/*!
 * ONNX Runtime Web v1.26.0-dev.20260416-b7804b056c
 * Copyright (c) Microsoft Corporation. All rights reserved.
 * Licensed under the MIT License.
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Xx(e);case"Split":return new rT(e);case"Punctuation":return new sT(e);case"Digits":return new oT(e);case"Replace":return new uT(e);case"FixedLength":return new mT(e);default:throw new Error(`Unknown PreTokenizer type: ${e.type}`)}}var Ny=gT,wT=class extends Mi{constructor(e){super(),this.config=e,this.vocab=[],this.tokens_to_ids=new Map,this.unk_token_id=void 0,this.unk_token=void 0,this.end_of_word_suffix=void 0,this.fuse_unk=this.config.fuse_unk??!1}_call(e){let t=this.encode(e);return this.fuse_unk&&(t=hx(t,this.tokens_to_ids,this.unk_token_id)),t}},Sl=wT,yT=class extends Sl{constructor(e){super(e),this.max_input_chars_per_word=100,this.tokens_to_ids=Hh(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.max_input_chars_per_word=e.max_input_chars_per_word??100,this.vocab=new Array(this.tokens_to_ids.size);for(const[t,r]of this.tokens_to_ids)this.vocab[r]=t}encode(e){const t=[];for(const r of e){const n=[...r];if(n.length>this.max_input_chars_per_word){t.push(this.unk_token);continue}let s=!1,a=0;const i=[];for(;a<n.length;){let c=n.length,u=null;for(;a<c;){let h=n.slice(a,c).join("");if(a>0&&(h=this.config.continuing_subword_prefix+h),this.tokens_to_ids.has(h)){u=h;break}--c}if(u===null){s=!0;break}i.push(u),a=c}s?t.push(this.unk_token):t.push(...i)}return t}},mg=yT,gg=class By{constructor(t,r){this.is_leaf=t,this.children=r}static default(){return new By(!1,new Map)}},vT=class{constructor(){this.root=gg.default()}extend(e){for(const t of e)this.push(t)}push(e){let t=this.root;for(const r of e){let n=t.children.get(r);n===void 0&&(n=gg.default(),t.children.set(r,n)),t=n}t.is_leaf=!0}*common_prefix_search(e){let t=this.root;if(t===void 0)return;let r="";for(const n of e){if(r+=n,t=t.children.get(n),t===void 0)return;t.is_leaf&&(yield r)}}},bT=vT,xf=class $y{constructor(t,r,n,s,a){this.token_id=t,this.node_id=r,this.pos=n,this.length=s,this.score=a,this.prev=null,this.backtrace_score=0}clone(){const t=new $y(this.token_id,this.node_id,this.pos,this.length,this.score);return t.prev=this.prev,t.backtrace_score=this.backtrace_score,t}},MT=class{constructor(e,t,r){this.chars=Array.from(e),this.len=this.chars.length,this.bos_token_id=t,this.eos_token_id=r,this.nodes=[],this.begin_nodes=Array.from({length:this.len+1},()=>[]),this.end_nodes=Array.from({length:this.len+1},()=>[]);const n=new xf(this.bos_token_id??0,0,0,0,0),s=new xf(this.eos_token_id??0,1,this.len,0,0);this.nodes.push(n.clone()),this.nodes.push(s.clone()),this.begin_nodes[this.len].push(s),this.end_nodes[0].push(n)}insert(e,t,r,n){const s=this.nodes.length,a=new xf(n,s,e,t,r);this.begin_nodes[e].push(a),this.end_nodes[e+t].push(a),this.nodes.push(a)}viterbi(){const e=this.len;let t=0;for(;t<=e;){if(this.begin_nodes[t].length==0)return[];for(let i of this.begin_nodes[t]){i.prev=null;let c=0,u=null;for(let h of this.end_nodes[t]){const p=h.backtrace_score+i.score;(u===null||p>c)&&(u=h.clone(),c=p)}if(u!==null)i.prev=u,i.backtrace_score=c;else return[]}++t}const r=[],s=this.begin_nodes[e][0].prev;if(s===null)return[];let a=s.clone();for(;a.prev!