_channel_order=e.do_flip_channel_order??!1,this.config=e}async thumbnail(e,t,n=2){let r=e.height,i=e.width,a=t.height,o=t.width,s=Math.min(r,a),c=Math.min(i,o);return s===r&&c===i?e:(r>i?c=Math.floor(i*s/r):i>r&&(s=Math.floor(r*c/i)),await e.resize(c,s,{resample:n}))}async crop_margin(e,t=200){let n=e.clone().grayscale(),r=cc(n.data)[0],i=lc(n.data)[0]-r;if(i===0)return e;let a=t/255,o=n.width,s=n.height,c=0,l=0,u=n.data;for(let e=0;e<n.height;++e){let t=e*n.width;for(let d=0;d<n.width;++d)(u[t+d]-r)/i<a&&(o=Math.min(o,d),s=Math.min(s,e),c=Math.max(c,d),l=Math.max(l,e))}return e=await e.crop([o,s,c,l]),e}pad_image(e,t,n,{mode:r=`constant`,center:i=!1,constant_values:a=0}={}){let[o,s,c]=t,l,u;if(typeof n==`number`?(l=n,u=n):n===`square`?l=u=Math.max(o,s):(l=n.width,u=n.height),l!==s||u!==o){let n=new Float32Array(l*u*c);if(Array.isArray(a))for(let e=0;e<n.length;++e)n[e]=a[e%c];else a!==0&&n.fill(a);let[d,f]=i?[Math.floor((l-s)/2),Math.floor((u-o)/2)]:[0,0];for(let t=0;t<o;++t){let r=(t+f)*l,i=t*s;for(let t=0;t<s;++t){let a=(r+t+d)*c,o=(i+t)*c;for(let t=0;t<c;++t)n[a+t]=e[o+t]}}if(r===`symmetric`){if(i)throw Error("`center` padding is not supported when `mode` is set to `symmetric`.");let t=o-1,r=s-1;for(let i=0;i<u;++i){let a=i*l,u=ui(i,t)*s;for(let t=0;t<l;++t){if(i<o&&t<s)continue;let l=(a+t)*c,d=(u+ui(t,r))*c;for(let t=0;t<c;++t)n[l+t]=e[d+t]}}}e=n,t=[u,l,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[n,r]=e.size,i,a;if(this.do_thumbnail){let{height:e,width:n}=t;i=Math.min(e,n)}else Number.isInteger(t)?(i=t,a=this.config.max_size??i):t!==void 0&&(i=t.shortest_edge,a=t.longest_edge);if(i!==void 0||a!==void 0){let e=i===void 0?1:Math.max(i/n,i/r),t=n*e,o=r*e,s=a===void 0?1:Math.min(a/t,a/o),c=Math.floor(Number((t*s).toFixed(2))),l=Math.floor(Number((o*s).toFixed(2)));return this.size_divisibility!==void 0&&([c,l]=Wd([c,l],this.size_divisibility)),[c,l]}else if(t!==void 0&&t.width!==void 0&&t.height!==void 0){let e=t.width,i=t.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let t=i/r,a=e/n;Math.abs(1-a)<Math.abs(1-t)?t=a:a=t,i=Ud(t*r,this.config.ensure_multiple_of),e=Ud(a*n,this.config.ensure_multiple_of)}return[e,i]}else if(this.size_divisibility!==void 0)return Wd([n,r],this.size_divisibility);else throw Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(t)}`)}async resize(e){let[t,n]=this.get_resize_output_image_size(e,this.size);return await e.resize(t,n,{resample:this.resample})}async preprocess(e,{do_normalize:t=null,do_pad:n=null,do_convert_rgb:r=null,do_convert_grayscale:i=null,do_flip_channel_order:a=null}={}){this.do_crop_margin&&(e=await this.crop_margin(e));let[o,s]=e.size;if(r??this.do_convert_rgb?e=e.rgb():i&&(e=e.grayscale()),this.do_resize&&(e=await this.resize(e)),this.do_thumbnail&&(e=await this.thumbnail(e,this.size,this.resample)),this.do_center_crop){let t,n;Number.isInteger(this.crop_size)?(t=this.crop_size,n=this.crop_size):(t=this.crop_size.width,n=this.crop_size.height),e=await e.center_crop(t,n)}let c=[e.height,e.width],l=Float32Array.from(e.data),u=[e.height,e.width,e.channels];if(this.do_rescale&&this.rescale(l),t??this.do_normalize){let t=this.image_mean;Array.isArray(this.image_mean)||(t=Array(e.channels).fill(t));let n=this.image_std;if(Array.isArray(this.image_std)||(n=Array(e.channels).fill(n)),t.length!==e.channels||n.length!==e.channels)throw Error(`When set to arrays, the length of \`image_mean\` (${t.length}) and \`image_std\` (${n.length}) must match the number of channels in the image (${e.channels}).`);for(let r=0;r<l.length;r+=e.channels)for(let i=0;i<e.channels;++i)l[r+i]=(l[r+i]-t[i])/n[i]}if(n??this.do_pad){if(this.pad_size){let t=this.pad_image(l,[e.height,e.width,e.channels],this.pad_size);[l,u]=t}else if(this.size_divisibility){let e=Math.ceil(u[1]/this.size_divisibility)*this.size_divisibility,t=Math.ceil(u[0]/this.size_divisibility)*this.size_divisibility;[l,u]=this.pad_image(l,u,{width:e,height:t})}}if(a??this.do_flip_channel_order){if(u[2]!==3)throw Error(`Flipping channel order is only supported for RGB images.`);for(let e=0;e<l.length;e+=3){let t=l[e];l[e]=l[e+2],l[e+2]=t}}let d=new U(`float32`,l,u).permute(2,0,1);return{original_size:[s,o],reshaped_input_size:c,pixel_values:d}}async _call(e,...t){Array.isArray(e)||(e=[e]);let n=await Promise.all(e.map(e=>this.preprocess(e)));return{pixel_values:pl(n.map(e=>e.pixel_values),0),original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}static async from_pretrained(e,t={}){let n=await rc(e,Lu,!0,t);return new this(n)}},ef={};Tr(ef,{BeitFeatureExtractor:()=>tf,BitImageProcessor:()=>nf,CHMv2ImageProcessor:()=>af,CLIPFeatureExtractor:()=>sf,CLIPImageProcessor:()=>of,ChineseCLIPFeatureExtractor:()=>rf,ConvNextFeatureExtractor:()=>lf,ConvNextImageProcessor:()=>cf,DINOv3ViTImageProcessor:()=>mf,DPTFeatureExtractor:()=>vf,DPTImageProcessor:()=>_f,DeiTFeatureExtractor:()=>df,DeiTImageProcessor:()=>uf,DetrFeatureExtractor:()=>pf,DetrImageProcessor:()=>ff,DonutFeatureExtractor:()=>gf,DonutImageProcessor:()=>hf,EfficientNetImageProcessor:()=>yf,GLPNFeatureExtractor:()=>Ef,Gemma3ImageProcessor:()=>bf,Gemma4ImageProcessor:()=>Cf,Glm46VImageProcessor:()=>Tf,GroundingDinoImageProcessor:()=>Df,Idefics3ImageProcessor:()=>Of,ImageFeatureExtractor:()=>q,ImageProcessor:()=>q,JinaCLIPImageProcessor:()=>Af,Lfm2VlImageProcessor:()=>If,LlavaOnevisionImageProcessor:()=>Lf,Mask2FormerImageProcessor:()=>Bf,MaskFormerFeatureExtractor:()=>zf,MaskFormerImageProcessor:()=>Rf,MobileNetV1FeatureExtractor:()=>Hf,MobileNetV1ImageProcessor:()=>Vf,MobileNetV2FeatureExtractor:()=>Wf,MobileNetV2ImageProcessor:()=>Uf,MobileNetV3FeatureExtractor:()=>Kf,MobileNetV3ImageProcessor:()=>Gf,MobileNetV4FeatureExtractor:()=>Jf,MobileNetV4ImageProcessor:()=>qf,MobileViTFeatureExtractor:()=>Xf,MobileViTImageProcessor:()=>Yf,NougatImageProcessor:()=>Zf,OwlViTFeatureExtractor:()=>$f,OwlViTImageProcessor:()=>Qf,Owlv2ImageProcessor:()=>ep,Phi3VImageProcessor:()=>op,PixtralImageProcessor:()=>sp,PvtImageProcessor:()=>cp,Qwen2VLImageProcessor:()=>wf,RTDetrImageProcessor:()=>lp,Sam2ImageProcessor:()=>up,Sam3ImageProcessor:()=>up,SamImageProcessor:()=>up,SapiensFeatureExtractor:()=>fp,SapiensImageProcessor:()=>dp,SegformerFeatureExtractor:()=>mp,SegformerImageProcessor:()=>pp,SiglipImageProcessor:()=>hp,SmolVLMImageProcessor:()=>Of,Swin2SRImageProcessor:()=>gp,VLMImageProcessor:()=>kf,ViTFeatureExtractor:()=>vp,ViTImageProcessor:()=>_p,VitMatteImageProcessor:()=>yp,VitPoseImageProcessor:()=>bp,YolosFeatureExtractor:()=>Sp,YolosImageProcessor:()=>xp});var tf=class extends q{},nf=class extends q{},rf=class extends q{},af=class extends q{},of=class extends q{},sf=class extends of{},cf=class extends q{constructor(e){super(e),this.crop_pct=this.config.crop_pct??224/256}async resize(e){let t=this.size?.shortest_edge;if(t===void 0)throw Error(`Size dictionary must contain 'shortest_edge' key.`);if(t<384){let n=Math.floor(t/this.crop_pct),[r,i]=this.get_resize_output_image_size(e,{shortest_edge:n});e=await e.resize(r,i,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}},lf=class extends cf{},uf=class extends q{},df=class extends uf{},ff=class extends q{async _call(e){let t=await super._call(e),n=yl([t.pixel_values.dims[0],64,64],1n);return{...t,pixel_mask:n}}post_process_object_detection(...e){return Kd(...e)}post_process_panoptic_segmentation(...e){return Qd(...e)}post_process_instance_segmentation(...e){return $d(...e)}},pf=class extends ff{},mf=class extends q{},hf=class extends q{pad_image(e,t,n,r={}){let[i,a,o]=t,s=this.image_mean;Array.isArray(this.image_mean)||(s=Array(o).fill(s));let c=this.image_std;Array.isArray(c)||(c=Array(o).fill(s));let l=s.map((e,t)=>-e/c[t]);return super.pad_image(e,t,n,{center:!0,constant_values:l,...r})}},gf=class extends hf{},_f=class extends q{},vf=class extends _f{},yf=class extends q{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(e=>e*e))}},bf=class extends q{};function xf(e,t,n,r,i){let a=r*n**2,o=Math.sqrt(a/(e*t)),s=i*n,c=Math.floor(o*e/s)*s,l=Math.floor(o*t/s)*s;if(c===0&&l===0)throw Error(`Attempting to resize to a 0 x 0 image. Resized height should be divisible by \`pooling_kernel_size * patch_size\`=${s}.`);let u=Math.floor(r/i**2)*s;return c===0?(c=s,l=Math.min(Math.floor(t/e)*s,u)):l===0&&(l=s,c=Math.min(Math.floor(e/t)*s,u)),[c,l]}function Sf(e,t,n,r,i,a,o){let s=Math.floor(t/i),c=Math.floor(n/i),l=s*c,u=i*i*r,d=new Float32Array(a*u),f=0;for(let t=0;t<s;++t)for(let a=0;a<c;++a)for(let o=0;o<i;++o){let s=(t*i+o)*n*r+a*i*r;for(let t=0;t<i;++t){let n=s+t*r;for(let t=0;t<r;++t)d[f++]=e[n+t]}}let p=new BigInt64Array(a*2).fill(-1n),m=0;for(let e=0;e<s;++e)for(let t=0;t<c;++t)p[m++]=BigInt(t),p[m++]=BigInt(e);return{patches:new U(`float32`,d,[a,u]),positions:new U(`int64`,p,[a,2]),num_soft_tokens:Math.floor(l/o**2)}}var Cf=class extends ni{constructor(e){super(),this.config=e,this.patch_size=e.patch_size??16,this.max_soft_tokens=e.max_soft_tokens??280,this.pooling_kernel_size=e.pooling_kernel_size??3,this.resample=e.resample??3,this.rescale_factor=e.rescale_factor??1/255,this.do_rescale=e.do_rescale??!0,this.do_resize=e.do_resize??!0,this.do_convert_rgb=e.do_convert_rgb??!0}async _call(e){Array.isArray(e)||(e=[e]);let{patch_size:t,pooling_kernel_size:n}=this,r=this.max_soft_tokens*n**2,i=[],a=[],o=[];for(let s of e){if(this.do_convert_rgb&&(s=s.rgb()),this.do_resize){let[e,i]=xf(s.height,s.width,t,r,n);(e!==s.height||i!==s.width)&&(s=await s.resize(i,e,{resample:this.resample}))}let e=Float32Array.from(s.data);if(this.do_rescale)for(let t=0;t<e.length;++t)e[t]*=this.rescale_factor;let{patches:c,positions:l,num_soft_tokens:u}=Sf(e,s.height,s.width,s.channels,t,r,n);i.push(c),a.push(l),o.push(u)}return{pixel_values:pl(i,0),image_position_ids:pl(a,0),num_soft_tokens_per_image:o}}},wf=class extends q{constructor(e){super(e),this.min_pixels=e.min_pixels??e.size?.shortest_edge,this.max_pixels=e.max_pixels??e.size?.longest_edge,this.patch_size=e.patch_size,this.merge_size=e.merge_size}get_resize_output_image_size(e,t){let n=this.patch_size*this.merge_size;return Zd(e.height,e.width,n,this.min_pixels,this.max_pixels)}async _call(e,...t){let{pixel_values:n,original_sizes:r,reshaped_input_sizes:i}=await super._call(e,...t),a=n,{temporal_patch_size:o,merge_size:s,patch_size:c}=this.config;a.dims[0]===1&&(a=fl(Array.from({length:o},()=>a),0));let l=a.dims[0]/o,u=a.dims[1],d=Math.floor(a.dims[2]/c),f=Math.floor(a.dims[3]/c);return{pixel_values:a.view(l,o,u,Math.floor(d/s),s,c,Math.floor(f/s),s,c).permute(0,3,6,4,7,2,1,5,8).view(l*d*f,u*o*c*c),image_grid_thw:new U(`int64`,[l,d,f],[1,3]),original_sizes:r,reshaped_input_sizes:i}}},Tf=class extends wf{get_resize_output_image_size(e,t){let n=this.patch_size*this.merge_size,r=this.config.temporal_patch_size??2;return Zd(e.height,e.width,n,this.min_pixels,this.max_pixels,r)}},Ef=class extends q{},Df=class extends q{async _call(e){let t=await super._call(e),n=t.pixel_values.dims,r=xl([n[0],n[2],n[3]]);return{...t,pixel_mask:r}}},Of=class extends q{constructor(e){super(e),this.do_image_splitting=e.do_image_splitting??!0,this.max_image_size=e.max_image_size}get_resize_for_vision_encoder(e,t){let[n,r]=e.dims.slice(-2),i=r/n;return r>=n?(r=Math.ceil(r/t)*t,n=Math.floor(r/i),n=Math.ceil(n/t)*t):(n=Math.ceil(n/t)*t,r=Math.floor(n*i),r=Math.ceil(r/t)*t),{height:n,width:r}}async _call(e,{do_image_splitting:t=null,return_row_col_info:n=!1}={}){let r;if(!Array.isArray(e))r=[[e]];else{if(e.length===0||!e[0])throw Error(`No images provided.`);r=Array.isArray(e[0])?e:[e]}let i=[],a=[],o=[],s=[],c=[];for(let e of r){let n=await Promise.all(e.map(e=>this.preprocess(e)));s.push(...n.map(e=>e.original_size)),c.push(...n.map(e=>e.reshaped_input_size)),n.forEach(e=>e.pixel_values.unsqueeze_(0));let{longest_edge:r}=this.max_image_size,l;if(t??this.do_image_splitting){let e=Array(n.length),t=Array(n.length);l=await Promise.all(n.map(async(n,i)=>{let a=this.get_resize_for_vision_encoder(n.pixel_values,r),o=await rl(n.pixel_values,{size:[a.height,a.width]}),{frames:s,num_splits_h:c,num_splits_w:l}=await this.split_image(o,this.max_image_size);return e[i]=c,t[i]=l,fl(s,0)})),a.push(e),o.push(t)}else{let e=[r,r];l=await Promise.all(n.map(t=>rl(t.pixel_values,{size:e}))),a.push(Array(n.length).fill(0)),o.push(Array(n.length).fill(0))}i.push(fl(l,0))}let l=i.length,[u,d,f,p]=i[0].dims,m,h;if(l===1)m=i[0].unsqueeze_(0),h=yl([l,u,f,p],!0);else{let e=Math.max(...i.map(e=>e.dims.at(0)));h=yl([l,e,f,p],!0);let t=h.data,n=e*f*p;for(let r=0;r<l;++r){let a=i[r].dims[0];if(a<e){i[r]=fl([i[r],yl([e-a,d,f,p],0)],0);let o=r*n+a*f*p,s=(r+1)*n;t.fill(!1,o,s)}}m=pl(i,0)}return{pixel_values:m,pixel_attention_mask:h,original_sizes:s,reshaped_input_sizes:c,...n?{rows:a,cols:o}:{}}}async split_image(e,{longest_edge:t}){let n=t,r=t,i=[],[a,o]=e.dims.slice(-2),s=0,c=0;if(a>n||o>r){s=Math.ceil(a/n),c=Math.ceil(o/r);let t=Math.ceil(a/s),l=Math.ceil(o/c);for(let n=0;n<s;++n)for(let r=0;r<c;++r){let u,d,f,p;n===s-1?(d=a-t,p=a):(d=n*t,p=(n+1)*t),r===c-1?(u=o-l,f=o):(u=r*l,f=(r+1)*l);let m=await sl(e,[d,u],[p,f],[2,3]);i.push(m)}let u=n,d=r;(a!==u||o!==d)&&(e=await rl(e,{size:[u,d]}))}return i.push(e),{frames:i,num_splits_h:s,num_splits_w:c}}},kf=class extends q{constructor(e){super({do_pad:!0,pad_size:{width:e.image_size,height:e.image_size},...e}),this.constant_values=this.config.background_color.map(e=>e*this.rescale_factor)}pad_image(e,t,n,r){return super.pad_image(e,t,n,{constant_values:this.constant_values,center:!0,...r})}},Af=class extends q{constructor(e){let{resize_mode:t,fill_color:n,interpolation:r,size:i,...a}=e,o=t===`squash`?{width:i,height:i}:t===`shortest`?{shortest_edge:i}:{longest_edge:i},s=r===`bicubic`?3:2;super({...a,size:o,resample:s,do_center_crop:!0,crop_size:i,do_normalize:!0})}};function jf(e,t){return Math.round(e/t)*t}function Mf(e,t,n,r,i){let a=1/0,o=[1,1],s=n*r;for(let n of t){let t=Math.abs(e-n[0]/n[1]);t<a?(a=t,o=n):t===a&&s>.5*i*i*n[0]*n[1]&&(o=n)}return o}function Nf(e,t){let n=[],r=new Set;for(let i=e;i<=t;++i)for(let a=1;a<=i;++a)for(let o=1;o<=i;++o){let i=a*o;if(i>=e&&i<=t){let e=a<<16|o;r.has(e)||(r.add(e),n.push([a,o]))}}return n.sort((e,t)=>e[0]*e[1]-t[0]*t[1])}function Pf(e,t){let[n,r,i,a]=e.dims,o=Math.floor(i/t),s=Math.floor(a/t),c=t*t*r,l=e.data,u=new Float32Array(n*o*s*c),d=i*a;for(let e=0;e<n;++e){let n=e*r*d,i=e*o*s*c;for(let e=0;e<o;++e)for(let o=0;o<s;++o){let f=i+(e*s+o)*c;for(let i=0;i<t;++i){let s=(e*t+i)*a+o*t;for(let e=0;e<t;++e){let t=s+e;for(let e=0;e<r;++e)u[f++]=l[n+e*d+t]}}}}return new U(`float32`,u,[n,o*s,c])}function Ff(e,t){let[,n,r]=e.dims,i=new BigInt64Array(t);i.fill(1n,0,n);let a=e;if(n<t){let n=new Float32Array(t*r);n.set(e.data),a=new U(`float32`,n,[1,t,r])}return{padded:a,mask:new U(`int64`,i,[t])}}var If=class extends q{constructor(e){super(e),this.downsample_factor=e.downsample_factor??2,this.do_image_splitting=e.do_image_splitting??!0,this.min_tiles=e.min_tiles??2,this.max_tiles=e.max_tiles??10,this.use_thumbnail=e.use_thumbnail??!0,this.min_image_tokens=e.min_image_tokens??64,this.max_image_tokens=e.max_image_tokens??256,this.encoder_patch_size=e.encoder_patch_size??e.patch_size??16,this.tile_size=e.tile_size??512,this.max_pixels_tolerance=e.max_pixels_tolerance??2,this.return_row_col_info=e.return_row_col_info??!1;let t=this.max_image_tokens*this.downsample_factor**2,n=this.do_image_splitting?(this.tile_size/this.encoder_patch_size)**2:0;this.max_num_patches=Math.max(t,n)}_is_image_too_large(e,t){let n=this.encoder_patch_size*this.downsample_factor;return Math.max(this.encoder_patch_size,jf(e,n))*Math.max(this.encoder_patch_size,jf(t,n))>this.max_image_tokens*(this.encoder_patch_size*this.downsample_factor)**2*this.max_pixels_tolerance}_get_grid_layout(e,t){let n=Nf(this.min_tiles,this.max_tiles),[r,i]=Mf(t/e,n,t,e,this.tile_size);return{grid_width:r,grid_height:i,target_width:this.tile_size*r,target_height:this.tile_size*i}}async _call(e,{return_row_col_info:t=null}={}){let n;n=Array.isArray(e)?Array.isArray(e[0])?e:[e]:[[e]];let r=[],i=[],a=[],o=[],s=[],c=[];for(let e of n){let t=await Promise.all(e.map(e=>this.preprocess(e,{do_pad:!1})));for(let{pixel_values:e}of t){let[,t,n]=e.dims,l=e.unsqueeze_(0),u=this.encoder_patch_size*this.downsample_factor,d=u**2,[f,p]=Zd(Math.max(u,t),Math.max(u,n),u,this.min_image_tokens*d,this.max_image_tokens*d).map(e=>Math.max(u,e)),m,h=1,g=1,_=this._is_image_too_large(t,n),v=this.do_image_splitting&&!(this.min_tiles===1&&this.max_tiles===1);if(_&&v){let{grid_width:e,grid_height:r,target_width:i,target_height:a}=this._get_grid_layout(t,n);h=r,g=e;let o=await rl(l,{size:[a,i]});m=[];for(let t=0;t<r;++t)for(let n=0;n<e;++n){let e=t*this.tile_size,r=n*this.tile_size;m.push(o.slice(null,null,[e,e+this.tile_size],[r,r+this.tile_size]))}this.use_thumbnail&&e*r!==1&&m.push(await rl(l,{size:[p,f]}))}else m=[await rl(l,{size:[p,f]})];for(let e of m){let[,,t,n]=e.dims,{padded:o,mask:s}=Ff(Pf(e,this.encoder_patch_size),this.max_num_patches);r.push(o),i.push(s),a.push([Math.floor(t/this.encoder_patch_size),Math.floor(n/this.encoder_patch_size)])}o.push(h),s.push(g),c.push([p,f])}}let l={pixel_values:fl(r,0),pixel_attention_mask:pl(i,0),spatial_shapes:new U(`int64`,BigInt64Array.from(a.flat(),BigInt),[a.length,2])};return(t??this.return_row_col_info)&&(l.image_rows=o,l.image_cols=s,l.image_sizes=c),l}},Lf=class extends q{},Rf=class extends q{post_process_panoptic_segmentation(...e){return Qd(...e)}post_process_instance_segmentation(...e){return $d(...e)}},zf=class extends Rf{},Bf=class extends Rf{},Vf=class extends q{},Hf=class extends Vf{},Uf=class extends q{},Wf=class extends Uf{},Gf=class extends q{},Kf=class extends Gf{},qf=class extends q{},Jf=class extends qf{},Yf=class extends q{},Xf=class extends Yf{},Zf=class extends hf{},Qf=class extends q{post_process_object_detection(...e){return Kd(...e)}},$f=class extends Qf{},ep=class extends Qf{},tp=336,np=[2,3],{ceil:rp,floor:ip,sqrt:ap}=Math,op=class extends q{constructor(e){super({...e,do_normalize:!0,do_pad:!0,pad_size:`custom`,do_convert_rgb:!0,do_resize:!0}),this._num_crops=e.num_crops}calc_num_image_tokens_from_image_size(e,t){let{num_img_tokens:n}=this.config;return ip((ip(t/tp)*ip(e/tp)+1)*n+1+(ip(t/tp)+1)*ap(n))}get_resize_output_image_size(e,t){let n=this._num_crops,[r,i]=e.size,a=r/i,o=1;for(;o*Math.ceil(o/a)<=n;)o+=1;--o;let s=Math.floor(o*336);return[s,Math.floor(s/a)]}pad_image(e,t,n,r={}){let[i,a]=t,o=tp*rp(i/tp),s=tp*rp(a/tp),c=[1,1,1].map((e,t)=>(e-this.image_mean[t])/this.image_std[t]);return super.pad_image(e,t,{width:s,height:o},{center:!0,constant_values:c,...r})}async _call(e,{num_crops:t=null}={}){if(this._num_crops=t??=this.config.num_crops,t<4||ap(t)%1!=0)throw Error(`num_crops must be a square number >= 4`);Array.isArray(e)||(e=[e]);let n=e.length,r=await Promise.all(e.map(e=>this.preprocess(e))),i=r.map(e=>e.original_size),a=r.map(e=>e.reshaped_input_size),o=[];for(let{pixel_values:e}of r){e.unsqueeze_(0);let[n,r]=e.dims.slice(-2),i=await rl(e,{size:[tp,tp],mode:`bicubic`});if(t>0){let a=[],s=ap(t),c=ip(r/s),l=ip(n/s);for(let t=0;t<s;++t)for(let i=0;i<s;++i){let o,u,d,f;t===s-1?(u=n-l,f=n):(u=t*l,f=(t+1)*l),i===s-1?(o=r-c,d=r):(o=i*c,d=(i+1)*c);let p=await sl(e,[u,o],[f,d],np);a.push(p)}let u=await rl(fl(a,0),{size:[tp,tp],mode:`bicubic`});o.push(fl([i,u],0))}else o.push(i)}let s=pl(o,0),c=a.map(e=>e.map(e=>tp*rp(e/tp)));return{pixel_values:s,original_sizes:i,reshaped_input_sizes:a,image_sizes:new U(`int64`,c.flat(),[n,2]),num_img_tokens:c.map(([e,t])=>this.calc_num_image_tokens_from_image_size(t,e))}}},sp=class extends q{get_resize_output_image_size(e,t){let{longest_edge:n}=t;if(n===void 0)throw Error(`size must contain 'longest_edge'`);let[r,i]=e.size,a=Math.max(r,i)/n,o=r,s=i;a>1&&(o=Math.floor(r/a),s=Math.floor(i/a));let{patch_size:c,spatial_merge_size:l}=this.config;if(!l)throw Error(`config must contain 'spatial_merge_size'`);let u=c*l,d=Math.floor((o-1)/u)+1,f=Math.floor((s-1)/u)+1;return[d*u,f*u]}},cp=class extends q{},lp=class extends q{post_process_object_detection(...e){return Kd(...e)}},up=class extends q{reshape_input_points(e,t,n,r=!1){e=structuredClone(e);let i=si(e);if(i.length===3)r||(i=[1,...i]),e=[e];else if(i.length!==4)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let r=0;r<e.length;++r){let[i,a]=t[r],[o,s]=n[r],c=[s/a,o/i];for(let t=0;t<e[r].length;++t)for(let n=0;n<e[r][t].length;++n)for(let i=0;i<e[r][t][n].length;++i)e[r][t][n][i]*=c[i%2]}return new U(`float32`,Float32Array.from(e.flat(1/0)),i)}add_input_labels(e,t){let n=si(e);if(n.length===2)n=[1,...n],e=[e];else if(n.length!==3)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");if(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 U(`int64`,e.flat(1/0).map(BigInt),n)}async _call(e,{input_points:t=null,input_labels:n=null,input_boxes:r=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 r&&(i.input_boxes=this.reshape_input_points(r,i.original_sizes,i.reshaped_input_sizes,!0)),i}async post_process_masks(e,t,n,{mask_threshold:r=0,binarize:i=!0,pad_size:a=null}={}){let o=[];a=a??this.pad_size??this.size;let s=[a.height,a.width];for(let a=0;a<t.length;++a){let c=t[a],l=n[a],u=await rl(e[a],{mode:`bilinear`,size:s});if(u=u.slice(null,null,[0,l[0]],[0,l[1]]),u=await rl(u,{mode:`bilinear`,size:c}),i){let e=u.data,t=new Uint8Array(e.length);for(let n=0;n<e.length;++n)e[n]>r&&(t[n]=1);u=new U(`bool`,t,u.dims)}o.push(u)}return o}generate_crop_boxes(e,t,{crop_n_layers:n=0,overlap_ratio:r=512/1500,points_per_crop:i=32,crop_n_points_downscale_factor:a=1}={}){}},dp=class extends q{post_process_semantic_segmentation(...e){return qd(...e)}},fp=class extends dp{},pp=class extends q{post_process_semantic_segmentation(...e){return qd(...e)}},mp=class extends pp{},hp=class extends q{},gp=class extends q{pad_image(e,t,n,r={}){let[i,a,o]=t;return super.pad_image(e,t,{width:a+(n-a%n)%n,height:i+(n-i%n)%n},{mode:`symmetric`,center:!1,constant_values:-1,...r})}},_p=class extends q{},vp=class extends _p{},yp=class extends q{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))),r=await Promise.all(t.map(e=>this.preprocess(e,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:pl(n.map((e,t)=>fl([e.pixel_values,r[t].pixel_values],0)),0),original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}},bp=class extends q{post_process_pose_estimation(e,t,{threshold:n=null}={}){let r=e.tolist(),[i,a,o,s]=e.dims,c=[];for(let e=0;e<i;++e){let i=r[e],a=t[e],l=[];for(let e=0;e<a.length;++e){let t=a[e],r=[],c=[],u=[],d=t.at(-2)/s,f=t.at(-1)/o;for(let e=0;e<i.length;++e){let[t,a]=[0,0],o=0,s=-1/0,l=i[e];for(let e=0;e<l.length;++e){let n=l[e];for(let r=0;r<n.length;++r){let i=n[r];o+=i,s=Math.max(s,i),t+=(r+.5)*i,a+=e*i}}if(n!=null&&s<n)continue;let p=[d*t/o,f*a/o];r.push(p),u.push(e),c.push(s)}l.push({bbox:t,scores:c,labels:u,keypoints:r})}c.push(l)}return c}},xp=class extends q{post_process_object_detection(...e){return Kd(...e)}},Sp=class extends xp{},Cp=class{static async from_pretrained(e,t={}){let n=await rc(e,Lu,!0,t),r=n.image_processor_type??n.feature_extractor_type,i=ef[r?.replace(/Fast$/,``)];return i||=(r!==void 0&&N.warn(`Image processor type '${r}' not found, assuming base ImageProcessor. Please report this at ${Fu}.`),q),new i(n)}},wp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;constructor(e,t,n){super(e,t,n);let{tasks_answer_post_processing_type:r,task_prompts_without_inputs:i,task_prompts_with_input:a}=this.image_processor.config;this.tasks_answer_post_processing_type=new Map(Object.entries(r??{})),this.task_prompts_without_inputs=new Map(Object.entries(i??{})),this.task_prompts_with_input=new Map(Object.entries(a??{})),this.regexes={quad_boxes:/(.+?)<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm,bboxes:/([^<]+)?<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm},this.size_per_bin=1e3}construct_prompts(e){typeof e==`string`&&(e=[e]);let t=[];for(let n of e)if(this.task_prompts_without_inputs.has(n))t.push(this.task_prompts_without_inputs.get(n));else{for(let[e,r]of this.task_prompts_with_input)if(n.includes(e)){t.push(r.replaceAll(`{input}`,n).replaceAll(e,``));break}t.length!==e.length&&t.push(n)}return t}post_process_generation(e,t,n){let r=this.tasks_answer_post_processing_type.get(t)??`pure_text`;e=e.replaceAll(`<s>`,``).replaceAll(`</s>`,``);let i;switch(r){case`pure_text`:i=e;break;case`description_with_bboxes`:case`bboxes`:case`phrase_grounding`:case`ocr`:let a=r===`ocr`?`quad_boxes`:`bboxes`,o=e.matchAll(this.regexes[a]),s=[],c=[];for(let[e,t,...r]of o)s.push(t?t.trim():s.at(-1)??``),c.push(r.map((e,t)=>(Number(e)+.5)/this.size_per_bin*n[t%2]));i={labels:s,[a]:c};break;default:throw Error(`Task "${t}" (of type "${r}") not yet implemented.`)}return{[t]:i}}async _call(e,t=null,n={}){if(!e&&!t)throw Error(`Either text or images must be provided`);let r=await this.image_processor(e,n),i=t?this.tokenizer(this.construct_prompts(t),n):{};return{...r,...i}}},Tp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.image_seq_length=this.config.image_seq_length;let{boi_token:r,image_token:i,eoi_token:a}=this.tokenizer.config;this.boi_token=r,this.image_token=i,this.eoi_token=a;let o=i.repeat(this.image_seq_length);this.full_image_sequence=`

${r}${o}${a}

`}async _call(e,t=null,n={}){typeof e==`string`&&(e=[e]);let r;return t&&(r=await this.image_processor(t,n),e=e.map(e=>e.replaceAll(this.boi_token,this.full_image_sequence))),{...this.tokenizer(e,n),...r}}},Ep=class extends K{static image_processor_class=Cp;static feature_extractor_class=Md;static tokenizer_class=G;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.audio_seq_length=this.config.audio_seq_length,this.image_seq_length=this.config.image_seq_length;let{audio_token_id:r,boa_token:i,audio_token:a,eoa_token:o,image_token_id:s,boi_token:c,image_token:l,eoi_token:u}=this.tokenizer.config;this.audio_token_id=r,this.boa_token=i,this.audio_token=a;let d=a.repeat(this.audio_seq_length);this.full_audio_sequence=`

${i}${d}${o}

`,this.image_token_id=s,this.boi_token=c,this.image_token=l;let f=l.repeat(this.image_seq_length);this.full_image_sequence=`

${c}${f}${u}

`}async _call(e,t=null,n=null,r={}){typeof e==`string`&&(e=[e]);let i;n&&(i=await this.feature_extractor(n,r),e=e.map(e=>e.replaceAll(this.audio_token,this.full_audio_sequence)));let a;return t&&(a=await this.image_processor(t,r),e=e.map(e=>e.replaceAll(this.image_token,this.full_image_sequence))),{...this.tokenizer(e,r),...a,...i}}},Dp=class extends K{static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.audio_ms_per_token=this.config.audio_ms_per_token??40,this.audio_seq_length=this.config.audio_seq_length??750,this.image_seq_length=this.config.image_seq_length??280;let{audio_token:r,boa_token:i,eoa_token:a,image_token:o,boi_token:s,eoi_token:c}=this.tokenizer.config;this.audio_token=r,this.boa_token=i,this.eoa_token=a,this.image_token=o,this.boi_token=s,this.eoi_token=c}static async from_pretrained(e,t={}){let[n,r,i]=await Promise.all([rc(e,Ru,!0,t),G.from_pretrained(e,t),nc(e,zu,!1,t)]),a={tokenizer:r};return n.image_processor&&(a.image_processor=new Cf(n.image_processor)),n.feature_extractor&&(a.feature_extractor=new xd(n.feature_extractor)),new this(n,a,i)}_compute_audio_num_tokens(e,t){let n=Math.round(t*20/1e3),r=Math.round(t*10/1e3),i=Math.floor(n/2),a=Math.floor((e+i-n-1)/r)+1;if(a<=0)return 0;for(let e=0;e<2;++e)a=Math.floor((a-1)/2)+1;return Math.min(a,this.audio_seq_length)}async _call(e,t=null,n=null,r={}){typeof e==`string`&&(e=[e]);let i;if(t){i=await this.image_processor(t,r);let n=i.num_soft_tokens_per_image,a=0;e=e.map(e=>e.replaceAll(this.image_token,()=>`

${this.boi_token}${this.image_token.repeat(n[a++])}${this.eoi_token}

`))}let a;if(n){let t=Array.isArray(n)?n:[n];a=await this.feature_extractor(t[0],r);let i=this.feature_extractor.config.sampling_rate??16e3,o=0;e=e.map(e=>e.replaceAll(this.audio_token,()=>`

${this.boa_token}${this.audio_token.repeat(this._compute_audio_num_tokens(t[o++].length,i))}${this.eoa_token}

`))}return{...this.tokenizer(e,r),...i,...a}}},Op=class extends K{static image_processor_class=Cp;static tokenizer_class=G;static image_token=`<|image_pad|>`;async _call(e,t=null,...n){Array.isArray(e)||(e=[e]);let r,i;if(t&&(r=await this.image_processor(t),i=r.image_grid_thw),i){let t=this.image_processor.config.merge_size**2,n=0,r=this.constructor.image_token,a=i.tolist();e=e.map(e=>{for(;e.includes(r);){let i=Number(a[n++].reduce((e,t)=>e*t,1n));e=e.replace(r,`<|placeholder|>`.repeat(Math.floor(i/t)))}return e.replaceAll(`<|placeholder|>`,r)})}return{...this.tokenizer(e),...r}}},kp=class extends Op{static image_token=`<|image|>`},Ap=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;static uses_processor_config=!0;_get_num_audio_features(e){let{hop_length:t}=this.feature_extractor.config.melspec_kwargs,{projector_window_size:n,projector_downsample_rate:r}=this.feature_extractor.config,i=Math.floor(n/r),a=Math.floor(e/t)+1,o=Math.floor(a/2);return Math.ceil(o/n)*i}async _call(e,t=null,n={}){if(Array.isArray(e))throw Error(`Batched inputs are not supported yet.`);let r={};if(t){let{input_features:n}=await this.feature_extractor(t);r.input_features=n;let i=this._get_num_audio_features(t.length);r.input_features_mask=new U(`bool`,new Uint8Array(i).fill(1),[1,i]);let a=this.config.audio_token??`<|audio|>`;if(!e.includes(a))throw Error(`The input text does not contain the audio token ${a}.`);e=e.replaceAll(a,a.repeat(i))}return{...this.tokenizer(e,{add_special_tokens:!1,...n}),...r}}};function jp(e,t){let n=e.dims.at(-1)-1,r=e.tolist();r.fill(!1,0,1),r.fill(!1,n);let i=t.tolist();return r.map((e,t)=>e?t:null).filter(e=>e!==null).map(e=>i[e])}var Mp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;async _call(e,t,n={}){let r=e?await this.image_processor(e,n):{};return{...t?this.tokenizer(t,n):{},...r}}post_process_grounded_object_detection(e,t,{box_threshold:n=.25,text_threshold:r=.25,target_sizes:i=null}={}){let{logits:a,pred_boxes:o}=e,s=a.dims[0];if(i!==null&&i.length!==s)throw Error(`Make sure that you pass in as many target sizes as the batch dimension of the logits`);let c=a.dims.at(1),l=a.sigmoid(),u=l.max(-1).tolist(),d=o.tolist().map(e=>e.map(e=>Gd(e))),f=[];for(let e=0;e<s;++e){let a=i===null?null:i[e];a!==null&&(d[e]=d[e].map(e=>e.map((e,t)=>e*a[(t+1)%2])));let o=u[e],s=[],p=[],m=[];for(let i=0;i<c;++i){let a=o[i];if(a<=n)continue;let c=d[e][i],u=l[e][i];s.push(a),m.push(c);let f=jp(u.gt(r),t[e]);p.push(f)}f.push({scores:s,boxes:m,labels:this.batch_decode(p)})}return f}};function Np(e,t,n,r,i,a){let o=``;for(let a=0;a<t;++a){for(let t=0;t<n;++t)o+=r+`<row_${a+1}_col_${t+1}>`+i.repeat(e);o+=`
`}return o+=`