==null;)r.push(a.clone()),a=a.clone().prev.clone();return r.reverse(),r}piece(e){return this.chars.slice(e.pos,e.pos+e.length).join("")}tokens(){return this.viterbi().map(t=>this.piece(t))}token_ids(){return this.viterbi().map(t=>t.token_id)}},xT=MT;function TT(e){if(e.length===0)throw new Error("Array must not be empty");let t=e[0],r=0;for(let n=1;n<e.length;++n)e[n]<t&&(t=e[n],r=n);return[t,r]}var ET=class extends Sl{constructor(e,t){super(e);const r=e.vocab.length;this.vocab=new Array(r),this.scores=new Array(r);for(let n=0;n<r;++n)[this.vocab[n],this.scores[n]]=e.vocab[n];this.unk_token_id=e.unk_id,this.unk_token=this.vocab[e.unk_id],this.tokens_to_ids=new Map(this.vocab.map((n,s)=>[n,s])),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=TT(this.scores)[0],this.unk_score=this.min_score-10,this.scores[this.unk_token_id]=this.unk_score,this.trie=new bT,this.trie.extend(this.vocab),this.fuse_unk=!0}populate_nodes(e){const t=e.chars,r=1;let n=0;for(;n<t.length;){let s=!1;const a=t.slice(n).join(""),i=this.trie.common_prefix_search(a);for(const c of i){const u=this.tokens_to_ids.get(c),h=this.scores[u],p=mx(c);e.insert(n,p,h,u),!s&&p===r&&(s=!0)}s||e.insert(n,r,this.unk_score,this.unk_token_id),n+=r}}tokenize(e){const t=new xT(e,this.bos_token_id,this.eos_token_id);return this.populate_nodes(t),t.tokens()}encode(e){const t=[];for(const r of e){const n=this.tokenize(r);t.push(...n)}return t}},wg=ET,kT=class{constructor(e=(r,n)=>r>n,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(const t of e)if(this.size<this._max_size)this._heap.push(t),this._sift_up();else{const r=this._smallest();this._comparator(t,this._heap[r])&&(this._heap[r]=t,this._sift_up_from(r))}return this.size}pop(){const e=this.peek(),t=this.size-1;return t>0&&this._swap(0,t),this._heap.pop(),this._sift_down(),e}replace(e){const 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){const r=this._heap[e];this._heap[e]=this._heap[t],this._heap[t]=r}_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);){const 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}},CT=kT,AT=class{constructor(e){this.capacity=e,this.cache=new Map}get(e){if(!this.cache.has(e))return;const 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()}},ST=AT,PT=class extends Sl{constructor(e){super(e),this.tokens_to_ids=Hh(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[r,n]of this.tokens_to_ids)this.vocab[n]=r;const t=Array.isArray(e.merges[0]);this.merges=t?e.merges:e.merges.map(r=>r.split(" ",2)),this.bpe_ranks=new Map(this.merges.map((r,n)=>[JSON.stringify(r),n])),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 ST(this.cache_capacity)}clear_cache(){this.cache.clear()}bpe(e){if(e.length===0)return[];const t=this.cache.get(e);if(t!==void 0)return t;const r=Array.from(e);this.end_of_word_suffix&&(r[r.length-1]+=this.end_of_word_suffix);let n=[];if(r.length>1){const s=new CT((c,u)=>c.score<u.score);let a={token:r[0],bias:0,prev:null,next:null},i=a;for(let c=1;c<r.length;++c){const u={bias:c/r.length,token:r[c],prev:i,next:null};i.next=u,this.add_node(s,i),i=u}for(;!s.is_empty();){const c=s.pop();if(c.deleted||!c.next||c.next.deleted)continue;if(c.deleted=!0,c.next.deleted=!0,c.prev){const h={...c.prev};c.prev.deleted=!0,c.prev=h,h.prev?h.prev.next=h:a=h}const u={token:c.token+c.next.token,bias:c.bias,prev:c.prev,next:c.next.next};u.prev?(u.prev.next=u,this.add_node(s,u.prev)):a=u,u.next&&(u.next.prev=u,this.add_node(s,u))}for(let c=a;c!==null;c=c.next)n.push(c.token)}else n=r;if(this.continuing_subword_suffix)for(let s=0;s<n.length-1;++s)n[s]+=this.continuing_subword_suffix;return e.length<this.max_length_to_cache&&this.cache.put(e,n),n}add_node(e,t){const r=this.bpe_ranks.get(JSON.stringify([t.token,t.next.token]));r!