${r}${a}`+i.repeat(e)+`${r}`,o}function Pp(e,t,n,r){return`${t}${r}`+n.repeat(e)+`${t}`}function Fp(e,t,n,r,i,a){return e===0&&t===0?Pp(n,r,i,a):Np(n,e,t,r,i,a)}var Ip=class extends K{static image_processor_class=Cp;static tokenizer_class=G;static uses_processor_config=!0;fake_image_token=`<fake_token_around_image>`;image_token=`<image>`;global_img_token=`<global-img>`;async _call(e,t=null,n={}){n.return_row_col_info??=!0;let r;t&&(r=await this.image_processor(t,n)),Array.isArray(e)||(e=[e]);let i=r.rows??[Array(e.length).fill(0)],a=r.cols??[Array(e.length).fill(0)],o=this.config.image_seq_len,s=[],c=[];for(let t=0;t<e.length;++t){let n=e[t],r=i[t],l=a[t];s.push(fi(n,this.image_token));let u=r.map((e,t)=>Fp(e,l[t],o,this.fake_image_token,this.image_token,this.global_img_token)),d=n.split(this.image_token);if(d.length===0)throw Error(`The image token should be present in the text.`);let f=d[0];for(let e=0;e<u.length;++e)f+=u[e]+d[e+1];c.push(f)}return{...this.tokenizer(c),...r}}},Lp=class extends K{static image_processor_class=Cp;static tokenizer_class=G;static uses_processor_config=!0;constructor(e,t,n){super(e,t,n),this.image_tag=this.config.image_tag,this.image_start_tag=this.config.image_start_tag,this.image_end_tag=this.config.image_end_tag,this.num_image_tokens=this.config.num_image_tokens}async _call(e,{images:t=null,chat_template:n=`default`}={}){t?Array.isArray(t)||(t=[t]):t=await Promise.all(e.filter(e=>e.images).flatMap(e=>e.images).map(e=>Hd.read(e)));let r=this.tokenizer,i=r.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0,chat_template:n}),a=e=>r.encode(e,{add_special_tokens:!1}),o=i.split(this.image_tag),s=o.length-1;if(t.length!==s)throw Error(`Number of images provided (${t.length}) does not match number of "${this.image_tag}" image tags (${s})`);let[c,l,u]=r.convert_tokens_to_ids([this.image_tag,this.image_start_tag,this.image_end_tag]),d=a(o[0]),f=Array(d.length).fill(!1);for(let e=1;e<o.length;++e){let t=Array(this.num_image_tokens).fill(c),n=a(o[e]);d=ci(d,[l],t,[u],n);let r=Array(this.num_image_tokens).fill(!0);f=ci(f,[!1],r,[!1],Array(n.length).fill(!1))}let p=[1,d.length],m={input_ids:new U(`int64`,d,p),attention_mask:new U(`int64`,Array(d.length).fill(1),p),images_seq_mask:new U(`bool`,f,p),images_emb_mask:new U(`bool`,Array(s*this.num_image_tokens).fill(!0),[1,s,this.num_image_tokens])};if(t&&t.length>0){let e=await this.image_processor(t);return e.pixel_values.unsqueeze_(0),{...m,...e}}return m}},Rp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;async _call(e=null,t=null,n={}){if(!e&&!t)throw Error(`Either text or images must be provided`);let r=e?this.tokenizer(e,n):{},i=t?await this.image_processor(t,n):{};return{...r,...i}}},zp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;async _call(e,t=null,n={}){let{image_rows:r,image_cols:i,image_sizes:a,...o}=await this.image_processor(e,{...n,return_row_col_info:!0});if(t){let e=this.config.image_token??`<image>`,{tile_size:n=512,downsample_factor:o=2,encoder_patch_size:s=16,use_thumbnail:c=!0}=this.image_processor.config,l=e=>Math.ceil(Math.floor(e/s)/o),u=l(n)**2,d=this.config.image_start_token??`<|image_start|>`,f=this.config.image_end_token??`<|image_end|>`,p=this.config.image_thumbnail??`<|img_thumbnail|>`;Array.isArray(t)||(t=[t]);let m=0;t=t.map(t=>{let n=t.split(e);return n[0]+n.slice(1).map(t=>{let n=m++,[o,s]=a[n],h=r[n],g=i[n],_=l(o)*l(s),v=d;if(h>1||g>1){let t=e.repeat(u);for(let e=0;e<h;++e)for(let n=0;n<g;++n)v+=`<|img_row_${e+1}_col_${n+1}|>`+t;c&&(v+=p+e.repeat(_))}else v+=e.repeat(_);return v+f+t}).join(``)})}return{...o,...t?this.tokenizer(t,n):{}}}},Bp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;static uses_processor_config=!0;async _call(e,t=null,n={}){let r=await this.image_processor(e,n);if(t){let[e,n]=r.pixel_values.dims.slice(-2),{image_token:i,patch_size:a,num_additional_image_tokens:o}=this.config,s=Math.floor(e/a)*Math.floor(n/a)+o;t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let e=0;e<t.length;++e)t[e]=t[e].replace(i,i.repeat(s))}let i=t?this.tokenizer(t,n):{};return{...r,...i}}},Vp={char:[`char_decode`,1],bpe:[`bpe_decode`,2],wp:[`wp_decode`,102]},Hp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;get char_tokenizer(){return this.components.char_tokenizer}get bpe_tokenizer(){return this.components.bpe_tokenizer}get wp_tokenizer(){return this.components.wp_tokenizer}_decode_helper(e,t){if(!Vp.hasOwnProperty(t))throw Error(`Format ${t} is not supported.`);let[n,r]=Vp[t],i=this[n].bind(this),[a,o]=e.dims,s=[],c=[],l=e.tolist();for(let e=0;e<a;++e){let t=l[e],n=[],i=[];for(let e=1;e<o;++e){let[a,o]=lc(oc(t[e]));if(i.push(a),o==r)break;n.push(o)}let a=i.length>0?i.reduce((e,t)=>e*t,1):0;c.push(n),s.push(a)}return[i(c),s]}char_decode(e){return this.char_tokenizer.batch_decode(e).map(e=>e.replaceAll(` `,``))}bpe_decode(e){return this.bpe_tokenizer.batch_decode(e)}wp_decode(e){return this.wp_tokenizer.batch_decode(e).map(e=>e.replaceAll(` `,``))}batch_decode([e,t,n]){let[r,i]=this._decode_helper(e,`char`),[a,o]=this._decode_helper(t,`bpe`),[s,c]=this._decode_helper(n,`wp`),l=[],u=[];for(let e=0;e<r.length;++e){let[t,n]=lc([i[e],o[e],c[e]]);l.push([r[e],a[e],s[e]][n]),u.push(t)}return{generated_text:l,scores:u,char_preds:r,bpe_preds:a,wp_preds:s}}static async from_pretrained(...e){let t=await super.from_pretrained(...e),n=await G.from_pretrained(`Xenova/gpt2`),r=await G.from_pretrained(`Xenova/bert-base-uncased`);return t.components={image_processor:t.image_processor,char_tokenizer:t.tokenizer,bpe_tokenizer:n,wp_tokenizer:r},t}async _call(e,t=null){let n=await this.image_processor(e);return t&&(n.labels=this.tokenizer(t).input_ids),n}},Up=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e){return await this.feature_extractor(e)}},Wp=class extends K{static tokenizer_class=G;static image_processor_class=Cp},Gp=`<image>`;function Kp(e,t,n,r,i){return`${r.repeat(n*i)}${t}${e}
`}var qp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;static uses_processor_config=!1;async _call(e,t=null,n={}){t||=(N.warn(`You are using PaliGemma without a text prefix. It will perform as a picture-captioning model.`),``),Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);let r=this.tokenizer.bos_token,i=this.image_processor.config.image_seq_length,a;t.some(e=>e.includes(Gp))?a=t.map(e=>{let t=e.replaceAll(Gp,Gp.repeat(i)),n=t.lastIndexOf(Gp),a=n===-1?0:n+Gp.length;return t.slice(0,a)+r+t.slice(a)+`
`}):(N.warn("You are passing both `text` and `images` to `PaliGemmaProcessor`. The processor expects special image tokens in the text, as many tokens as there are images per each text. It is recommended to add `<image>` tokens in the very beginning of your text. For this call, we will infer how many images each text has and add special tokens."),a=t.map(t=>Kp(t,r,i,Gp,e.length)));let o=this.tokenizer(a,n);return{...await this.image_processor(e,n),...o}}},Jp=`<|image|>`,Yp=/<\|image_\d+\|>/g,Xp=class extends K{static image_processor_class=Cp;static tokenizer_class=G;async _call(e,t=null,{padding:n=!0,truncation:r=!0,num_crops:i=null}={}){Array.isArray(e)||(e=[e]);let a,o;if(t){o=await this.image_processor(t,{num_crops:i});let{num_img_tokens:s}=o,c=e.map((e,t)=>e.split(Yp).join(Jp.repeat(s[t])));a=this.tokenizer(c,{padding:n,truncation:r});let l=this.tokenizer._tokenizer.token_to_id(Jp);a.input_ids.map_(e=>e==l?-e:e)}else a=this.tokenizer(e);return{...a,...o}}},Zp=class extends K{static tokenizer_class=G;static image_processor_class=Cp;static uses_processor_config=!0;async _call(e,t=null,n={}){let r=await this.image_processor(e,n);if(t){let[e,n]=r.pixel_values.dims.slice(-2),{image_token:i,image_break_token:a,image_end_token:o,patch_size:s,spatial_merge_size:c}=this.config,l=s*c,u=Math.floor(e/l),d=Math.floor(n/l);t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let e=0;e<t.length;++e){let n=i.repeat(d),r=n+a,s=n+o,c=r.repeat(u-1)+s;t[e]=t[e].replace(i,c)}}let i=t?this.tokenizer(t,n):{};return{...r,...i}}},Qp=class extends K{static feature_extractor_class=wd;async _call(e){return await this.feature_extractor(e)}post_process_speaker_diarization(...e){return this.feature_extractor.post_process_speaker_diarization(...e)}get sampling_rate(){return this.feature_extractor.config.sampling_rate}},$p=class extends Op{},em=class extends $p{},tm=class extends K{static image_processor_class=Cp;async _call(...e){return await this.image_processor(...e)}post_process_masks(...e){return this.image_processor.post_process_masks(...e)}reshape_input_points(...e){return this.image_processor.reshape_input_points(...e)}},nm=class extends tm{},rm=class extends nm{},im=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e){return await this.feature_extractor(e)}},am=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;static uses_processor_config=!0;async _call(e,t=null,n={}){if(Array.isArray(e))throw Error(`Batched inputs are not supported yet.`);let r={};if(t){let i=t.length,{input_features:a}=await this.feature_extractor(t,{...n,max_length:i}),o=Math.round(i/this.config.encoder_ds_factor+1e-4),s=1+Math.ceil(o/this.config.stack_factor);r.audio_token_len=[s],r.audio_values=a;let c=this.config.audio_placeholder;if(!e.includes(c))throw Error(`The input text does not contain the image token ${c}.`);e=e.replaceAll(c,c.repeat(s))}return{...this.tokenizer(e,{add_special_tokens:!1,...n}),...r}}},om=`[AUDIO]`,sm=`[BEGIN_AUDIO]`,cm=375;function lm(e,t){let n=[];for(let r=0;r<e.length;r+=t)n.push(e.subarray(r,Math.min(r+t,e.length)));return n}var um=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;static uses_processor_config=!1;async _call(e,t=null,n={}){if(Array.isArray(e))throw Error(`Batched inputs are not supported yet.`);let r={};if(t){if(!e.includes(om))throw Error(`The input text does not contain the audio token ${om}.`);Array.isArray(t)||(t=[t]);let i=e.split(om),a=i.length-1;if(a!==t.length)throw Error(`The number of audio inputs (${t.length}) does not match the number of audio tokens in the text (${a}).`);let o=this.feature_extractor.config.n_samples,s=t.map(e=>lm(e,o)),c=s.map(e=>e.length),l=s.flat(),u=(await Promise.all(l.map(e=>this.feature_extractor(e,n)))).map(e=>e.input_features);r.audio_values=u.length>1?fl(u,0):u[0];let d=i[0];for(let e=0;e<c.length;++e){d+=sm;for(let t=0;t<c[e];++t)d+=om.repeat(cm);d+=i[e+1]}e=d}return{...this.tokenizer(e,{add_special_tokens:!1,...n}),...r}}},dm=32,fm=6,pm=8,mm=10,hm=32,gm=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;static uses_processor_config=!1;get num_mel_frames_first_audio_chunk(){return(fm+1)*pm}get num_samples_first_audio_chunk(){let{hop_length:e,n_fft:t}=this.feature_extractor.config;return(this.num_mel_frames_first_audio_chunk-1)*e+Math.floor(t/2)}get num_samples_per_audio_chunk(){let{hop_length:e,n_fft:t}=this.feature_extractor.config;return pm*e+t}get num_right_pad_tokens(){return fm+1+mm}get audio_length_per_tok(){return pm}get raw_audio_length_per_tok(){return pm*this.feature_extractor.config.hop_length}async _call(e,{is_streaming:t=!1,is_first_audio_chunk:n=!0}={}){if(Vu(e,`VoxtralRealtimeProcessor`),!t&&!n)throw Error("In non-streaming mode (`is_streaming=false`), `is_first_audio_chunk` must be `true`.");if(n)if(t){let t=dm*this.raw_audio_length_per_tok,n=new Float32Array(t+e.length);n.set(e,t);let r=await this.feature_extractor(n,{center:!0}),i=1+(dm+fm),a=new BigInt64Array(i).fill(BigInt(hm));return a[0]=1n,{input_ids:new U(`int64`,a,[1,i]),...r}}else{let t=this.num_right_pad_tokens*this.raw_audio_length_per_tok,n=new Float32Array(e.length+t);return n.set(e),await this.feature_extractor(n,{center:!0})}else return await this.feature_extractor(e,{center:!1})}},_m=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e){return await this.feature_extractor(e)}},vm=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e){return await this.feature_extractor(e)}},ym=class extends K{static tokenizer_class=G;static feature_extractor_class=Md;async _call(e){return await this.feature_extractor(e)}};async function bm(e,t){return await rc(e,`config.json`,!0,t)}function xm(e){let t={},n={};switch(e.model_type){case`llava`:case`paligemma`:case`gemma3`:case`florence2`:case`llava_onevision`:case`idefics3`:case`granite_speech`:case`ultravox`:case`voxtral`:case`voxtral_realtime`:case`smolvlm`:case`gemma3n`:case`gemma4`:case`lfm2_vl`:case`chatterbox`:case`lighton_ocr`:case`glm_ocr`:case`mistral3`:case`qwen2_5_vl`:case`qwen3_vl`:case`qwen3_vl_moe`:n=xm(e.text_config);break;case`moondream1`:n=xm(e.phi_config);break;case`musicgen`:n=xm(e.decoder);break;case`multi_modality`:n=xm(e.language_config);break;case`gpt2`:case`gptj`:case`jais`:case`codegen`:case`gpt_bigcode`:t.num_heads=`n_head`,t.num_layers=`n_layer`,t.hidden_size=`n_embd`;break;case`gpt_neox`:case`stablelm`:case`opt`:case`falcon`:case`modernbert-decoder`:t.num_heads=`num_attention_heads`,t.num_layers=`num_hidden_layers`,t.hidden_size=`hidden_size`;break;case`gpt_oss`:case`llama`:case`llama4_text`:case`nanochat`:case`apertus`:case`arcee`:case`afmoe`:case`lfm2`:case`lfm2_moe`:case`smollm3`:case`olmo`:case`olmo2`:case`olmo3`:case`mobilellm`:case`granite`:case`granitemoehybrid`:case`cohere`:case`cohere2`:case`mistral`:case`voxtral_realtime_text`:case`voxtral_realtime_encoder`:case`starcoder2`:case`qwen2`:case`qwen2_moe`:case`qwen2_vl`:case`qwen2_vl_text`:case`qwen2_5_vl_text`:case`qwen3_moe`:case`qwen3_vl_text`:case`qwen3_vl_moe_text`:case`phi`:case`phi3`:case`phi3_v`:case`llava_qwen2`:t.num_heads=`num_key_value_heads`,t.num_layers=`num_hidden_layers`,t.hidden_size=`hidden_size`,t.num_attention_heads=`num_attention_heads`,t.dim_kv=`head_dim`;break;case`qwen3`:case`solar_open`:case`glm_ocr_text`:case`gemma`:case`gemma2`:case`vaultgemma`:case`gemma3_text`:case`gemma3n_text`:case`gemma4_text`:case`glm`:case`helium`:case`ernie4_5`:case`hunyuan_v1_dense`:case`falcon_h1`:case`nemotron_h`:case`ministral`:case`ministral3`:t.num_heads=`num_key_value_heads`,t.num_layers=`num_hidden_layers`,t.dim_kv=`head_dim`;break;case`openelm`:t.num_heads=`num_kv_heads`,t.num_layers=`num_transformer_layers`,t.dim_kv=`head_dim`;break;case`gpt_neo`:case`donut-swin`:t.num_heads=`num_heads`,t.num_layers=`num_layers`,t.hidden_size=`hidden_size`;break;case`bloom`:t.num_heads=`n_head`,t.num_layers=`n_layer`,t.hidden_size=`hidden_size`;break;case`mpt`:t.num_heads=`n_heads`,t.num_layers=`n_layers`,t.hidden_size=`d_model`;break;case`exaone`:t.num_heads=`num_key_value_heads`,t.num_layers=`num_layers`,t.dim_kv=`head_dim`,t.num_attention_heads=`num_attention_heads`;break;case`youtu`:case`deepseek_v3`:case`glm_moe_dsa`:case`mistral4`:t.num_heads=`num_key_value_heads`,t.num_layers=`num_hidden_layers`,t.dim_kv=`qk_head_dim`,t.num_attention_heads=`num_attention_heads`;break;case`t5`:case`mt5`:case`longt5`:t.num_decoder_layers=`num_decoder_layers`,t.num_decoder_heads=`num_heads`,t.decoder_dim_kv=`d_kv`,t.num_encoder_layers=`num_layers`,t.num_encoder_heads=`num_heads`,t.encoder_dim_kv=`d_kv`;break;case`bart`:case`mbart`:case`marian`:case`whisper`:case`lite-whisper`:case`m2m_100`:case`blenderbot`:case`blenderbot-small`:case`florence2_language`:t.num_decoder_layers=`decoder_layers`,t.num_decoder_heads=`decoder_attention_heads`,t.decoder_hidden_size=`d_model`,t.num_encoder_layers=`encoder_layers`,t.num_encoder_heads=`encoder_attention_heads`,t.encoder_hidden_size=`d_model`;break;case`speecht5`:t.num_decoder_layers=`decoder_layers`,t.num_decoder_heads=`decoder_attention_heads`,t.decoder_hidden_size=`hidden_size`,t.num_encoder_layers=`encoder_layers`,t.num_encoder_heads=`encoder_attention_heads`,t.encoder_hidden_size=`hidden_size`;break;case`trocr`:t.num_encoder_layers=t.num_decoder_layers=`decoder_layers`,t.num_encoder_heads=t.num_decoder_heads=`decoder_attention_heads`,t.encoder_hidden_size=t.decoder_hidden_size=`d_model`;break;case`musicgen_decoder`:t.num_encoder_layers=t.num_decoder_layers=`num_hidden_layers`,t.num_encoder_heads=t.num_decoder_heads=`num_attention_heads`,t.encoder_hidden_size=t.decoder_hidden_size=`hidden_size`;break;case`moonshine`:t.num_decoder_layers=`decoder_num_hidden_layers`,t.num_decoder_heads=`decoder_num_key_value_heads`,t.num_encoder_layers=`encoder_num_hidden_layers`,t.num_encoder_heads=`encoder_num_key_value_heads`,t.encoder_hidden_size=t.decoder_hidden_size=`hidden_size`;break;case`cohere_asr`:t.num_decoder_layers=`num_hidden_layers`,t.num_decoder_heads=`num_key_value_heads`,t.decoder_hidden_size=`hidden_size`,t.decoder_dim_kv=`head_dim`;let{num_hidden_layers:r,num_attention_heads:i,hidden_size:a}=e.encoder_config;n={num_encoder_layers:r,num_encoder_heads:i,encoder_hidden_size:a,encoder_dim_kv:e.head_dim};break;case`vision-encoder-decoder`:let o=xm(e.decoder),s=`num_decoder_layers`in o,c=di(e,[`model_type`,`is_encoder_decoder`]);return s?(c.num_decoder_layers=o.num_decoder_layers,c.num_decoder_heads=o.num_decoder_heads,c.decoder_hidden_size=o.decoder_hidden_size,c.num_encoder_layers=o.num_encoder_layers,c.num_encoder_heads=o.num_encoder_heads,c.encoder_hidden_size=o.encoder_hidden_size):(c.num_layers=o.num_layers,c.num_heads=o.num_heads,c.hidden_size=o.hidden_size),c}let r={...n,...di(e,[`model_type`,`multi_query`,`is_encoder_decoder`])};for(let n in t)r[n]=e[t[n]];return r}function Sm(e,t){e instanceof wm||(e=new wm(e));let n=t?.prefix??`past_key_values`,r=n===`present`?`present`:`past`,i=new Set;if([`lfm2`,`lfm2_moe`].includes(e.model_type)){let{layer_types:t}=e;for(let e=0;e<t.length;++e)if(t[e]===`full_attention`)i.add(`${n}.${e}.key`),i.add(`${n}.${e}.value`);else if(t[e]===`conv`)i.add(`${r}_conv.${e}`);else throw Error(`Unsupported layer type: ${t[e]}`);return i}else if([`granitemoehybrid`,`falcon_h1`,`nemotron_h`].includes(e.model_type)){let t=e,a=t.layer_types??t.layers_block_type,o=t.num_hidden_layers??a?.length;for(let e=0;e<o;++e)(!a||a[e]===`mamba`)&&(i.add(`${r}_conv.${e}`),i.add(`${r}_ssm.${e}`)),(!a||a[e]===`attention`)&&(i.add(`${n}.${e}.key`),i.add(`${n}.${e}.value`));return i}else if([`qwen3_next`,`qwen3_5_text`,`qwen3_5_moe_text`,`olmo_hybrid`].includes(e.model_type)){let{layer_types:t}=e;for(let a=0;a<t.length;++a)if(t[a]===`full_attention`)i.add(`${n}.${a}.key`),i.add(`${n}.${a}.value`);else if(t[a]===`linear_attention`)e.model_type===`olmo_hybrid`?(i.add(`${r}_conv.${a}.key`),i.add(`${r}_conv.${a}.value`),i.add(`${r}_conv.${a}.query`)):i.add(`${r}_conv.${a}`),i.add(`${r}_recurrent.${a}`);else throw Error(`Unsupported layer type: ${t[a]}`);return i}else if([`gemma4`,`gemma4_text`].includes(e.model_type)){let t=e.model_type===`gemma4`?e.text_config:e,r=t.num_hidden_layers-(t.num_kv_shared_layers??0);for(let 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n||(r.audio_encoder=`audio_encoder`,r.vision_encoder=`vision_encoder`),r},optional_configs:{generation_config:`generation_config.json`}},[X.Phi3V]:{sessions:()=>({prepare_inputs_embeds:`prepare_inputs_embeds`,model:`model`,vision_encoder:`vision_encoder`}),cache_sessions:{model:!0},optional_configs:{generation_config:`generation_config.json`}},[X.MultiModality]:{sessions:()=>({prepare_inputs_embeds:`prepare_inputs_embeds`,model:`language_model`,lm_head:`lm_head`,gen_head:`gen_head`,gen_img_embeds:`gen_img_embeds`,image_decode:`image_decode`}),cache_sessions:{model:!0},optional_configs:{generation_config:`generation_config.json`}},[X.AutoEncoder]:{sessions:()=>({encoder_model:`encoder_model`,decoder_model:`decoder_model`})},[X.Supertonic]:{sessions:()=>({text_encoder:`text_encoder`,latent_denoiser:`latent_denoiser`,voice_decoder:`voice_decoder`})},[X.Chatterbox]:{sessions:()=>({embed_tokens:`embed_tokens`,speech_encoder:`speech_encoder`,model:`language_model`,conditional_decoder:`conditional_decoder`}),cache_sessions:{model:!0},optional_configs:{generation_config:`generation_config.json`}},[X.VoxtralRealtime]:{text_only_sessions:{embed_tokens:`embed_tokens`,decoder_model_merged:`decoder_model_merged`},sessions:(e,t,n)=>{let r={...dh[X.VoxtralRealtime].text_only_sessions};return n||(r.audio_encoder=`audio_encoder`),r},cache_sessions:{decoder_model_merged:!0,audio_encoder:!0},optional_configs:{generation_config:`generation_config.json`}},default:{sessions:(e,t)=>({model:t.model_file_name??`model`})}};function fh(e){return dh[e]?.text_only_sessions??null}function ph(e,t,n={}){let r=dh[e]??dh.default;return{sessions:r.sessions(t,n,n.textOnly??!1),cache_sessions:r.cache_sessions,optional_configs:r.optional_configs}}function mh(e,{warn:t=!0}={}){let n=e.architectures||[];for(let e of n){let t=Ch.get(e);if(t!==void 0)return t}if(e.model_type){let t=Ch.get(e.model_type);if(t!==void 0)return t;for(let t of Object.values(_h))if(t.has(e.model_type)){let n=Ch.get(t.get(e.model_type));if(n!==void 0)return n}}if(t){let t=n.length>0?n.join(`, `):`(none)`;N.warn(`[resolve_model_type] Architecture(s) not found in MODEL_TYPE_MAPPING: [${t}] for model type '${e.model_type}'. Falling back to EncoderOnly (single model.onnx file). 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Please report this at ${Fu}.`)}if(t&&!(t instanceof ii)){let r={};try{let t=await gh(e,{config:n,dtype:l,device:c,model_file_name:o});(await Promise.all(t.map(t=>Ks(e,t,f)))).forEach((e,n)=>{if(e.exists){let i=t[n]===`config.json`;r[t[n]]={loaded:i?e.size??0:0,total:e.size??0}}})}catch(e){N.warn(`Unable to fetch model file metadata for total progress tracking: ${e}`)}Object.keys(r).length>0&&(f.progress_callback=new ii(t,r))}let _=[jm(e,m.sessions(n,f,h),f,m.cache_sessions)];m.optional_configs&&_.push(Gh(e,m.optional_configs,f));let v=await Promise.all(_);return new this(n,...v)}async _call(e){return await this.forward(e)}async forward(e){return await this._forward(this,e)}get generation_config(){return this.configs?.generation_config??null}_get_logits_processor(e,t,n=null){let r=new Hm;if(e.repetition_penalty!==null&&e.repetition_penalty!==1&&r.push(new Ym(e.repetition_penalty)),e.no_repeat_ngram_size!==null&&e.no_repeat_ngram_size>0&&r.push(new Jm(e.no_repeat_ngram_size)),e.bad_words_ids!==null&&r.push(new Qm(e.bad_words_ids,e.eos_token_id)),e.min_length!==null&&e.eos_token_id!==null&&e.min_length>0&&r.push(new Xm(e.min_length,e.eos_token_id)),e.min_new_tokens!==null&&e.eos_token_id!==null&&e.min_new_tokens>0&&r.push(new Zm(t,e.min_new_tokens,e.eos_token_id)),e.forced_bos_token_id!==null&&r.push(new Um(e.forced_bos_token_id)),e.forced_eos_token_id!==null&&r.push(new Wm(e.max_length,e.forced_eos_token_id)),e.suppress_tokens!==null&&r.push(new Gm(e.suppress_tokens)),e.begin_suppress_tokens!==null){let n=t>1||e.forced_bos_token_id===null?t:t+1;r.push(new Km(e.begin_suppress_tokens,n))}return e.guidance_scale!==null&&e.guidance_scale>1&&r.push(new $m(e.guidance_scale)),e.temperature===0&&e.do_sample&&(N.warn("`do_sample` changed to false because `temperature: 0` implies greedy sampling (always selecting the most likely token), which is incompatible with `do_sample: true`."),e.do_sample=!1),e.do_sample&&e.temperature!==null&&e.temperature!==1&&r.push(new eh(e.temperature)),n!==null&&r.extend(n),r}_prepare_generation_config(e,t,n=th){let r={...this.config};for(let e of[`decoder`,`generator`,`text_config`])e in r&&Object.assign(r,r[e]);let i=new n(r);return Object.assign(i,this.generation_config??{}),e&&Object.assign(i,e),t&&Object.assign(i,di(t,Object.getOwnPropertyNames(i))),i}_get_stopping_criteria(e,t=null){let n=new rh;return e.max_length!==null&&n.push(new ih(e.max_length,this.config.max_position_embeddings??null)),e.eos_token_id!==null&&n.push(new ah(e.eos_token_id)),t&&n.extend(t),n}_validate_model_class(){if(!this.can_generate){let e=[_h.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,_h.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,_h.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,_h.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES].filter(Boolean),t=Th.get(this.constructor),n=new Set,r=this.config.model_type;for(let t of e){let e=t?.get(r);e&&n.add(e)}let i=`The current model class (${t}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw n.size>0&&(i+=` Please use the following class instead: ${[...n].join(`, `)}`),Error(i)}}prepare_inputs_for_generation(...e){if(!this._prepare_inputs_for_generation)throw Error(`prepare_inputs_for_generation is not implemented for this model.`);return this._prepare_inputs_for_generation(this,...e)}_update_model_kwargs_for_generation({generated_input_ids:e,outputs:t,model_inputs:n,is_encoder_decoder:r}){return n.past_key_values=kh(t,n.past_key_values),n.input_ids=new U(`int64`,e.flat(),[e.length,1]),r?`decoder_attention_mask`in n&&(n.decoder_attention_mask=fl([n.decoder_attention_mask,xl([n.decoder_attention_mask.dims[0],1])],1)):n.attention_mask=fl([n.attention_mask,xl([n.attention_mask.dims[0],1])],1),n.position_ids=null,n}_prepare_model_inputs({inputs:e,bos_token_id:t,model_kwargs:n}){let r=di(n,this.forward_params),i=this.main_input_name;if(i in r){if(e)throw Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else r[i]=e;return{inputs_tensor:r[i],model_inputs:r,model_input_name:i}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:e,model_inputs:t,model_input_name:n,generation_config:r}){if(this.sessions.model.inputNames.includes(`inputs_embeds`)&&!t.inputs_embeds&&`_prepare_inputs_embeds`in this){let{input_ids:e,pixel_values:n,attention_mask:r,...i}=t,a=await this._prepare_inputs_embeds(t);t={...i,...di(a,[`inputs_embeds`,`attention_mask`])}}let{last_hidden_state:i}=await Dh(this,t);if(r.guidance_scale!==null&&r.guidance_scale>1)i=fl([i,bl(i,0)],0),`attention_mask`in t&&(t.attention_mask=fl([t.attention_mask,wl(t.attention_mask)],0));else if(t.decoder_input_ids){let e=yh(t.decoder_input_ids).dims[0];if(e!==i.dims[0]){if(i.dims[0]!==1)throw Error(`The encoder outputs have a different batch size (${i.dims[0]}) than the decoder inputs (${e}).`);i=fl(Array.from({length:e},()=>i),0)}}return t.encoder_outputs=i,t}_prepare_decoder_input_ids_for_generation({batch_size:e,model_input_name:t,model_kwargs:n,decoder_start_token_id:r,bos_token_id:i,generation_config:a}){let{decoder_input_ids:o,...s}=n;if(!(o instanceof U)){if(o)Array.isArray(o[0])||(o=Array.from({length:e},()=>o));else if(r??=i,this.config.model_type===`musicgen`)o=Array.from({length:e*this.config.decoder.num_codebooks},()=>[r]);else if(Array.isArray(r)){if(r.length!==e)throw Error(`\`decoder_start_token_id\` expcted to have length ${e} but got ${r.length}`);o=r}else o=Array.from({length:e},()=>[r]);o=yh(o)}return s.decoder_attention_mask=Sl(o),{input_ids:o,model_inputs:s}}async generate({inputs:e=null,generation_config:t=null,logits_processor:n=null,stopping_criteria:r=null,streamer:i=null,...a}){this._validate_model_class(),t=this._prepare_generation_config(t,a);let{inputs_tensor:o,model_inputs:s,model_input_name:c}=this._prepare_model_inputs({inputs:e,model_kwargs:a}),l=this.config.is_encoder_decoder;l&&(`encoder_outputs`in s||(s=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:o,model_inputs:s,model_input_name:c,generation_config:t})));let u;l?{input_ids:u,model_inputs:s}=this._prepare_decoder_input_ids_for_generation({batch_size:s[c].dims.at(0),model_input_name:c,model_kwargs:s,decoder_start_token_id:t.decoder_start_token_id,bos_token_id:t.bos_token_id,generation_config:t}):u=s[c];let d=u.dims.at(-1);t.max_new_tokens!==null&&(t.max_length=d+t.max_new_tokens);let f=this._get_logits_processor(t,d,n),p=this._get_stopping_criteria(t,r),m=s[c].dims.at(0),h=oh.getSampler(t),g=Array(m).fill(0),_=u.tolist();i&&i.put(_);let v,y={},b={};for(;;){if(s=this.prepare_inputs_for_generation(_,s,t),v=await this.forward(s),t.return_dict_in_generate)if(t.output_attentions){let e=Ah(v);for(let t in e)t in y||(y[t]=[]),y[t].push(e[t])}else this._return_dict_in_generate_keys&&Object.assign(b,di(v,this._return_dict_in_generate_keys));let e=f(_,v.logits.slice(null,-1,null).to(`float32`)),n=[];for(let t=0;t<e.dims.at(0);++t){let r=e[t],i=await h(r);for(let[e,r]of i){let i=BigInt(e);g[t]+=r,_[t].push(i),n.push([i]);break}}if(i&&i.put(n),p(_).every(e=>e))break;s=this._update_model_kwargs_for_generation({generated_input_ids:n,outputs:v,model_inputs:s,is_encoder_decoder:l})}i&&i.end();let x=new U(`int64`,_.flat(),[_.length,_[0].length]),ee=kh(v,s.past_key_values),S=new Set(Object.values(ee));for(let e of Object.values(v))e.location===`gpu-buffer`&&!S.has(e)&&e.dispose();return`past_key_values`in a||t.return_dict_in_generate||await ee.dispose(),t.return_dict_in_generate?{sequences:x,past_key_values:ee,...y,...b}:x}async _encode_input(e,t,n){if(!Object.hasOwn(this.sessions,e))throw Error(`Model does not have a ${e} session.`);let r=this.sessions[e];return(await J(r,di(t,r.inputNames)))[n]}async encode_image(e){return this._encode_input(`vision_encoder`,e,`image_features`)}async encode_text(e){return this._encode_input(`embed_tokens`,e,`inputs_embeds`)}async encode_audio(e){return this._encode_input(`audio_encoder`,e,`audio_features`)}};async function Eh(e,t){let{encoder_outputs:n,input_ids:r,decoder_input_ids:i,decoder_attention_mask:a,...o}=t;return n||=(await Dh(e,di(t,e.sessions.model.inputNames))).last_hidden_state,o.input_ids=i,o.encoder_hidden_states=n,e.sessions.decoder_model_merged.inputNames.includes(`encoder_attention_mask`)&&(o.encoder_attention_mask=t.attention_mask),a&&!o.attention_mask&&(o.attention_mask=a),await Nh(e,o,!0)}async function Dh(e,t){let n=e.sessions.model,r=di(t,n.inputNames);if(n.inputNames.includes(`inputs_embeds`)&&!r.inputs_embeds){if(!t.input_ids)throw Error("Both `input_ids` and `inputs_embeds` are missing in the model inputs.");r.inputs_embeds=await e.encode_text({input_ids:t.input_ids})}if(n.inputNames.includes(`token_type_ids`)&&!r.token_type_ids){if(!r.input_ids)throw Error("Both `input_ids` and `token_type_ids` are missing in the model inputs.");r.token_type_ids=wl(r.input_ids)}if(n.inputNames.includes(`pixel_mask`)&&!r.pixel_mask){if(!r.pixel_values)throw Error("Both `pixel_values` and `pixel_mask` are missing in the model inputs.");let e=r.pixel_values.dims;r.pixel_mask=xl([e[0],e[2],e[3]])}return await J(n,r)}async function Oh(e,t){let n=await e.encode(t);return await e.decode(n)}function kh(e,t){let n=Object.create(null);for(let r in e)if(r.startsWith(`present`)){let i=r.replace(`present_ssm`,`past_ssm`).replace(`present_conv`,`past_conv`).replace(`present_recurrent`,`past_recurrent`).replace(`present`,`past_key_values`);r.includes(`encoder`)&&t?n[i]=t[i]:n[i]=e[r]}return t?(t.update(n),t):new uh(n)}function Ah(e){let t={};for(let n 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Z{forward_params=[`input_ids`,`inputs_embeds`,`attention_mask`,`position_ids`,`audio_values`,`exaggeration`,`audio_features`,`audio_tokens`,`speaker_embeddings`,`speaker_features`,`past_key_values`];main_input_name=`input_ids`;_return_dict_in_generate_keys=[`audio_tokens`,`speaker_embeddings`,`speaker_features`]},Vg=class extends Bg{async encode_speech(e){return J(this.sessions.speech_encoder,{audio_values:e})}async forward({input_ids:e=null,attention_mask:t=null,audio_values:n=null,exaggeration:r=null,position_ids:i=null,inputs_embeds:a=null,past_key_values:o=null,generation_config:s=null,logits_processor:c=null,audio_features:l=null,audio_tokens:u=null,speaker_embeddings:d=null,speaker_features:f=null,...p}){let m;if(!a){let s=this.sessions.embed_tokens.inputNames,c={input_ids:e};if(s.includes(`exaggeration`)){if(!(r instanceof U)){let t=e.dims[0];if(r==null)r=yl([t],.5);else if(typeof r==`number`)r=yl([t],r);else if(Array.isArray(r))r=new U(`float32`,r,[t]);else throw Error("Unsupported type for `exaggeration` input")}c.exaggeration=r}if(s.includes(`position_ids`)&&(c.position_ids=i),{inputs_embeds:a}=await J(this.sessions.embed_tokens,c),l&&u&&d&&f&&(m={audio_features:l,audio_tokens:u,speaker_embeddings:d,speaker_features:f}),m||n)m??=await this.encode_speech(n),a=fl([m.audio_features,a],1),t=xl([a.dims[0],a.dims[1]]);else{let e=a.dims[1];if(!o||e!==1)throw Error(`Incorrect state encountered during generation.`);let n=o.get_seq_length();t=xl([a.dims[0],n+e])}}return{...await Nh(this,{inputs_embeds:a,past_key_values:o,attention_mask:t,generation_config:s,logits_processor:c},!1),...m}}prepare_inputs_for_generation(e,t,n){return!t.position_ids&&this.sessions.embed_tokens.inputNames.includes(`position_ids`)&&(t.input_ids.dims[1]===1?t.position_ids=new U(`int64`,Array.from({length:e.length},(t,n)=>e[n].length-e[n].findLastIndex(e=>e==zg)-1),[e.length,1]):t.position_ids=new U(`int64`,t.input_ids.tolist().map(e=>{let t=0;return 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xy{},Cy=class extends xy{},wy=class extends Z{},Ty=class extends wy{},Ey=class extends wy{},Dy=class extends Z{forward_params=[`input_ids`,`attention_mask`,`pixel_values`,`position_ids`,`past_key_values`]},Oy=class extends Dy{_merge_input_ids_with_image_features(e){let t=e.image_features.dims.at(-1),n=e.image_features.view(-1,t);return Uh({image_token_id:this.config.image_token_index??this.config.image_token_id,...e,image_features:n})}},ky=class extends Oy{},Ay=class extends Oy{},jy=class extends Z{},My=class extends jy{},Ny=class extends Oy{},Py=class extends Ny{},Fy=class extends Z{forward_params=[`input_ids`,`attention_mask`,`inputs_embeds`,`per_layer_inputs`,`position_ids`,`pixel_values`,`input_features`,`input_features_mask`,`past_key_values`]},Iy=class extends Fy{async forward({input_ids:e=null,attention_mask:t=null,pixel_values:n=null,input_features:r=null,input_features_mask:i=null,position_ids:a=null,inputs_embeds:o=null,per_layer_inputs:s=null,past_key_values:c=null,generation_config:l=null,logits_processor:u=null,...d}){if((!o||!s)&&({inputs_embeds:o,per_layer_inputs:s}=await J(this.sessions.embed_tokens,{input_ids:e}),e.dims[1]!==1)){if(n){let{image_features:r}=await this._encode_vision({pixel_values:n,...d});({inputs_embeds:o,attention_mask:t}=this._merge_input_ids_with_image_features({image_features:r,inputs_embeds:o,input_ids:e,attention_mask:t}))}if(r){let{audio_features:n}=await J(this.sessions.audio_encoder,{input_features:r,input_features_mask:i});({inputs_embeds:o,attention_mask:t}=this._merge_input_ids_with_audio_features({audio_features:n,inputs_embeds:o,input_ids:e,attention_mask:t}))}}return await Nh(this,{inputs_embeds:o,per_layer_inputs:s,past_key_values:c,attention_mask:t,position_ids:a,generation_config:l,logits_processor:u},!0)}_encode_vision(e){return J(this.sessions.vision_encoder,{pixel_values:e.pixel_values})}_merge_input_ids_with_image_features(e){let t=e.image_features.dims.at(-1),n=e.image_features.view(-1,t);return Uh({image_token_id:this.config.image_token_id,...e,image_features:n})}_merge_input_ids_with_audio_features(e){let t=e.audio_features.dims.at(-1),n=e.audio_features.view(-1,t);return Wh({audio_token_id:this.config.audio_token_id,...e,audio_features:n})}},Ly=class extends Iy{},Ry=class extends Iy{forward_params=[`input_ids`,`attention_mask`,`inputs_embeds`,`per_layer_inputs`,`position_ids`,`pixel_values`,`image_position_ids`,`input_features`,`input_features_mask`,`past_key_values`];_encode_vision(e){return J(this.sessions.vision_encoder,{pixel_values:e.pixel_values,pixel_position_ids:e.image_position_ids})}},zy=class extends Ry{},By=class extends Z{},Vy=class extends By{},Hy=class extends By{},Uy=class extends Z{},Wy=class extends Uy{},Gy=class extends Uy{},Ky=class extends Z{forward_params=[`input_ids`,`attention_mask`,`position_ids`,`past_key_values`,`pixel_values`,`image_grid_thw`]},qy=class extends Ky{image_grid_thw_name=`grid_thw`;_get_text_only_rope_index(e,t){if(t){let{data:e,dims:n}=Lh(t),r=BigInt64Array.from({length:3*e.length},(t,n)=>e[n%e.length]),i=Array.from({length:n[0]},(t,r)=>lc(e.subarray(n[1]*r,n[1]*(r+1)))[0]+1n+BigInt(n[1]));return[new U(`int64`,r,[3,...n]),new U(`int64`,i,[i.length,1])]}else{let[t,n]=e.dims;return[new U(`int64`,BigInt64Array.from({length:3*t*n},(e,r)=>BigInt(Math.floor(r%n/t))),[3,...e.dims]),Cl([t,1])]}}_reorder_and_write_positions(e,t,n,r){let i=e.reduce((e,t)=>e+t.length,0),a=Array(i),o=0;for(let t=0;t<3;++t)for(let n of e){let e=n.length/3;for(let r=t*e;r<(t+1)*e;++r)a[o++]=n[r]}let s=0;for(let e=0;e<t.length;++e)if(t[e]==1){for(let t=0;t<3;++t)n[t][r][e]=a[t*i/3+s];++s}return a}_get_multimodal_rope_positions({filtered_ids:e,image_grid_thw_list:t,video_grid_thw_list:n,spatial_merge_size:r,state:i}){let{image_token_id:a,video_token_id:o,vision_start_token_id:s}=this.config,c=e,l=c.reduce((e,t,n)=>(t==s&&e.push(n),e),[]).map(e=>c[e+1]),u=l.filter(e=>e==a).length,d=l.filter(e=>e==o).length,f=[],p=0,m=u,h=d;for(let e=0;e<l.length;++e){let e=c.findIndex((e,t)=>t>p&&e==a),s=c.findIndex((e,t)=>t>p&&e==o),l=m>0&&e!