==void 0&&(t.score=r+t.bias,e.push(t))}encode(e){const t=[];for(const r of e){if(this.ignore_merges&&this.tokens_to_ids.has(r)){t.push(r);continue}const n=this.bpe(r);for(const s of n)if(this.tokens_to_ids.has(s))t.push(s);else if(this.byte_fallback){const a=Array.from(this.text_encoder.encode(s)).map(i=>`<0x${i.toString(16).toUpperCase().padStart(2,"0")}>`);a.every(i=>this.tokens_to_ids.has(i))?t.push(...a):this.unk_token!=null&&t.push(this.unk_token)}else this.unk_token!=null&&t.push(this.unk_token)}return t}},yg=PT,FT=class extends Sl{constructor(e,t){super(e);const r=e.vocab;this.tokens_to_ids=Hh(t.target_lang?r[t.target_lang]:r),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=new Array(this.tokens_to_ids.size);for(const[n,s]of this.tokens_to_ids)this.vocab[s]=n}encode(e){return e}},IT=FT;function LT(e,t){switch(e.type){case"WordPiece":return new mg(e);case"Unigram":return new wg(e,t.eos_token);case"BPE":return new yg(e);default:if(e.vocab)return Array.isArray(e.vocab)?new wg(e,t.eos_token):Object.hasOwn(e,"continuing_subword_prefix")&&Object.hasOwn(e,"unk_token")?Object.hasOwn(e,"merges")?new yg(e):new mg(e):new IT(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 new Error(`Unknown TokenizerModel type: ${e?.type}`)}}var OT=LT,NT=class extends Mi{constructor(e){super(),this.config=e}_call(e,...t){return this.post_process(e,...t)}},xi=NT,BT=class extends xi{post_process(e,t=null,r=!0){const n=t===null?this.config.single:this.config.pair;let s=[],a=[];for(const i of n)"SpecialToken"in i?r&&(s.push(i.SpecialToken.id),a.push(i.SpecialToken.type_id)):"Sequence"in i&&(i.Sequence.id==="A"?(s=fr(s,e),a=fr(a,new Array(e.length).fill(i.Sequence.type_id))):i.Sequence.id==="B"&&(s=fr(s,t),a=fr(a,new Array(t.length).fill(i.Sequence.type_id))));return{tokens:s,token_type_ids:a}}},$T=BT,DT=class extends xi{post_process(e,t=null){return{tokens:e,tokens_pair:t}}},RT=DT,zT=class extends xi{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t=null,r=!0){r&&(e=fr([this.cls[0]],e,[this.sep[0]]));let n=new Array(e.length).fill(0);if(t){const s=[],a=r?[this.sep[0]]:[];e=fr(e,s,t,a),n=fr(n,new Array(t.length+s.length+a.length).fill(1))}return{tokens:e,token_type_ids:n}}},GT=zT,UT=class extends xi{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t,r=!0){r&&(e=fr([this.cls[0]],e,[this.sep[0]]));let n=new Array(e.length).fill(0);if(t){const s=r?[this.sep[0]]:[],a=r?[this.sep[0]]:[];e=fr(e,s,t,a),n=fr(n,new Array(t.length+s.length+a.length).fill(1))}return{tokens:e,token_type_ids:n}}},VT=UT,WT=class extends xi{constructor(e){super(e),this.processors=(e.processors??[]).map(t=>Dy(t))}post_process(e,t=null,r=!0){let n={tokens:e,tokens_pair:t};for(const s of this.processors)n=s.post_process(n.tokens,n.tokens_pair,r);return n}},jT=WT;function qT(e){if(e===null)return null;switch(e.type){case"TemplateProcessing":return new $T(e);case"ByteLevel":return new RT(e);case"BertProcessing":return new GT(e);case"RobertaProcessing":return new VT(e);case"Sequence":return new jT(e);default:throw new Error(`Unknown PostProcessor type: ${e.type}`)}}var Dy=qT,HT=class extends Mi{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:!1}_call(e){return this.decode(e)}decode(e){return this.decode_chain(e).join("")}},_r=HT,QT=class extends _r{constructor(e){super(e),this.byte_decoder=ux,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){const t=e.join(""),r=new Uint8Array([...t].map(n=>this.byte_decoder[n]));return this.text_decoder.decode(r)}decode_chain(e){const t=[];let r=[];for(const n of e)this.added_tokens.find(s=>s.content===n)!