==-1?e:c.length+1,u=h>0&&s!==-1?s:c.length+1,d,g,_,v;l<u?([g,_,v]=t[i.image_index],++i.image_index,--m,d=l):([g,_,v]=n[i.video_index],++i.video_index,--h,d=u);let[y,b,x]=[Number(g),Math.floor(Number(_)/r),Math.floor(Number(v)/r)],ee=d-p,S=f.length>0?lc(f.at(-1))[0]+1:0;f.push(Array.from({length:3*ee},(e,t)=>S+t%ee));let te=ee+S,C=y*b*x,w=Array.from({length:C},(e,t)=>te+Math.floor(t/(b*x))),ne=Array.from({length:C},(e,t)=>te+Math.floor(t/x)%b),re=Array.from({length:C},(e,t)=>te+t%x);f.push([w,ne,re].flat()),p=d+C}if(p<c.length){let 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J(this.sessions.decoder_model,e)}},FT=class extends NT{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`encoder_model`})}},IT=class extends NT{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`decoder_model`})}},LT=class extends Z{},RT=class extends LT{},zT=class extends LT{},BT=class extends Z{},VT=class extends BT{},HT=class extends BT{},UT=class extends BT{async generate_speech(e,t,{threshold:n=.5,minlenratio:r=0,maxlenratio:i=20,vocoder:a=null}={}){let o={input_ids:e},{encoder_outputs:s,encoder_attention_mask:c}=await Dh(this,o),l=s.dims[1]/this.config.reduction_factor,u=Math.floor(l*i),d=Math.floor(l*r),f=this.config.num_mel_bins,p=[],m=null,h=null,g=0;for(;;){++g;let e=bh(!!h),r;r=h?h.output_sequence_out:new U(`float32`,new Float32Array(f),[1,1,f]);let i={use_cache_branch:e,output_sequence:r,encoder_attention_mask:c,speaker_embeddings:t,encoder_hidden_states:s};Mh(this,i,m),h=await J(this.sessions.decoder_model_merged,i),m=kh(h,m);let{prob:a,spectrum:o}=h;if(p.push(o),g>=d&&(Array.from(a.data).filter(e=>e>=n).length>0||g>=u))break}let _=fl(p),{waveform:v}=await J(a.sessions.model,{spectrogram:_});return{spectrogram:_,waveform:v}}},WT=class extends Z{main_input_name=`spectrogram`},GT=class extends Z{},KT=class extends GT{},qT=class extends GT{async _call(e){return new Im(await super._call(e))}},JT=class extends GT{async _call(e){return new Y(await super._call(e))}},YT=class extends GT{async _call(e){return new Lm(await super._call(e))}},XT=class extends Z{},ZT=class extends XT{},QT=class extends XT{},$T=class extends Z{},eE=class extends $T{},tE=class extends $T{},nE=class extends Z{},rE=class extends nE{},iE=class extends Z{},aE=class extends iE{async generate_speech({input_ids:e,attention_mask:t,style:n,num_inference_steps:r=5,speed:i=1.05}){let{sampling_rate:a,chunk_compress_factor:o,base_chunk_size:s,latent_dim:c}=this.config,{last_hidden_state:l,durations:u}=await J(this.sessions.text_encoder,{input_ids:e,attention_mask:t,style:n}),d=u.div(i).mul_(a),f=s*o,p=d.data,m=Int32Array.from(p,e=>Math.ceil(e/f)),h=Math.max(...m),g=e.dims[0],_=new BigInt64Array(g*h);for(let e=0;e<g;++e)_.fill(1n,e*h,e*h+m[e]);let v=new U(`int64`,_,[g,h]),y=c*o,b=y*h,x=Tl([g,y,h]),ee=x.data;for(let e=0;e<g;++e)if(m[e]!==h)for(let t=0;t<y;++t)ee.fill(0,e*b+t*h+m[e],e*b+(t+1)*h);let S=yl([g],r);for(let e=0;e<r;++e){let r=yl([g],e);({denoised_latents:x}=await J(this.sessions.latent_denoiser,{style:n,noisy_latents:x,latent_mask:v,encoder_outputs:l,attention_mask:t,timestep:r,num_inference_steps:S}))}let{waveform:te}=await J(this.sessions.voice_decoder,{latents:x});return{waveform:te,durations:d}}},oE=class extends Z{},sE=class extends oE{},cE=class extends oE{async _call(e){return new Y(await super._call(e))}},lE=class extends oE{},uE=class extends Z{},dE=class extends uE{},fE=class extends uE{},pE=class extends Z{forward_params=[`input_ids`,`attention_mask`,`encoder_outputs`,`decoder_input_ids`,`decoder_attention_mask`,`past_key_values`]},mE=class extends pE{},hE=class extends pE{},gE=class extends Z{},_E=class extends gE{},vE=class extends gE{async _call(e){return new yE(await super._call(e))}},yE=class extends gv{},bE=class extends Z{},xE=class extends bE{},SE=class extends Z{},CE=class extends SE{},wE=class extends SE{async _call(e){return new Rm(await super._call(e))}},TE=class extends SE{async _call(e){return new Y(await super._call(e))}},EE=class extends Z{},DE=class extends EE{},OE=class extends EE{async _call(e){return new Rm(await super._call(e))}},kE=class extends EE{async _call(e){return new Y(await super._call(e))}},AE=class extends EE{async _call(e){return new Fm(await super._call(e))}},jE=class extends Z{},ME=class extends jE{},NE=class extends jE{},PE=class extends Z{main_input_name=`pixel_values`;forward_params=[`pixel_values`,`decoder_input_ids`,`encoder_hidden_states`,`past_key_values`]},FE=class extends Z{},IE=class extends FE{},LE=class extends FE{async _call(e){return new Y(await super._call(e))}},RE=class extends Z{},zE=class extends RE{},BE=class extends Z{},VE=class extends BE{},HE=class extends BE{async _call(e){return new Y(await super._call(e))}},UE=class extends Z{},WE=class extends UE{async _call(e){return new zm(await super._call(e))}},GE=class extends Z{},KE=class extends GE{},qE=class extends Pm{constructor({waveform:e,spectrogram:t}){super(),this.waveform=e,this.spectrogram=t}},JE=class extends Z{},YE=class extends JE{async _call(e){return new qE(await super._call(e))}},XE=class extends Eb{},ZE=2,QE=1,$E=new WeakMap;function eD(e,t){let{text_config:n,audio_config:r}=e.config,i=e.sessions.audio_encoder,{num_mel_bins:a,hidden_size:o}=r,s=a+o,c=new uh,l=Sm(r),u={batch_size:1},d=`float32`;for(let e of i.inputMetadata){if(e.name===`past_padding_cache`){d=e.type;continue}if(!l.has(e.name))continue;let t=jh(e.shape,u),n=t.reduce((e,t)=>e*t,1),r=$c[e.type];c[e.name]=new U(e.type,new r(n),t)}let f=$c[d],p=new U(d,new f(s*ZE),[1,s,ZE]),m=t[Symbol.asyncIterator]?.()??t[Symbol.iterator]?.();if(!m)throw Error(`input_features must be iterable or async iterable`);return{encoder_session:i,enc_kv_cache:c,enc_padding_cache:p,enc_past_seq_len:0,audio_embed_queue:[],audio_embed_total_tokens:0,audio_queue_offset:0,audio_consumed:0,stream_exhausted:!1,chunks_iter:m,text_hidden_size:n.hidden_size}}async function tD(e,t){let n=t.dims[2],r=Math.floor((QE+n-3)/2)+1,i=new U(`int64`,BigInt64Array.from({length:r},(t,n)=>BigInt(e.enc_past_seq_len+n)),[1,r]),a=e.enc_past_seq_len+r,o=xl([1,a]),{audio_embeds:s,present_padding_cache:c,...l}=await J(e.encoder_session,{input_features:t,attention_mask:o,position_ids:i,past_padding_cache:e.enc_padding_cache,...e.enc_kv_cache});e.enc_padding_cache.location===`gpu-buffer`&&e.enc_padding_cache.dispose(),e.enc_padding_cache=c;for(let t in l)if(t.startsWith(`present.`)){let n=t.replace(`present`,`past_key_values`),r=e.enc_kv_cache[n];r?.location===`gpu-buffer`&&r.dispose(),e.enc_kv_cache[n]=l[t]}return e.enc_past_seq_len=a,s}async function nD(e,t){for(;e.audio_embed_total_tokens<t&&!e.stream_exhausted;){let t=await e.chunks_iter.next();if(t.done){e.stream_exhausted=!0;break}let n=await tD(e,t.value);e.audio_embed_queue.push({data:n.data,tokens:n.dims[1]}),e.audio_embed_total_tokens+=n.dims[1]}}function rD(e,t,n){if(e.audio_embed_queue.length===0)return;let r=t.data,i=0,a=n;for(;a>0&&e.audio_embed_queue.length>0;){let t=e.audio_embed_queue[0],n=t.tokens-e.audio_queue_offset,o=Math.min(a,n),s=e.audio_queue_offset*e.text_hidden_size;for(let n=0;n<o*e.text_hidden_size;++n)r[i*e.text_hidden_size+n]+=t.data[s+n];i+=o,a-=o,e.audio_queue_offset+=o,e.audio_queue_offset>=t.tokens&&(e.audio_embed_queue.shift(),e.audio_queue_offset=0)}e.audio_consumed+=n-a}var iD=class extends nh{constructor(e){super(),this._s=e}_call(e){let t=this._s.stream_exhausted&&this._s.audio_embed_queue.length===0;return e.map(()=>t)}},aD=class extends Z{forward_params=[`input_ids`,`attention_mask`,`position_ids`,`past_key_values`]},oD=class extends aD{async forward({input_ids:e,past_key_values:t,...n}){let r=e.dims[1],i=$E.get(this);i&&await nD(i,i.audio_consumed+r);let{inputs_embeds:a}=await J(this.sessions.embed_tokens,{input_ids:e});i&&rD(i,a,r);let o={inputs_embeds:a,...n};Mh(this,o,t);let s=this.sessions.decoder_model_merged;return await J(s,di(o,s.inputNames))}async generate({input_features:e,stopping_criteria:t,...n}){if(!e)throw Error(`input_features (generator/iterable) must be provided`);let r=eD(this,e);$E.set(this,r);let i=new rh;i.push(new iD(r)),t&&i.extend(t);try{return await super.generate({...n,stopping_criteria:i})}finally{r.enc_kv_cache.dispose(),$E.delete(this)}}},sD=class extends Z{},cD=class extends sD{},lD=class extends sD{async _call(e){return new Rm(await super._call(e))}},uD=class extends sD{async _call(e){return new Y(await super._call(e))}},dD=class extends Pm{constructor({logits:e,embeddings:t}){super(),this.logits=e,this.embeddings=t}},fD=class extends Z{},pD=class extends fD{},mD=class extends fD{async _call(e){return new Rm(await super._call(e))}},hD=class extends fD{async _call(e){return new Y(await super._call(e))}},gD=class extends fD{async _call(e){return new dD(await super._call(e))}},_D=class extends fD{async _call(e){return new Fm(await super._call(e))}},vD=class extends Z{},yD=class extends vD{},bD=class extends th{return_timestamps=null;return_token_timestamps=null;num_frames=null;alignment_heads=null;task=null;language=null;no_timestamps_token_id=null;prompt_ids=null;is_multilingual=null;lang_to_id=null;task_to_id=null;max_initial_timestamp_index=1},xD=class extends Z{requires_attention_mask=!1;main_input_name=`input_features`;forward_params=[`input_features`,`attention_mask`,`decoder_input_ids`,`decoder_attention_mask`,`past_key_values`]},SD=class extends xD{},CD=class extends xD{_prepare_generation_config(e,t){return super._prepare_generation_config(e,t,bD)}_retrieve_init_tokens(e){let t=[e.decoder_start_token_id],n=e.language,r=e.task;if(e.is_multilingual){n||=(N.warn(`No language specified - defaulting to English (en).`),`en`);let i=`<|${ku(n)}|>`;t.push(e.lang_to_id[i]),t.push(e.task_to_id[r??`transcribe`])}else if(n||r)throw Error("Cannot specify `task` or `language` for an English-only model. If the model is intended to be multilingual, pass `is_multilingual=true` to generate, or update the generation config.");return!e.return_timestamps&&e.no_timestamps_token_id&&t.at(-1)!==e.no_timestamps_token_id?t.push(e.no_timestamps_token_id):e.return_timestamps&&t.at(-1)===e.no_timestamps_token_id&&(N.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),t.pop()),t.filter(e=>e!=null)}async generate({inputs:e=null,generation_config:t=null,logits_processor:n=null,stopping_criteria:r=null,...i}){t=this._prepare_generation_config(t,i);let a=i.decoder_input_ids instanceof U?kl(i.decoder_input_ids):i.decoder_input_ids??this._retrieve_init_tokens(t);if(t.return_timestamps&&(n??=new Hm,n.push(new qm(t,a))),t.begin_suppress_tokens&&(n??=new Hm,n.push(new Km(t.begin_suppress_tokens,a.length))),t.return_token_timestamps){if(!t.alignment_heads)throw Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");t.task===`translate`&&N.warn(`Token-level timestamps may not be reliable for task 'translate'.`),t.output_attentions=!0,t.return_dict_in_generate=!0}if(t.return_timestamps&&!i.max_new_tokens)return this._generate_with_seek({inputs:e,generation_config:t,logits_processor:n,init_tokens:a,kwargs:i});let o=await super.generate({inputs:e,generation_config:t,logits_processor:n,decoder_input_ids:a,...i});return t.return_token_timestamps&&(o.token_timestamps=this._extract_token_timestamps(o,t.alignment_heads,t.num_frames,.02,a.length)),o}async _generate_with_seek({inputs:e,generation_config:t,logits_processor:n,init_tokens:r,kwargs:i}){let a=t.no_timestamps_token_id+1,o=Array.isArray(t.eos_token_id)?t.eos_token_id[0]:t.eos_token_id,s=t.return_token_timestamps,c=e,l=c.dims[2],u=2*this.config.max_source_positions,d=0,f=[],p=[];for(;d<l;){let e=Math.min(d+u,l),m=c.slice(null,null,[d,e]),h,g=m.dims[2];if(g<u){let e=c.dims[1],t=new Float32Array(e*u),n=m.data;for(let r=0;r<e;++r)t.set(n.subarray(r*g,(r+1)*g),r*u);h=new U(`float32`,t,[1,e,u])}else h=m;if(n)for(let e of n)`begin_index`in e&&(e.begin_index=r.length);let _=await super.generate({inputs:h,generation_config:t,logits_processor:n,decoder_input_ids:r,...i}),v=(s?_.sequences:_)[0].tolist().map(Number).slice(r.length),y;if(s){_.token_timestamps=this._extract_token_timestamps(_,t.alignment_heads,Math.floor((e-d)/2),.02,r.length);let n=d/2*.02;y=_.token_timestamps[0].tolist().slice(r.length).map(e=>e+n)}if(v.length>0&&v.at(-1)===o&&v.pop(),v.length===0)break;let b=v.map(e=>e>=a),x=v.length>=2&&b[v.length-1]&&!b[v.length-2],ee=[];for(let e=0;e<v.length-1;++e)b[e]&&b[e+1]&&ee.push(e+1);let S,te=v.length;if(ee.length>0)if(x)S=e-d;else{let e=ee.at(-1);S=(v[e-1]-a)*2,te=e}else S=e-d;let C=Math.floor(d/2),w=a+1500;for(let e=0;e<te;++e)v[e]>=a&&(v[e]=Math.min(v[e]+C,w));f.push(...v.slice(0,te)),y&&p.push(...y.slice(0,te)),d+=S}f.push(o);let m=[...r,...f];if(s){let e=new U(`int64`,m.map(BigInt),[1,m.length]),t=[...Array(r.length).fill(0),...p,0];return{sequences:e,token_timestamps:new U(`float32`,new Float32Array(t),[1,t.length])}}return new U(`int64`,m.map(BigInt),[1,m.length])}_extract_token_timestamps(e,t,n=null,r=.02,i=0){if(!e.cross_attentions)throw Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");n??N.warn("`num_frames` has not been set, meaning the entire audio will be analyzed. This may lead to inaccurate token-level timestamps for short audios (< 30 seconds).");let a=this.config.median_filter_width;a===void 0&&(N.warn("Model config has no `median_filter_width`, using default value of 7."),a=7);let o=e.cross_attentions,s=Array.from({length:this.config.decoder_layers},(e,t)=>fl(o.map(e=>e[t]),2)),c=pl(t.map(([e,t])=>{if(e>=s.length)throw Error(`Layer index ${e} is out of bounds for cross attentions (length ${s.length}).`);return n?s[e].slice(null,t,null,[0,n]):s[e].slice(null,t)})).transpose(1,0,2,3),[l,u]=hl(c,-2,0,!0),d=c.clone();for(let e=0;e<d.dims[0];++e){let t=d[e];for(let n=0;n<t.dims[0];++n){let r=t[n],i=l[e][n][0].data,o=u[e][n][0].data;for(let e=0;e<r.dims[0];++e){let t=r[e].data;for(let e=0;e<t.length;++e)t[e]=(t[e]-o[e])/i[e];t.set(mc(t,a))}}}let f=[gl(i>0?d.slice(null,null,[i,d.dims[2]],null):d,1)],p=e.sequences.dims,m=new U(`float32`,new Float32Array(p[0]*p[1]),p);for(let e=0;e<p[0];++e){let[t,n]=_c(f[e].neg().squeeze_(0).tolist()),a=ci([1],Array.from({length:t.length-1},(e,n)=>t[n+1]-t[n])).map(e=>!!e),o=[];for(let e=0;e<a.length;++e)a[e]&&o.push(n[e]*r);let s=Array(i).fill(0);s.push(...o),o.length>0&&s.push(o.at(-1)),m[e].data.set(s)}return m}},wD=class extends CD{},TD=class extends Z{},ED=class extends TD{},DD=class extends TD{async _call(e){return new Im(await super._call(e))}},OD=class extends TD{async _call(e){return new Y(await super._call(e))}},kD=class extends TD{async _call(e){return new Fm(await super._call(e))}},AD=class extends TD{async _call(e){return new Lm(await super._call(e))}},jD=class extends Z{},MD=class extends jD{},ND=class extends jD{async _call(e){return new Im(await super._call(e))}},PD=class extends jD{async _call(e){return new Y(await super._call(e))}},FD=class extends jD{async _call(e){return new Fm(await super._call(e))}},ID=class extends jD{async _call(e){return new Lm(await super._call(e))}},LD=class extends Z{},RD=class extends LD{},zD=class extends LD{async _call(e){return new BD(await super._call(e))}},BD=class extends Pm{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},VD=class extends Z{},HD=class extends VD{},UD=class extends VD{},WD=new Map([[`bert`,`BertModel`],[`eurobert`,`EuroBertModel`],[`neobert`,`NeoBertModel`],[`modernbert`,`ModernBertModel`],[`nomic_bert`,`NomicBertModel`],[`roformer`,`RoFormerModel`],[`electra`,`ElectraModel`],[`esm`,`EsmModel`],[`convbert`,`ConvBertModel`],[`camembert`,`CamembertModel`],[`deberta`,`DebertaModel`],[`deberta-v2`,`DebertaV2Model`],[`mpnet`,`MPNetModel`],[`albert`,`AlbertModel`],[`distilbert`,`DistilBertModel`],[`roberta`,`RobertaModel`],[`xlm`,`XLMModel`],[`xlm-roberta`,`XLMRobertaModel`],[`clap`,`ClapModel`],[`clip`,`CLIPModel`],[`clipseg`,`CLIPSegModel`],[`chinese_clip`,`ChineseCLIPModel`],[`siglip`,`SiglipModel`],[`jina_clip`,`JinaCLIPModel`],[`mobilebert`,`MobileBertModel`],[`squeezebert`,`SqueezeBertModel`],[`wav2vec2`,`Wav2Vec2Model`],[`wav2vec2-bert`,`Wav2Vec2BertModel`],[`unispeech`,`UniSpeechModel`],[`unispeech-sat`,`UniSpeechSatModel`],[`hubert`,`HubertModel`],[`wavlm`,`WavLMModel`],[`audio-spectrogram-transformer`,`ASTModel`],[`vits`,`VitsModel`],[`pyannote`,`PyAnnoteModel`],[`wespeaker-resnet`,`WeSpeakerResNetModel`],[`detr`,`DetrModel`],[`rt_detr`,`RTDetrModel`],[`rt_detr_v2`,`RTDetrV2Model`],[`rf_detr`,`RFDetrModel`],[`d_fine`,`DFineModel`],[`table-transformer`,`TableTransformerModel`],[`vit`,`ViTModel`],[`ijepa`,`IJepaModel`],[`pvt`,`PvtModel`],[`vit_msn`,`ViTMSNModel`],[`vit_mae`,`ViTMAEModel`],[`groupvit`,`GroupViTModel`],[`fastvit`,`FastViTModel`],[`mobilevit`,`MobileViTModel`],[`mobilevitv2`,`MobileViTV2Model`],[`owlvit`,`OwlViTModel`],[`owlv2`,`Owlv2Model`],[`beit`,`BeitModel`],[`deit`,`DeiTModel`],[`hiera`,`HieraModel`],[`convnext`,`ConvNextModel`],[`convnextv2`,`ConvNextV2Model`],[`dinov2`,`Dinov2Model`],[`dinov2_with_registers`,`Dinov2WithRegistersModel`],[`dinov3_vit`,`DINOv3ViTModel`],[`dinov3_convnext`,`DINOv3ConvNextModel`],[`resnet`,`ResNetModel`],[`swin`,`SwinModel`],[`swin2sr`,`Swin2SRModel`],[`donut-swin`,`DonutSwinModel`],[`yolos`,`YolosModel`],[`dpt`,`DPTModel`],[`glpn`,`GLPNModel`],[`hifigan`,`SpeechT5HifiGan`],[`efficientnet`,`EfficientNetModel`],[`decision_transformer`,`DecisionTransformerModel`],[`patchtst`,`PatchTSTModel`],[`patchtsmixer`,`PatchTSMixerModel`],[`mobilenet_v1`,`MobileNetV1Model`],[`mobilenet_v2`,`MobileNetV2Model`],[`mobilenet_v3`,`MobileNetV3Model`],[`mobilenet_v4`,`MobileNetV4Model`],[`maskformer`,`MaskFormerModel`],[`mgp-str`,`MgpstrForSceneTextRecognition`],[`style_text_to_speech_2`,`StyleTextToSpeech2Model`],[`openai_privacy_filter`,`OpenAIPrivacyFilterModel`]]),GD=new Map([[`t5`,`T5Model`],[`longt5`,`LongT5Model`],[`mt5`,`MT5Model`],[`bart`,`BartModel`],[`mbart`,`MBartModel`],[`marian`,`MarianModel`],[`whisper`,`WhisperModel`],[`cohere_asr`,`CohereAsrModel`],[`m2m_100`,`M2M100Model`],[`blenderbot`,`BlenderbotModel`],[`blenderbot-small`,`BlenderbotSmallModel`]]),KD=new Map([[`mimi`,`MimiModel`],[`dac`,`DacModel`],[`snac`,`SnacModel`]]),qD=new Map([[`bloom`,`BloomModel`],[`jais`,`JAISModel`],[`gpt2`,`GPT2Model`],[`gpt_oss`,`GptOssModel`],[`gptj`,`GPTJModel`],[`gpt_bigcode`,`GPTBigCodeModel`],[`gpt_neo`,`GPTNeoModel`],[`gpt_neox`,`GPTNeoXModel`],[`codegen`,`CodeGenModel`],[`llama`,`LlamaModel`],[`apertus`,`ApertusModel`],[`nanochat`,`NanoChatModel`],[`arcee`,`ArceeModel`],[`afmoe`,`AfmoeModel`],[`lfm2`,`Lfm2Model`],[`lfm2_moe`,`Lfm2MoeModel`],[`smollm3`,`SmolLM3Model`],[`exaone`,`ExaoneModel`],[`olmo`,`OlmoModel`],[`olmo2`,`Olmo2Model`],[`olmo3`,`Olmo3Model`],[`olmo_hybrid`,`OlmoHybridModel`],[`mobilellm`,`MobileLLMModel`],[`granite`,`GraniteModel`],[`granitemoehybrid`,`GraniteMoeHybridModel`],[`cohere`,`CohereModel`],[`cohere2`,`Cohere2Model`],[`gemma`,`GemmaModel`],[`gemma2`,`Gemma2Model`],[`vaultgemma`,`VaultGemmaModel`],[`gemma3_text`,`Gemma3Model`],[`helium`,`HeliumModel`],[`glm`,`GlmModel`],[`glm_moe_dsa`,`GlmMoeDsaModel`],[`openelm`,`OpenELMModel`],[`qwen2`,`Qwen2Model`],[`qwen2_moe`,`Qwen2MoeModel`],[`qwen3`,`Qwen3Model`],[`qwen3_moe`,`Qwen3MoeModel`],[`qwen3_next`,`Qwen3NextModel`],[`phi`,`PhiModel`],[`phi3`,`Phi3Model`],[`mpt`,`MptModel`],[`opt`,`OPTModel`],[`mistral`,`MistralModel`],[`mistral4`,`Mistral4Model`],[`ministral`,`MinistralModel`],[`ministral3`,`Ministral3Model`],[`ernie4_5`,`Ernie4_5ForCausalLM`],[`starcoder2`,`Starcoder2Model`],[`deepseek_v3`,`DeepseekV3Model`],[`falcon`,`FalconModel`],[`falcon_h1`,`FalconH1Model`],[`nemotron_h`,`NemotronHModel`],[`solar_open`,`SolarOpenModel`],[`stablelm`,`StableLmModel`],[`modernbert-decoder`,`ModernBertDecoderModel`],[`hunyuan_v1_dense`,`HunYuanDenseV1Model`],[`youtu`,`YoutuModel`]]),JD=new Map([[`speecht5`,`SpeechT5ForSpeechToText`],[`whisper`,`WhisperForConditionalGeneration`],[`lite-whisper`,`LiteWhisperForConditionalGeneration`],[`moonshine`,`MoonshineForConditionalGeneration`],[`cohere_asr`,`CohereAsrForConditionalGeneration`]]),YD=new Map([[`speecht5`,`SpeechT5ForTextToSpeech`]]),XD=new Map([[`vits`,`VitsModel`],[`musicgen`,`MusicgenForConditionalGeneration`],[`supertonic`,`SupertonicForConditionalGeneration`]]),ZD=new Map([[`bert`,`BertForSequenceClassification`],[`eurobert`,`EuroBertForSequenceClassification`],[`neobert`,`NeoBertForSequenceClassification`],[`modernbert`,`ModernBertForSequenceClassification`],[`roformer`,`RoFormerForSequenceClassification`],[`electra`,`ElectraForSequenceClassification`],[`esm`,`EsmForSequenceClassification`],[`convbert`,`ConvBertForSequenceClassification`],[`camembert`,`CamembertForSequenceClassification`],[`deberta`,`DebertaForSequenceClassification`],[`deberta-v2`,`DebertaV2ForSequenceClassification`],[`mpnet`,`MPNetForSequenceClassification`],[`albert`,`AlbertForSequenceClassification`],[`distilbert`,`DistilBertForSequenceClassification`],[`roberta`,`RobertaForSequenceClassification`],[`xlm`,`XLMForSequenceClassification`],[`xlm-roberta`,`XLMRobertaForSequenceClassification`],[`bart`,`BartForSequenceClassification`],[`mbart`,`MBartForSequenceClassification`],[`mobilebert`,`MobileBertForSequenceClassification`],[`squeezebert`,`SqueezeBertForSequenceClassification`]]),QD=new Map([[`bert`,`BertForTokenClassification`],[`eurobert`,`EuroBertForTokenClassification`],[`neobert`,`NeoBertForTokenClassification`],[`modernbert`,`ModernBertForTokenClassification`],[`roformer`,`RoFormerForTokenClassification`],[`electra`,`ElectraForTokenClassification`],[`esm`,`EsmForTokenClassification`],[`convbert`,`ConvBertForTokenClassification`],[`camembert`,`CamembertForTokenClassification`],[`deberta`,`DebertaForTokenClassification`],[`deberta-v2`,`DebertaV2ForTokenClassification`],[`mpnet`,`MPNetForTokenClassification`],[`distilbert`,`DistilBertForTokenClassification`],[`roberta`,`RobertaForTokenClassification`],[`xlm`,`XLMForTokenClassification`],[`xlm-roberta`,`XLMRobertaForTokenClassification`],[`openai_privacy_filter`,`OpenAIPrivacyFilterForTokenClassification`]]),$D=new Map([[`t5`,`T5ForConditionalGeneration`],[`longt5`,`LongT5ForConditionalGeneration`],[`mt5`,`MT5ForConditionalGeneration`],[`bart`,`BartForConditionalGeneration`],[`mbart`,`MBartForConditionalGeneration`],[`marian`,`MarianMTModel`],[`m2m_100`,`M2M100ForConditionalGeneration`],[`blenderbot`,`BlenderbotForConditionalGeneration`],[`blenderbot-small`,`BlenderbotSmallForConditionalGeneration`]]),eO=new Map([[`bloom`,`BloomForCausalLM`],[`gpt2`,`GPT2LMHeadModel`],[`gpt_oss`,`GptOssForCausalLM`],[`jais`,`JAISLMHeadModel`],[`gptj`,`GPTJForCausalLM`],[`gpt_bigcode`,`GPTBigCodeForCausalLM`],[`gpt_neo`,`GPTNeoForCausalLM`],[`gpt_neox`,`GPTNeoXForCausalLM`],[`codegen`,`CodeGenForCausalLM`],[`llama`,`LlamaForCausalLM`],[`nanochat`,`NanoChatForCausalLM`],[`apertus`,`ApertusForCausalLM`],[`llama4_text`,`Llama4ForCausalLM`],[`arcee`,`ArceeForCausalLM`],[`afmoe`,`AfmoeForCausalLM`],[`lfm2`,`Lfm2ForCausalLM`],[`lfm2_moe`,`Lfm2MoeForCausalLM`],[`smollm3`,`SmolLM3ForCausalLM`],[`exaone`,`ExaoneForCausalLM`],[`olmo`,`OlmoForCausalLM`],[`olmo2`,`Olmo2ForCausalLM`],[`olmo3`,`Olmo3ForCausalLM`],[`olmo_hybrid`,`OlmoHybridForCausalLM`],[`mobilellm`,`MobileLLMForCausalLM`],[`granite`,`GraniteForCausalLM`],[`granitemoehybrid`,`GraniteMoeHybridForCausalLM`],[`cohere`,`CohereForCausalLM`],[`cohere2`,`Cohere2ForCausalLM`],[`gemma`,`GemmaForCausalLM`],[`gemma2`,`Gemma2ForCausalLM`],[`vaultgemma`,`VaultGemmaForCausalLM`],[`gemma3_text`,`Gemma3ForCausalLM`],[`gemma3`,`Gemma3ForCausalLM`],[`helium`,`HeliumForCausalLM`],[`glm`,`GlmForCausalLM`],[`glm_moe_dsa`,`GlmMoeDsaForCausalLM`],[`openelm`,`OpenELMForCausalLM`],[`qwen2`,`Qwen2ForCausalLM`],[`qwen2_moe`,`Qwen2MoeForCausalLM`],[`qwen3`,`Qwen3ForCausalLM`],[`qwen3_moe`,`Qwen3MoeForCausalLM`],[`qwen3_next`,`Qwen3NextForCausalLM`],[`qwen2_vl`,`Qwen2VLForCausalLM`],[`qwen2_5_vl`,`Qwen2_5_VLForCausalLM`],[`qwen3_vl`,`Qwen3VLForCausalLM`],[`qwen3_vl_moe`,`Qwen3VLMoeForCausalLM`],[`qwen3_5`,`Qwen3_5ForCausalLM`],[`qwen3_5_text`,`Qwen3_5ForCausalLM`],[`qwen3_5_moe`,`Qwen3_5MoeForCausalLM`],[`gemma3n`,`Gemma3nForCausalLM`],[`gemma4`,`Gemma4ForCausalLM`],[`phi`,`PhiForCausalLM`],[`phi3`,`Phi3ForCausalLM`],[`mpt`,`MptForCausalLM`],[`opt`,`OPTForCausalLM`],[`mbart`,`MBartForCausalLM`],[`mistral`,`MistralForCausalLM`],[`mistral4`,`Mistral4ForCausalLM`],[`ministral`,`MinistralForCausalLM`],[`ministral3`,`Ministral3ForCausalLM`],[`ernie4_5`,`Ernie4_5ForCausalLM`],[`starcoder2`,`Starcoder2ForCausalLM`],[`deepseek_v3`,`DeepseekV3ForCausalLM`],[`falcon`,`FalconForCausalLM`],[`falcon_h1`,`FalconH1ForCausalLM`],[`nemotron_h`,`NemotronHForCausalLM`],[`trocr`,`TrOCRForCausalLM`],[`solar_open`,`SolarOpenForCausalLM`],[`stablelm`,`StableLmForCausalLM`],[`modernbert-decoder`,`ModernBertDecoderForCausalLM`],[`hunyuan_v1_dense`,`HunYuanDenseV1ForCausalLM`],[`youtu`,`YoutuForCausalLM`],[`phi3_v`,`Phi3VForCausalLM`]]),tO=new Map([[`multi_modality`,`MultiModalityCausalLM`]]),nO=new Map([[`bert`,`BertForMaskedLM`],[`eurobert`,`EuroBertForMaskedLM`],[`neobert`,`NeoBertForMaskedLM`],[`modernbert`,`ModernBertForMaskedLM`],[`roformer`,`RoFormerForMaskedLM`],[`electra`,`ElectraForMaskedLM`],[`esm`,`EsmForMaskedLM`],[`convbert`,`ConvBertForMaskedLM`],[`camembert`,`CamembertForMaskedLM`],[`deberta`,`DebertaForMaskedLM`],[`deberta-v2`,`DebertaV2ForMaskedLM`],[`mpnet`,`MPNetForMaskedLM`],[`albert`,`AlbertForMaskedLM`],[`distilbert`,`DistilBertForMaskedLM`],[`roberta`,`RobertaForMaskedLM`],[`xlm`,`XLMWithLMHeadModel`],[`xlm-roberta`,`XLMRobertaForMaskedLM`],[`mobilebert`,`MobileBertForMaskedLM`],[`squeezebert`,`SqueezeBertForMaskedLM`]]),rO=new Map([[`bert`,`BertForQuestionAnswering`],[`neobert`,`NeoBertForQuestionAnswering`],[`roformer`,`RoFormerForQuestionAnswering`],[`electra`,`ElectraForQuestionAnswering`],[`convbert`,`ConvBertForQuestionAnswering`],[`camembert`,`CamembertForQuestionAnswering`],[`deberta`,`DebertaForQuestionAnswering`],[`deberta-v2`,`DebertaV2ForQuestionAnswering`],[`mpnet`,`MPNetForQuestionAnswering`],[`albert`,`AlbertForQuestionAnswering`],[`distilbert`,`DistilBertForQuestionAnswering`],[`roberta`,`RobertaForQuestionAnswering`],[`xlm`,`XLMForQuestionAnswering`],[`xlm-roberta`,`XLMRobertaForQuestionAnswering`],[`mobilebert`,`MobileBertForQuestionAnswering`],[`squeezebert`,`SqueezeBertForQuestionAnswering`]]),iO=new Map([[`vision-encoder-decoder`,`VisionEncoderDecoderModel`],[`idefics3`,`Idefics3ForConditionalGeneration`],[`smolvlm`,`SmolVLMForConditionalGeneration`]]),aO=new Map([[`llava`,`LlavaForConditionalGeneration`],[`llava_onevision`,`LlavaOnevisionForConditionalGeneration`],[`moondream1`,`Moondream1ForConditionalGeneration`],[`florence2`,`Florence2ForConditionalGeneration`],[`qwen2_vl`,`Qwen2VLForConditionalGeneration`],[`qwen2_5_vl`,`Qwen2_5_VLForConditionalGeneration`],[`qwen3_vl`,`Qwen3VLForConditionalGeneration`],[`qwen3_vl_moe`,`Qwen3VLMoeForConditionalGeneration`],[`qwen3_5`,`Qwen3_5ForConditionalGeneration`],[`qwen3_5_moe`,`Qwen3_5MoeForConditionalGeneration`],[`lfm2_vl`,`Lfm2VlForConditionalGeneration`],[`idefics3`,`Idefics3ForConditionalGeneration`],[`smolvlm`,`SmolVLMForConditionalGeneration`],[`paligemma`,`PaliGemmaForConditionalGeneration`],[`llava_qwen2`,`LlavaQwen2ForCausalLM`],[`gemma3`,`Gemma3ForConditionalGeneration`],[`gemma3n`,`Gemma3nForConditionalGeneration`],[`gemma4`,`Gemma4ForConditionalGeneration`],[`mistral3`,`Mistral3ForConditionalGeneration`],[`lighton_ocr`,`LightOnOcrForConditionalGeneration`],[`glm_ocr`,`GlmOcrForConditionalGeneration`]]),oO=new Map([[`granite_speech`,`GraniteSpeechForConditionalGeneration`],[`ultravox`,`UltravoxModel`],[`voxtral`,`VoxtralForConditionalGeneration`],[`voxtral_realtime`,`VoxtralRealtimeForConditionalGeneration`]]),sO=new Map([[`vision-encoder-decoder`,`VisionEncoderDecoderModel`]]),cO=new Map([[`vit`,`ViTForImageClassification`],[`ijepa`,`IJepaForImageClassification`],[`pvt`,`PvtForImageClassification`],[`vit_msn`,`ViTMSNForImageClassification`],[`fastvit`,`FastViTForImageClassification`],[`mobilevit`,`MobileViTForImageClassification`],[`mobilevitv2`,`MobileViTV2ForImageClassification`],[`beit`,`BeitForImageClassification`],[`deit`,`DeiTForImageClassification`],[`hiera`,`HieraForImageClassification`],[`convnext`,`ConvNextForImageClassification`],[`convnextv2`,`ConvNextV2ForImageClassification`],[`dinov2`,`Dinov2ForImageClassification`],[`dinov2_with_registers`,`Dinov2WithRegistersForImageClassification`],[`resnet`,`ResNetForImageClassification`],[`swin`,`SwinForImageClassification`],[`segformer`,`SegformerForImageClassification`],[`efficientnet`,`EfficientNetForImageClassification`],[`mobilenet_v1`,`MobileNetV1ForImageClassification`],[`mobilenet_v2`,`MobileNetV2ForImageClassification`],[`mobilenet_v3`,`MobileNetV3ForImageClassification`],[`mobilenet_v4`,`MobileNetV4ForImageClassification`]]),lO=new Map([[`detr`,`DetrForObjectDetection`],[`rt_detr`,`RTDetrForObjectDetection`],[`rt_detr_v2`,`RTDetrV2ForObjectDetection`],[`rf_detr`,`RFDetrForObjectDetection`],[`d_fine`,`DFineForObjectDetection`],[`table-transformer`,`TableTransformerForObjectDetection`],[`yolos`,`YolosForObjectDetection`]]),uO=new Map([[`owlvit`,`OwlViTForObjectDetection`],[`owlv2`,`Owlv2ForObjectDetection`],[`grounding-dino`,`GroundingDinoForObjectDetection`]]),dO=new Map([[`detr`,`DetrForSegmentation`],[`clipseg`,`CLIPSegForImageSegmentation`]]),fO=new Map([[`segformer`,`SegformerForSemanticSegmentation`],[`sapiens`,`SapiensForSemanticSegmentation`],[`swin`,`SwinForSemanticSegmentation`],[`mobilenet_v1`,`MobileNetV1ForSemanticSegmentation`],[`mobilenet_v2`,`MobileNetV2ForSemanticSegmentation`],[`mobilenet_v3`,`MobileNetV3ForSemanticSegmentation`],[`mobilenet_v4`,`MobileNetV4ForSemanticSegmentation`]]),pO=new Map([[`detr`,`DetrForSegmentation`],[`maskformer`,`MaskFormerForInstanceSegmentation`]]),mO=new Map([[`sam`,`SamModel`],[`sam2`,`Sam2Model`],[`edgetam`,`EdgeTamModel`],[`sam3_tracker`,`Sam3TrackerModel`]]),hO=new Map([[`wav2vec2`,`Wav2Vec2ForCTC`],[`wav2vec2-bert`,`Wav2Vec2BertForCTC`],[`unispeech`,`UniSpeechForCTC`],[`unispeech-sat`,`UniSpeechSatForCTC`],[`wavlm`,`WavLMForCTC`],[`hubert`,`HubertForCTC`],[`parakeet_ctc`,`ParakeetForCTC`]]),gO=new Map([[`wav2vec2`,`Wav2Vec2ForSequenceClassification`],[`wav2vec2-bert`,`Wav2Vec2BertForSequenceClassification`],[`unispeech`,`UniSpeechForSequenceClassification`],[`unispeech-sat`,`UniSpeechSatForSequenceClassification`],[`wavlm`,`WavLMForSequenceClassification`],[`hubert`,`HubertForSequenceClassification`],[`audio-spectrogram-transformer`,`ASTForAudioClassification`]]),_O=new Map([[`wavlm`,`WavLMForXVector`]]),vO=new Map([[`unispeech-sat`,`UniSpeechSatForAudioFrameClassification`],[`wavlm`,`WavLMForAudioFrameClassification`],[`wav2vec2`,`Wav2Vec2ForAudioFrameClassification`],[`pyannote`,`PyAnnoteForAudioFrameClassification`]]),yO=new Map([[`vitmatte`,`VitMatteForImageMatting`]]),bO=new Map([[`patchtst`,`PatchTSTForPrediction`],[`patchtsmixer`,`PatchTSMixerForPrediction`]]),xO=new Map([[`swin2sr`,`Swin2SRForImageSuperResolution`]]),SO=new Map([[`chmv2`,`CHMv2ForDepthEstimation`],[`dpt`,`DPTForDepthEstimation`],[`depth_anything`,`DepthAnythingForDepthEstimation`],[`glpn`,`GLPNForDepthEstimation`],[`sapiens`,`SapiensForDepthEstimation`],[`depth_pro`,`DepthProForDepthEstimation`],[`metric3d`,`Metric3DForDepthEstimation`],[`metric3dv2`,`Metric3Dv2ForDepthEstimation`]]),CO=new Map([[`sapiens`,`SapiensForNormalEstimation`]]),wO=new Map([[`vitpose`,`VitPoseForPoseEstimation`]]),TO=new