==void 0?(r.length>0&&(t.push(this.convert_tokens_to_string(r)),r=[]),t.push(n)):r.push(n);return r.length>0&&t.push(this.convert_tokens_to_string(r)),t}},YT=QT,XT=class extends _r{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map((t,r)=>{if(r!==0){const n=this.config.prefix;n&&t.startsWith(n)?t=t.replace(n,""):t=" "+t}return this.cleanup&&(t=qh(t)),t})}},JT=XT,KT=class extends _r{constructor(e){super(e),this.replacement=e.replacement??"▁"}decode_chain(e){const t=[];for(let r=0;r<e.length;++r){let n=e[r].replaceAll(this.replacement," ");r==0&&n.startsWith(" ")&&(n=n.substring(1)),t.push(n)}return t}},ZT=KT,e2=class extends _r{constructor(e){super(e),this.suffix=e.suffix??""}decode_chain(e){return e.map((t,r)=>t.replaceAll(this.suffix,r===e.length-1?"":" "))}},t2=e2,r2=class extends _r{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"";const t=[e[0]];for(let s=1;s<e.length;++s)e[s]!==t.at(-1)&&t.push(e[s]);let n=t.filter(s=>s!==this.pad_token).join("");return this.cleanup&&(n=qh(n).replaceAll(this.word_delimiter_token," ").trim()),n}decode_chain(e){return[this.convert_tokens_to_string(e)]}},n2=r2,s2=class extends _r{constructor(e){super(e),this.decoders=(e.decoders??[]).map(t=>Ry(t))}decode_chain(e){return this.decoders.reduce((t,r)=>r.decode_chain(t),e)}},a2=s2,o2=class extends _r{decode_chain(e){const t=Cl(this.config.pattern),r=this.config.content??"";return t===null?e:e.map(n=>n.replaceAll(t,r))}},i2=o2,l2=class extends _r{decode_chain(e){return[e.join("")]}},c2=l2,u2=class extends _r{constructor(e){super(e),this.content=e.content??"",this.start=e.start??0,this.stop=e.stop??0}decode_chain(e){return e.map(t=>{let r=0;for(let s=0;s<this.start&&t[s]===this.content;++s){r=s+1;continue}let n=t.length;for(let s=0;s<this.stop;++s){const a=t.length-s-1;if(t[a]===this.content){n=a;continue}else break}return t.slice(r,n)})}},d2=u2,f2=class extends _r{constructor(e){super(e),this.text_decoder=new TextDecoder}decode_chain(e){const t=[];let r=[];for(const n of e){let s=null;if(n.length===6&&n.startsWith("<0x")&&n.endsWith(">")){const a=parseInt(n.slice(3,5),16);isNaN(a)||(s=a)}if(s!==null)r.push(s);else{if(r.length>0){const a=this.text_decoder.decode(Uint8Array.from(r));t.push(a),r=[]}t.push(n)}}if(r.length>0){const n=this.text_decoder.decode(Uint8Array.from(r));t.push(n),r=[]}return t}},h2=f2;function p2(e){if(e===null)return null;switch(e.type){case"ByteLevel":return new YT(e);case"WordPiece":return new JT(e);case"Metaspace":return new ZT(e);case"BPEDecoder":return new t2(e);case"CTC":return new n2(e);case"Sequence":return new a2(e);case"Replace":return new i2(e);case"Fuse":return new c2(e);case"Strip":return new d2(e);case"ByteFallback":return new h2(e);default:throw new Error(`Unknown Decoder type: ${e.type}`)}}var Ry=p2,_2=class{constructor(e,t){const r=_g(e,"Tokenizer",["model","decoder","post_processor","pre_tokenizer","normalizer"]);if(r)throw new Error(r);const n=_g(t,"Config");if(n)throw new Error(n);this.tokenizer=e,this.config=t,this.normalizer=Oy(this.tokenizer.normalizer),this.pre_tokenizer=Ny(this.tokenizer.pre_tokenizer),this.model=OT(this.tokenizer.model,this.config),this.post_processor=Dy(this.tokenizer.post_processor),this.decoder=Ry(this.tokenizer.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];const s=[],a=[];this.added_tokens_map=new Map;for(const i of this.tokenizer.added_tokens){const c=new lx(i);if(this.added_tokens.push(c),this.model.tokens_to_ids.set(c.content,c.id),this.model.vocab[c.id]=c.content,c.special&&(this.special_tokens.push(c.content),this.all_special_ids.push(c.id)),this.added_tokens_map.set(c.content,c),c.normalized&&this.normalizer!