Map([[`clip`,`CLIPVisionModelWithProjection`],[`siglip`,`SiglipVisionModel`],[`jina_clip`,`JinaCLIPVisionModel`]]),EO=[[WD,X.EncoderOnly],[GD,X.EncoderDecoder],[qD,X.DecoderOnlyWithoutHead],[KD,X.AutoEncoder],[ZD,X.EncoderOnly],[QD,X.EncoderOnly],[$D,X.Seq2Seq],[JD,X.Seq2Seq],[eO,X.DecoderOnly],[tO,X.MultiModality],[nO,X.EncoderOnly],[rO,X.EncoderOnly],[iO,X.Vision2Seq],[aO,X.ImageTextToText],[oO,X.AudioTextToText],[cO,X.EncoderOnly],[dO,X.EncoderOnly],[pO,X.EncoderOnly],[fO,X.EncoderOnly],[yO,X.EncoderOnly],[bO,X.EncoderOnly],[xO,X.EncoderOnly],[SO,X.EncoderOnly],[CO,X.EncoderOnly],[wO,X.EncoderOnly],[lO,X.EncoderOnly],[uO,X.EncoderOnly],[mO,X.MaskGeneration],[hO,X.EncoderOnly],[gO,X.EncoderOnly],[YD,X.Seq2Seq],[XD,X.EncoderOnly],[_O,X.EncoderOnly],[vO,X.EncoderOnly],[TO,X.EncoderOnly]];for(let[e,t]of EO)for(let n of e.values()){Ch.set(n,t);let e=Kh[n];Th.set(e,n),wh.set(n,e)}var DO=[[`MusicgenForConditionalGeneration`,oC,X.Musicgen],[`Phi3VForCausalLM`,uw,X.Phi3V],[`CLIPTextModelWithProjection`,$g,X.EncoderOnly],[`SiglipTextModel`,DT,X.EncoderOnly],[`JinaCLIPTextModel`,ax,X.EncoderOnly],[`ClapTextModelWithProjection`,Jg,X.EncoderOnly],[`ClapAudioModelWithProjection`,Yg,X.EncoderOnly],[`DacEncoderModel`,B_,X.EncoderOnly],[`DacDecoderModel`,V_,X.EncoderOnly],[`MimiEncoderModel`,Jx,X.EncoderOnly],[`MimiDecoderModel`,Yx,X.EncoderOnly],[`SnacEncoderModel`,FT,X.EncoderOnly],[`SnacDecoderModel`,IT,X.EncoderOnly],[`Gemma3nForConditionalGeneration`,Iy,X.ImageAudioTextToText],[`Gemma4ForConditionalGeneration`,Ry,X.ImageAudioTextToText],[`SupertonicForConditionalGeneration`,aE,X.Supertonic],[`ChatterboxModel`,Vg,X.Chatterbox],[`VoxtralRealtimeForConditionalGeneration`,oD,X.VoxtralRealtime]];for(let[e,t,n]of DO)Ch.set(e,n),Th.set(t,e),wh.set(e,t);var OO=new Map([[`modnet`,dO],[`birefnet`,dO],[`isnet`,dO],[`ben`,dO]]);for(let[e,t]of OO.entries())t.set(e,`PreTrainedModel`),Ch.set(e,X.EncoderOnly),wh.set(e,Z);var kO=new Set(OO.keys());Ch.set(`PreTrainedModel`,X.EncoderOnly),Th.set(Z,`PreTrainedModel`);var Q={MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES:ZD,MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES:QD,MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES:YD,MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES:XD,MODEL_FOR_MASKED_LM_MAPPING_NAMES:nO,MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES:rO,MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES:cO,MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES:dO,MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES:fO,MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES:pO,MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES:lO,MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES:uO,MODEL_FOR_MASK_GENERATION_MAPPING_NAMES:mO,MODEL_FOR_CTC_MAPPING_NAMES:hO,MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES:gO,MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES:_O,MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES:vO,MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES:sO,MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES:yO,MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES:xO,MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES:SO,MODEL_FOR_NORMAL_ESTIMATION_MAPPING_NAMES:CO,MODEL_FOR_POSE_ESTIMATION_MAPPING_NAMES:wO,MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES:TO,MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES:aO,MODEL_FOR_AUDIO_TEXT_TO_TEXT_MAPPING_NAMES:oO,MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES:$D,MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES:JD,MODEL_FOR_CAUSAL_LM_MAPPING_NAMES:eO,MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES:iO};vh(Q);var $=class{static MODEL_CLASS_MAPPINGS=null;static BASE_IF_FAIL=!1;static supports(e){if(!this.MODEL_CLASS_MAPPINGS)return!1;for(let t of this.MODEL_CLASS_MAPPINGS)if(t.has(e))return!0;return this.BASE_IF_FAIL}static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:a=`main`,model_file_name:o=null,subfolder:s=`onnx`,device:c=null,dtype:l=null,use_external_data_format:u=null,session_options:d={}}={}){let f={progress_callback:t,config:n,cache_dir:r,local_files_only:i,revision:a,model_file_name:o,subfolder:s,device:c,dtype:l,use_external_data_format:u,session_options:d};if(f.config=await Tm.from_pretrained(e,f),!this.MODEL_CLASS_MAPPINGS)throw Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);let{model_type:p}=f.config;for(let t of this.MODEL_CLASS_MAPPINGS){let n=t.get(p);if(!n){for(let e of t.values())if(e[0]===p){n=e;break}if(!n)continue}return await Kh[n].from_pretrained(e,f)}if(this.BASE_IF_FAIL)return kO.has(p)||N.warn(`Unknown model class "${p}", attempting to construct from base class.`),await Z.from_pretrained(e,f);throw Error(`Unsupported model type: ${p}`)}},AO=class extends ${static MODEL_CLASS_MAPPINGS=EO.map(e=>e[0]);static BASE_IF_FAIL=!0},jO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]},MO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]},NO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]},PO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]},FO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]},IO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES]},LO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES]},RO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_MASKED_LM_MAPPING_NAMES]},zO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]},BO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]},VO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]},HO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]},UO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES]},WO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES]},GO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]},KO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_MASK_GENERATION_MAPPING_NAMES]});var qO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_CTC_MAPPING_NAMES]},JO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES]};var YO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES]});var XO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES]},ZO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_NORMAL_ESTIMATION_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_POSE_ESTIMATION_MAPPING_NAMES]};var QO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_TEXT_TO_TEXT_MAPPING_NAMES]};async function $O(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>Hd.read(e)))}async function ek(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>typeof e==`string`||e instanceof URL?Ku(e,t):e instanceof Float64Array?new Float32Array(e):e))}function tk(e,t){t&&(e=e.map(e=>e|0));let[n,r,i,a]=e;return{xmin:n,ymin:r,xmax:i,ymax:a}}var nk=class extends ni{constructor({task:e,model:t,tokenizer:n=null,processor:r=null}){super(),this.task=e,this.model=t,this.tokenizer=n,this.processor=r}async dispose(){await this.model.dispose()}},rk=class extends nk{async _call(e,{top_k:t=1}={}){let n=this.tokenizer(e,{padding:!0,truncation:!0}),r=await this.model(n),{problem_type:i,id2label:a}=this.model.config,o=i===`multi_label_classification`?e=>e.sigmoid():e=>new U(`float32`,oc(e.data),e.dims),s=[];for(let e of r.logits){let n=await al(o(e),t),r=n[0].tolist(),i=n[1].tolist().map((e,t)=>({label:a?a[e]:`LABEL_${e}`,score:r[t]}));t===1?s.push(...i):s.push(i)}return Array.isArray(e)||t===1?s:s[0]}},ik=class extends nk{async _call(e,{ignore_labels:t=[`O`],aggregation_strategy:n=`none`}={}){if(n!==`none`&&n!==`simple`)throw Error(`Invalid aggregation_strategy: "${n}". Must be one of "none" or "simple".`);let r=Array.isArray(e),i=this.tokenizer(r?e:[e],{padding:!0,truncation:!0}),a=(await this.model(i)).logits,o=this.model.config.id2label,s=[];for(let e=0;e<a.dims[0];++e){let r=i.input_ids[e].tolist(),c=a[e],l=[];for(let e=0;e<c.dims[0];++e){let n=c[e],i=lc(n.data)[1],a=o?o[i]:`LABEL_${i}`;if(t.includes(a))continue;let s=this.tokenizer.decode([r[e]],{skip_special_tokens:!0});if(s===``)continue;let u=oc(n.data);l.push({entity:a,score:u[i],index:e,word:s})}s.push(n===`simple`?ok(l,r,this.tokenizer):l)}return r?s:s[0]}};function ak(e){let t=e[0];return e[1]===`-`&&(t===`B`||t===`I`||t===`E`||t===`S`)?[t,e.slice(2)]:[`I`,e]}function ok(e,t,n){let r=[],i=null;for(let t=0;t<e.length;++t){let[n,a]=ak(e[t].entity);i===a&&n!==`B`&&n!==`S`?(r[r.length-1].end=t+1,n===`E`&&(i=null)):(r.push({tag:a,start:t,end:t+1}),i=n===`S`?null:a)}return r.map(({tag:r,start:i,end:a})=>{let o=0,s=[];for(let n=i;n<a;++n)o+=e[n].score,s.push(t[e[n].index]);return{entity_group:r,score:o/(a-i),word:n.decode(s,{skip_special_tokens:!0})}})}var sk=class extends nk{async _call(e,t,{top_k:n=1}={}){let r=this.tokenizer(e,{text_pair:t,padding:!0,truncation:!0}),i=Array.isArray(e),{start_logits:a,end_logits:o}=await this.model(r),s=r.input_ids.tolist(),c=r.attention_mask.tolist(),{all_special_ids:l,sep_token_id:u}=this.tokenizer,d=[];for(let e=0;e<a.dims[0];++e){let t=s[e],r=t.findIndex(e=>e==u),i=a[e].tolist(),f=o[e].tolist();for(let n=1;n<i.length;++n)(c[e]==0||n<=r||l.findIndex(e=>e==t[n])!==-1)&&(i[n]=-1/0,f[n]=-1/0);let p=oc(i).map((e,t)=>[e,t]),m=oc(f).map((e,t)=>[e,t]);p[0][0]=0,m[0][0]=0;let h=li(p,m).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]),g=[];for(let e=0;e<Math.min(h.length,n);++e){let[n,r,i]=h[e],a=t.slice(n,r+1),o=this.tokenizer.decode(a,{skip_special_tokens:!0});g.push({answer:o,score:i})}n===1?d.push(...g):d.push(g)}return i?d:d[0]}},ck=class extends nk{async _call(e,{top_k:t=5}={}){let{mask_token_id:n,mask_token:r}=this.tokenizer,i=this.tokenizer(e,{padding:!0,truncation:!0}),{logits:a}=await this.model(i),o=[],s=i.input_ids.tolist();for(let e=0;e<s.length;++e){let i=s[e],c=i.findIndex(e=>e==n);if(c===-1)throw Error(`Mask token (${r}) not found in text.`);let l=a[e][c],u=await al(new U(`float32`,oc(l.data),l.dims),t),d=u[0].tolist(),f=u[1].tolist();o.push(f.map((e,t)=>{let n=i.slice();return n[c]=e,{score:d[t],token:Number(e),token_str:this.tokenizer.decode([e]),sequence:this.tokenizer.decode(n,{skip_special_tokens:!0})}}))}return Array.isArray(e)?o:o[0]}},lk=class extends nk{_default_generation_config={max_new_tokens:256};_key=`generated_text`;async _call(e,t={}){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 r=this.tokenizer,i={padding:!0,truncation:!0},a;a=this.task===`translation`&&`_build_translation_inputs`in r?r._build_translation_inputs(e,i,t):r(e,i);let o=await this.model.generate({...a,...this._default_generation_config,...t});return r.batch_decode(o,{skip_special_tokens:!0}).map(e=>({[this._key]:e}))}},uk=class extends lk{_key=`summary_text`},dk=class extends lk{_key=`translation_text`};function fk(e){return Array.isArray(e)&&e.every(e=>`role`in e&&`content`in e)}var pk=class extends nk{_default_generation_config={max_new_tokens:256};async _call(e,t={}){let{add_special_tokens:n,return_full_text:r,tools:i,documents:a,chat_template:o,tokenizer_encode_kwargs:s,...c}=t,l=!1,u=!1,d=n??(this.tokenizer.add_bos_token||this.tokenizer.add_eos_token)??!1,f=s,p;if(typeof e==`string`)p=e=[e];else if(Array.isArray(e)&&e.every(e=>typeof e==`string`))l=!0,p=e;else{if(fk(e))e=[e];else if(Array.isArray(e)&&e.every(fk))l=!0;else throw Error(`Input must be a string, an array of strings, a Chat, or an array of Chats`);u=!0;let t={tokenize:!1,add_generation_prompt:!0,...di({tools:i,documents:a,chat_template:o},[`tools`,`documents`,`chat_template`]),...f};p=e.map(e=>this.tokenizer.apply_chat_template(e,t)),d=!1,f=void 0}let m=u?!1:r??!0;this.tokenizer.padding_side=`left`;let h=this.tokenizer(p,{add_special_tokens:d,padding:!0,truncation:!0,...f}),g=await this.model.generate({...h,...this._default_generation_config,...c}),_=this.tokenizer.batch_decode(g,{skip_special_tokens:!0}),v;!m&&h.input_ids.dims.at(-1)>0&&(v=this.tokenizer.batch_decode(h.input_ids,{skip_special_tokens:!0}).map(e=>e.length));let y=Array.from({length:e.length},e=>[]);for(let t=0;t<_.length;++t){let n=Math.floor(t/g.dims[0]*e.length);v&&(_[t]=_[t].slice(v[n])),y[n].push({generated_text:u?[...e[n],{role:`assistant`,content:_[t]}]:_[t]})}return!l&&y.length===1?y[0]:y}},mk=class extends nk{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,this.entailment_id===void 0&&(N.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,this.contradiction_id===void 0&&(N.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:r=!1}={}){let i=Array.isArray(e);i||(e=[e]),Array.isArray(t)||(t=[t]);let a=t.map(e=>n.replace(`{}`,e)),o=r||t.length===1,s=[];for(let n of e){let e=[];for(let t of a){let r=this.tokenizer(n,{text_pair:t,padding:!0,truncation:!0}),i=await this.model(r);o?e.push([i.logits.data[this.contradiction_id],i.logits.data[this.entailment_id]]):e.push(i.logits.data[this.entailment_id])}let r=(o?e.map(e=>oc(e)[1]):oc(e)).map((e,t)=>[e,t]).sort((e,t)=>t[0]-e[0]);s.push({sequence:n,labels:r.map(e=>t[e[1]]),scores:r.map(e=>e[0])})}return i?s:s[0]}},hk=class extends nk{async _call(e,{top_k:t=5}={}){let n=this.processor.feature_extractor.config.sampling_rate,r=await ek(e,n),i=this.model.config.id2label,a=[];for(let e of r){let n=await this.processor(e),r=(await this.model(n)).logits[0],o=await al(new U(`float32`,oc(r.data),r.dims),t),s=o[0].tolist(),c=o[1].tolist().map((e,t)=>({label:i?i[e]:`LABEL_${e}`,score:s[t]}));a.push(c)}return Array.isArray(e)?a:a[0]}},gk=class extends nk{async _call(e,t,{hypothesis_template:n=`This is a sound of {}.`}={}){let r=!Array.isArray(e);r&&(e=[e]);let i=t.map(e=>n.replace(`{}`,e)),a=this.tokenizer(i,{padding:!0,truncation:!0}),o=this.processor.feature_extractor.config.sampling_rate,s=await ek(e,o),c=[];for(let e of s){let n=await this.processor(e),r=oc((await this.model({...a,...n})).logits_per_audio.data);c.push([...r].map((e,n)=>({score:e,label:t[n]})))}return r?c[0]:c}},_k=class extends nk{_default_generation_config={};async _call(e,t={}){switch(t={...this._default_generation_config,...t},this.model.config.model_type){case`whisper`:case`lite-whisper`:return this._call_whisper(e,t);case`wav2vec2`:case`wav2vec2-bert`:case`unispeech`:case`unispeech-sat`:case`hubert`:case`parakeet_ctc`:return this._call_wav2vec2(e,t);case`moonshine`:return this._call_moonshine(e,t);case`cohere_asr`:return this._call_cohere_asr(e,t);default:throw Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(e,t){t.language&&N.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),t.task&&N.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor.config.sampling_rate,a=await ek(r,i),o=[];for(let e of a){let t=await this.processor(e),n=(await this.model(t)).logits[0],r=[];for(let e of n)r.push(lc(e.data)[1]);let i=this.tokenizer.decode(r,{skip_special_tokens:!0}).trim();o.push({text:i})}return n?o[0]:o}async _call_whisper(e,t){let n=t.return_timestamps??!1,r=t.chunk_length_s??0,i=t.force_full_sequences??!1,a=t.stride_length_s??null,o={...t};n===`word`&&(o.return_token_timestamps=!0,o.return_timestamps=!0);let s=!Array.isArray(e),c=s?[e]:e,l=this.processor.feature_extractor.config,u=l.chunk_length/this.model.config.max_source_positions,d=l.hop_length,f=l.sampling_rate,p=await ek(c,f),m=[];for(let e of p){let t=[];if(r>0){if(a===null)a=r/6;else if(r<=a)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");let n=f*r,i=f*a,o=n-2*i,s=0;for(;;){let r=s+n,a=e.subarray(s,r),c=await this.processor(a),l=s===0,u=r>=e.length;if(t.push({stride:[a.length,l?0:i,u?0:i],input_features:c.input_features,is_last:u}),u)break;s+=o}}else t=[{stride:[e.length,0,0],input_features:(await this.processor(e)).input_features,is_last:!0}];for(let e of t){o.num_frames=Math.floor(e.stride[0]/d);let t=await this.model.generate({inputs:e.input_features,...o});if(n===`word`){let n=t.sequences.tolist()[0],r=t.token_timestamps.tolist()[0],i=this.tokenizer.timestamp_begin,a=Math.max(n.findIndex(e=>Number(e)>=i),0);e.tokens=n.slice(a),e.token_timestamps=r.slice(a).map(e=>hc(e,2))}else e.tokens=t[0].tolist();e.stride=e.stride.map(e=>e/f)}let[s,c]=this.tokenizer._decode_asr(t,{time_precision:u,return_timestamps:n,force_full_sequences:i});m.push({text:s,...c})}return s?m[0]:m}async _call_moonshine(e,t){let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor.config.sampling_rate,a=await ek(r,i),o=[];for(let e of a){let n=await this.processor(e),r=Math.floor(e.length/i)*6,a=await this.model.generate({max_new_tokens:r,...t,...n}),s=this.processor.batch_decode(a,{skip_special_tokens:!0})[0];o.push({text:s})}return n?o[0]:o}async _call_cohere_asr(e,t){let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor,a=i.config.sampling_rate,o=await ek(r,a),s=t.language??`en`,c=this.processor.get_decoder_prompt_ids(s),l=[];for(let e of o){let n=i.split_audio(e),r=[];for(let e of n){let n=await this.processor(e),i=await this.model.generate({...n,decoder_input_ids:c,...t}),a=this.tokenizer.decode(i[0].tolist(),{skip_special_tokens:!0}).trim();r.push(a)}let a=this.processor.constructor.join_chunks(r,s);l.push({text:a})}return n?l[0]:l}},vk=class extends nk{DEFAULT_VOCODER_ID=`Xenova/speecht5_hifigan`;constructor(e){super(e),this.vocoder=e.vocoder??null}async _prepare_speaker_embeddings(e,t){if((typeof e==`string`||e instanceof URL)&&(e=new Float32Array(await(await M.fetch(e)).arrayBuffer())),e instanceof Float32Array)e=new U(`float32`,e,[e.length]);else if(!(e instanceof U))throw Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");if(t>1){if(e.dims[0]===1)e=e.repeat(t,1);else if(e.dims[0]!==t)throw Error(`Expected speaker embeddings batch size to be 1 or ${t}, but got ${e.dims[0]}.`)}return e}_postprocess_waveform(e,t,n,r=null){let i=t.data,[a,o]=t.dims,s=r?r.data:null,c=[];for(let e=0;e<a;++e){let t=s?Math.min(Math.ceil(s[e]),o):o,r=e*o;c.push(new dd(i.slice(r,r+t),n))}return Array.isArray(e)?c:c[0]}async _call(e,t){return this.processor?this._call_text_to_spectrogram(e,t):this.model.config.model_type===`supertonic`?this._call_supertonic(e,t):this._call_text_to_waveform(e)}async _call_supertonic(e,{speaker_embeddings:t,num_inference_steps:n,speed:r}){if(!t)throw Error(`Speaker embeddings must be provided for Supertonic models.`);let{sampling_rate:i,style_dim:a}=this.model.config,o=this.tokenizer(e,{padding:!0,truncation:!0}),s=o.input_ids.dims[0];t=await this._prepare_speaker_embeddings(t,s),t=t.view(s,-1,a);let{waveform:c,durations:l}=await this.model.generate_speech({...o,style:t,num_inference_steps:n,speed:r});return this._postprocess_waveform(e,c,i,l)}async _call_text_to_waveform(e){let t=this.tokenizer(e,{padding:!0,truncation:!0}),{waveform:n}=await this.model(t),r=this.model.config.sampling_rate;return this._postprocess_waveform(e,n,r)}async _call_text_to_spectrogram(e,{speaker_embeddings:t}){this.vocoder||=(N.info(`No vocoder specified, using default HifiGan vocoder.`),await AO.from_pretrained(this.DEFAULT_VOCODER_ID,{dtype:`fp32`}));let{input_ids:n}=this.tokenizer(e,{padding:!0,truncation:!0}),r=n.dims[0];t=await this._prepare_speaker_embeddings(t,r),t=t.view(r,-1);let{waveform:i}=await this.model.generate_speech(n,t,{vocoder:this.vocoder}),a=this.processor.feature_extractor.config.sampling_rate;return this._postprocess_waveform(e,i,a)}},yk=class extends nk{async _call(e,t={}){let n=Array.isArray(e),r=await $O(e),{pixel_values:i}=await this.processor(r),a=[];for(let e of i){e.dims=[1,...e.dims];let n=await this.model.generate({inputs:e,...t}),r=this.tokenizer.batch_decode(n,{skip_special_tokens:!0}).map(e=>({generated_text:e.trim()}));a.push(r)}return n?a:a[0]}},bk=class extends nk{async _call(e,{top_k:t=5}={}){let n=await $O(e),{pixel_values:r}=await this.processor(n),i=await this.model({pixel_values:r}),{id2label:a}=this.model.config,o=[];for(let e of i.logits){let n=await al(new U(`float32`,oc(e.data),e.dims),t),r=n[0].tolist(),i=n[1].tolist().map((e,t)=>({label:a?a[e]:`LABEL_${e}`,score:r[t]}));o.push(i)}return Array.isArray(e)?o:o[0]}},xk={panoptic:`post_process_panoptic_segmentation`,instance:`post_process_instance_segmentation`,semantic:`post_process_semantic_segmentation`},Sk=class extends nk{async _call(e,{threshold:t=.5,mask_threshold:n=.5,overlap_mask_area_threshold:r=.8,label_ids_to_fuse:i=null,target_sizes:a=null,subtask:o=null}={}){if(Array.isArray(e)&&e.length!==1)throw Error(`Image segmentation pipeline currently only supports a batch size of 1.`);let s=await $O(e),c=s.map(e=>[e.height,e.width]),l=await this.processor(s),{inputNames:u,outputNames:d}=this.model.sessions.model;if(!u.includes(`pixel_values`)){if(u.length!==1)throw Error(`Expected a single input name, but got ${u.length} inputs: ${u}.`);let e=u[0];if(e in l)throw Error(`Input name ${e} already exists in the inputs.`);l[e]=l.pixel_values}let f=await this.model(l),p=null;if(o!==null)p=xk[o];else if(this.processor.image_processor){for(let[e,t]of Object.entries(xk))if(t in this.processor.image_processor){p=this.processor.image_processor[t].bind(this.processor.image_processor),o=e;break}}let m=this.model.config.id2label,h=[];if(!o){let e=f[d[0]];for(let t=0;t<c.length;++t){let n=c[t],r=e[t];r.data.some(e=>e<-1e-5||e>1.00001)&&r.sigmoid_();let i=await Hd.fromTensor(r.mul_(255).to(`uint8`)).resize(n[1],n[0]);h.push({label:null,score:null,mask:i})}}else if(o===`panoptic`||o===`instance`){let e=p(f,t,n,r,i,a??c)[0],o=e.segmentation;for(let t of e.segments_info){let e=new Uint8ClampedArray(o.data.length);for(let n=0;n<o.data.length;++n)o.data[n]===t.id&&(e[n]=255);let n=new Hd(e,o.dims[1],o.dims[0],1);h.push({score:t.score,label:m[t.label_id],mask:n})}}else if(o===`semantic`){let{segmentation:e,labels:t}=p(f,a??c)[0];for(let n of t){let t=new Uint8ClampedArray(e.data.length);for(let r=0;r<e.data.length;++r)e.data[r]===n&&(t[r]=255);let r=new Hd(t,e.dims[1],e.dims[0],1);h.push({score:null,label:m[n],mask:r})}}else throw Error(`Subtask ${o} not supported.`);return h}},Ck=Object.freeze({"text-classification":{pipeline:rk,model:jO,default:{model:`Xenova/distilbert-base-uncased-finetuned-sst-2-english`},type:`text`},"token-classification":{pipeline:ik,model:MO,default:{model:`Xenova/bert-base-multilingual-cased-ner-hrl`},type:`text`},"question-answering":{pipeline:sk,model:zO,default:{model:`Xenova/distilbert-base-cased-distilled-squad`},type:`text`},"fill-mask":{pipeline:ck,model:RO,default:{model:`onnx-community/ettin-encoder-32m-ONNX`,dtype:`fp32`},type:`text`},summarization:{pipeline:uk,model:NO,default:{model:`Xenova/distilbart-cnn-6-6`},type:`text`},translation:{pipeline:dk,model:NO,default:{model:`Xenova/t5-small`},type:`text`},"text2text-generation":{pipeline:lk,model:NO,default:{model:`Xenova/flan-t5-small`},type:`text`},"text-generation":{pipeline:pk,model:LO,default:{model:`onnx-community/Qwen3-0.6B-ONNX`,dtype:`q4`},type:`text`},"zero-shot-classification":{pipeline:mk,model:jO,default:{model:`Xenova/distilbert-base-uncased-mnli`},type:`text`},"audio-classification":{pipeline:hk,model:JO,default:{model:`Xenova/wav2vec2-base-superb-ks`},type:`audio`},"zero-shot-audio-classification":{pipeline:gk,model:AO,default:{model:`Xenova/clap-htsat-unfused`},type:`multimodal`},"automatic-speech-recognition":{pipeline:_k,model:[PO,qO],default:{model:`Xenova/whisper-tiny.en`},type:`multimodal`},"text-to-audio":{pipeline:vk,model:[IO,FO],default:{model:`onnx-community/Supertonic-TTS-ONNX`,dtype:`fp32`},type:`text`},"image-to-text":{pipeline:yk,model:BO,default:{model:`Xenova/vit-gpt2-image-captioning`},type:`multimodal`},"image-classification":{pipeline:bk,model:VO,default:{model:`Xenova/vit-base-patch16-224`},type:`multimodal`},"image-segmentation":{pipeline:Sk,model:[HO,UO,WO],default:{model:`Xenova/detr-resnet-50-panoptic`},type:`multimodal`},"background-removal":{pipeline:class extends Sk{async _call(e,t={}){let n=await $O(e),r=await super._call(e,t),i=n.map((e,t)=>{let n=e.clone();return n.putAlpha(r[t].mask),n});return Array.isArray(e)?i:i[0]}},model:[HO,UO,WO],default:{model:`Xenova/modnet`},type:`image`},"zero-shot-image-classification":{pipeline:class extends nk{async _call(e,t,{hypothesis_template:n=`This is a photo of {}`}={}){let r=Array.isArray(e),i=await $O(e),a=t.map(e=>n.replace(`{}`,e)),o=this.tokenizer(a,{padding:this.model.config.model_type!==`siglip`||`max_length`,truncation:!0}),{pixel_values:s}=await this.processor(i),c=await this.model({...o,pixel_values:s}),l=this.model.config.model_type===`siglip`?e=>e.sigmoid().data:e=>oc(e.data),u=[];for(let e of c.logits_per_image){let n=[...l(e)].map((e,n)=>({score:e,label:t[n]}));n.sort((e,t)=>t.score-e.score),u.push(n)}return r?u:u[0]}},model:AO,default:{model:`Xenova/clip-vit-base-patch32`},type:`multimodal`},"object-detection":{pipeline:class extends nk{async _call(e,{threshold:t=.9,percentage:n=!1}={}){let r=Array.isArray(e);if(r&&e.length!==1)throw Error(`Object detection pipeline currently only supports a batch size of 1.`);let i=await $O(e),a=n?null:i.map(e=>[e.height,e.width]),{pixel_values:o,pixel_mask:s}=await this.processor(i),c=await this.model({pixel_values:o,pixel_mask:s}),l=this.processor.image_processor.post_process_object_detection(c,t,a),{id2label:u}=this.model.config,d=l.map(e=>e.boxes.map((t,r)=>({score:e.scores[r],label:u[e.classes[r]],box:tk(t,!n)})));return r?d:d[0]}},model:GO,default:{model:`Xenova/detr-resnet-50`},type:`multimodal`},"zero-shot-object-detection":{pipeline:class extends nk{async _call(e,t,{threshold:n=.1,top_k:r=null,percentage:i=!1}={}){let a=Array.isArray(e),o=await $O(e),s=this.tokenizer(t,{padding:!0,truncation:!0}),c=await this.processor(o),l=[];for(let e=0;e<o.length;++e){let a=o[e],u=i?null:[[a.height,a.width]],d=c.pixel_values[e].unsqueeze_(0),f=await this.model({...s,pixel_values:d}),p;if(`post_process_grounded_object_detection`in this.processor){let e=this.processor.post_process_grounded_object_detection(f,s.input_ids,{box_threshold:n,text_threshold:n,target_sizes:u})[0];p=e.boxes.map((t,n)=>({score:e.scores[n],label:e.labels[n],box:tk(t,!i)}))}else{let e=this.processor.image_processor.post_process_object_detection(f,n,u,!0)[0];p=e.boxes.map((n,r)=>({score:e.scores[r],label:t[e.classes[r]],box:tk(n,!i)}))}p.sort((e,t)=>t.score-e.score),r!==null&&(p=p.slice(0,r)),l.push(p)}return a?l:l[0]}},model:KO,default:{model:`Xenova/owlvit-base-patch32`},type:`multimodal`},"document-question-answering":{pipeline:class extends nk{_default_generation_config={max_new_tokens:256};async _call(e,t,n={}){if(Array.isArray(e)){if(e.length!==1)throw Error(`Document Question Answering pipeline currently only supports a batch size of 1.`);e=e[0]}let r=(await $O(e))[0],{pixel_values:i}=await this.processor(r),a=`<s_docvqa><s_question>${t}</s_question><s_answer>`,o=this.tokenizer(a,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,s=await this.model.generate({inputs:i,max_length:this.model.config.decoder.max_position_embeddings,decoder_input_ids:o,...this._default_generation_config,...n}),c=this.tokenizer.batch_decode(s)[0].match(/<s_answer>(.*?)<\/s_answer>/),l=null;return c&&c.length>=2&&(l=c[1].trim()),[{answer:l}]}},model:YO,default:{model:`Xenova/donut-base-finetuned-docvqa`},type:`multimodal`},"image-to-image":{pipeline:class extends nk{async _call(e){let t=await $O(e),n=await this.processor(t),r=await this.model(n),i=[];for(let e of r.reconstruction){let t=e.squeeze().clamp_(0,1).mul_(255).round_().to(`uint8`);i.push(Hd.fromTensor(t))}return Array.isArray(e)?i:i[0]}},model:XO,default:{model:`Xenova/swin2SR-classical-sr-x2-64`},type:`image`},"depth-estimation":{pipeline:class extends nk{async _call(e){let t=await $O(e),n=await this.processor(t),{predicted_depth:r}=await this.model(n),i=[];for(let e=0;e<t.length;++e){let n=r[e],[a,o]=n.dims.slice(-2),[s,c]=t[e].size,l=(await rl(n.view(1,1,a,o),{size:[c,s],mode:`bilinear`})).view(c,s),u=l.min().item(),d=l.max().item(),f=l.sub(u).div_(d-u).mul_(255).to(`uint8`).unsqueeze(0),p=Hd.fromTensor(f);i.push({predicted_depth:l,depth:p})}return Array.isArray(e)?i:i[0]}},model:ZO,default:{model:`onnx-community/depth-anything-v2-small`},type:`image`},"feature-extraction":{pipeline:class extends nk{async _call(e,{pooling:t=`none`,normalize:n=!1,quantize:r=!1,precision:i=`binary`}={}){let a=this.tokenizer(e,{padding:!0,truncation:!0}),o=await this.model(a),s=o.last_hidden_state??o.logits??o.token_embeddings;switch(t){case`none`:break;case`mean`:s=cl(s,a.attention_mask);break;case`first_token`:case`cls`:s=s.slice(null,0);break;case`last_token`:case`eos`:s=s.slice(null,-1);break;default:throw Error(`Pooling method '${t}' not supported.`)}return n&&(s=s.normalize(2,-1)),r&&(s=El(s,i)),s}},model:AO,default:{model:`onnx-community/all-MiniLM-L6-v2-ONNX`,dtype:`fp32`},type:`text`},"image-feature-extraction":{pipeline:class extends nk{async _call(e,{pool:t=null}={}){let n=await $O(e),{pixel_values:r}=await this.processor(n),i=await this.model({pixel_values:r}),a;if(t){if(!(`pooler_output`in i))throw Error(`No pooled output was returned. Make sure the model has a 'pooler' layer when using the 'pool' option.`);a=i.pooler_output}else a=i.last_hidden_state??i.logits??i.image_embeds;return a}},model:[QO,AO],default:{model:`onnx-community/dinov3-vits16-pretrain-lvd1689m-ONNX`,dtype:`fp32`},type:`image`}}),wk=Object.freeze({"sentiment-analysis":`text-classification`,ner:`token-classification`,asr:`automatic-speech-recognition`,"text-to-speech":`text-to-audio`,embeddings:`feature-extraction`});async function Tk(e){if(!e)throw Error(`modelId is required`);return(await Ks(e,Lu,{})).exists?[Lu]:[]}async function Ek(e,{config:t=null,dtype:n=null,device:r=null,model_file_name:i=null,include_tokenizer:a=!0,include_processor:o=!0}={}){let s=await gh(e,{config:t,dtype:n,device:r,model_file_name:i});if(a){let t=await Dl(e);s.push(...t)}if(o){let t=await Tk(e);s.push(...t)}return s}async function Dk(e,t,n={}){e=wk[e]??e;let r=Ck[e];if(!r)throw Error(`Unsupported pipeline task: ${e}. Must be one of [${Object.keys(Ck).join(`, `)}]`);let{type:i}=r,a=i!==`audio`&&i!==`image`,o=i!==`text`,s=await Ek(t,{...n,include_tokenizer:a,include_processor:o});if(e===`text-generation`){let e=fh(mh(await hh(t,n)));if(e){let t=Object.values(e).map(e=>`onnx/${e}`);return s.filter(e=>!e.startsWith(`onnx/`)||t.some(t=>e.startsWith(t)))}}return s}j.IS_PROCESS_AVAILABLE;async function Ok(e,t,n={}){let r=await Vs(n?.cache_dir);if(!r)return{allCached:!1,files:t.map(e=>({file:e,cached:!1}))};let i=await Promise.all(t.map(async t=>{let{localPath:i,proposedCacheKey:a}=Xs(e,t,n,r);return{file:t,cached:!!await Zs(r,i,a)}}));return{allCached:i.every(e=>e.cached),files:i}}async function kk(e,t,n={}){let r=await Vs(n?.cache_dir);if(!r)return!1;let{localPath:i,proposedCacheKey:a}=Xs(e,t,n,r);return!!await Zs(r,i,a)}async function Ak(e,t={}){if(!e)throw Error(`modelId is required`);return await kk(e,`config.json`,t)?(await Ok(e,await Ek(e,t),t)).allCached:!1}async function jk(e,t={}){if(!e)throw Error(`modelId is required`);return await Ok(e,await Ek(e,t),t)}async function Mk(e,t,n={}){if(!e)throw Error(`task is required`);if(!t)throw Error(`modelId is required`);return await kk(t,`config.json`,n)?(await Ok(t,await Dk(e,t,n),n)).allCached:!1}async function Nk(e,t,n={}){if(!e)throw Error(`task is required`);if(!t)throw Error(`modelId is required`);return await Ok(t,await Dk(e,t,n),n)}async function Pk(e,t,n={}){let r=await Vs(n?.cache_dir);if(!r)return{filesDeleted:0,filesCached:0,files:t.map(e=>({file:e,deleted:!1,wasCached:!1}))};if(!r.delete)throw Error(`Cache does not support delete operation`);let i=await Promise.all(t.map(async t=>{let{localPath:i,proposedCacheKey:a}=Xs(e,t,n,r),o=!!await Zs(r,i,a),s=!1;if(o){let e=await r.delete(a),t=!e&&a!==i&&await r.delete(i);s=e||t}return{file:t,deleted:s,wasCached:o}}));return{filesDeleted:i.filter(e=>e.deleted).length,filesCached:i.filter(e=>e.wasCached).length,files:i}}async function Fk(e,t={}){if(!e)throw Error(`modelId is required`);return await Pk(e,await Ek(e,t),t)}async function Ik(e,t,n={}){if(!e)throw Error(`task is required`);if(!t)throw Error(`modelId is required`);return await Pk(t,await Dk(e,t,n),n)}var Lk=Object.keys(Zc);async function Rk(e,{config:t=null,model_file_name:n=null,revision:r=`main`,cache_dir:i=null,local_files_only:a=!1}={}){t=await hh(e,{config:t,cache_dir:i,local_files_only:a,revision:r});let{sessions:o}=ph(mh(t),t,{model_file_name:n}),s=Object.values(o),c={revision:r,cache_dir:i,local_files_only:a};return(await Promise.all(Lk.map(async t=>{let n=Zc[t]??``;return{dtype:t,available:(await Promise.all(s.map(async t=>(await Ks(e,`onnx/${t}${n}.onnx`,c)).exists))).every(Boolean)}}))).filter(e=>e.available).map(e=>e.dtype)}var zk=class{static async get_files(e,t={}){return Ek(e,t)}static async get_pipeline_files(e,t,n={}){return Dk(e,t,n)}static async get_model_files(e,t={}){return gh(e,t)}static async get_tokenizer_files(e){return Dl(e)}static async get_processor_files(e){return Tk(e)}static async get_available_dtypes(e,t={}){return Rk(e,t)}static async is_cached(e,t={}){return Ak(e,t)}static async is_cached_files(e,t={}){return jk(e,t)}static async is_pipeline_cached(e,t,n={}){return Mk(e,t,n)}static async is_pipeline_cached_files(e,t,n={}){return Nk(e,t,n)}static async get_file_metadata(e,t,n={}){return Ks(e,t,n)}static async clear_cache(e,t={}){return Fk(e,t)}static async clear_pipeline_cache(e,t,n={}){return Ik(e,t,n)}};export{zk as ModelRegistry,M as env};