==null){const u=this.normalizer(c.content);a.push(u),this.added_tokens_map.set(u,c)}else s.push(c.content)}(this.config.additional_special_tokens??[]).forEach(i=>{this.special_tokens.includes(i)||this.special_tokens.push(i)}),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 hg(s),this.splitter_normalized=new hg(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:r=!0,return_token_type_ids:n=null}={}){const{tokens:s,token_type_ids:a}=this.tokenize_helper(e,{text_pair:t,add_special_tokens:r}),i=s.map(u=>this.added_tokens_map.get(u)?.id??this.model.tokens_to_ids.get(u)??this.model.unk_token_id),c={ids:i,tokens:s,attention_mask:new Array(i.length).fill(1)};return n&&a&&(c.token_type_ids=a),c}decode(e,t={}){if(!Array.isArray(e)||e.length===0||!_x(e[0]))throw Error("token_ids must be a non-empty array of integers.");let r=e.map(s=>this.model.vocab[Number(s)]??this.model.unk_token);t.skip_special_tokens&&(r=r.filter(s=>!this.special_tokens.includes(s)));let n=this.decoder?this.decoder(r):r.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(n=n.replaceAll(this.decoder.end_of_word_suffix," "),t.skip_special_tokens&&(n=n.trim())),(t.clean_up_tokenization_spaces??this.clean_up_tokenization_spaces)&&(n=qh(n)),n}tokenize(e,{text_pair:t=null,add_special_tokens:r=!1}={}){return this.tokenize_helper(e,{text_pair:t,add_special_tokens:r}).tokens}encode_text(e){if(e===null)return null;const t=this.splitter_unnormalized.split(e);return t.forEach((r,n)=>{const s=this.added_tokens_map.get(r);s&&(s.lstrip&&n>0&&(t[n-1]=t[n-1].trimEnd()),s.rstrip&&n<t.length-1&&(t[n+1]=t[n+1].trimStart()))}),t.flatMap((r,n)=>{if(r.length===0)return[];if(this.added_tokens_map.has(r))return[r];if(this.remove_space===!0&&(r=r.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(r=gx(r)),this.normalizer!==null&&(r=this.normalizer(r)),r.length===0)return[];const s=this.splitter_normalized.split(r);return s.forEach((a,i)=>{const 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this._nearest_interpolate_4d||(this._nearest_interpolate_4d=Kr([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||(this._bilinear_interpolate_4d=Kr([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||(this._bicubic_interpolate_4d=Kr([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||(this._matmul=Kr([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||(this._stft=Kr([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||(this._rfft=Kr([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||(this._top_k=Kr([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||(this._slice=Kr([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}},jE=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"}),Ef=ve.IS_NODE_ENV?"cpu":"wasm";function rv(e,t,{warn:r}={}){return e?typeof 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t=="number")r="float32",n=Float32Array;else if(typeof t=="bigint")r="int64",n=BigInt64Array;else if(typeof t=="boolean")r="bool",n=Uint8Array;else throw new Error(`Unsupported data type: ${typeof t}`);return ep(e,t,r,n)}function dh(e,t){return At(e.dims,t)}function Ot(e){return ep(e,1n,"int64",BigInt64Array)}function iv(e){return Ot(e.dims)}function lv(e){return ep(e,0n,"int64",BigInt64Array)}function cv(e){return lv(e.dims)}function JE(e){const t=e.reduce((r,n)=>r*n,1);return new K("float32",Float32Array.from({length:t},()=>Qh.gauss()),e)}async function KE(e){if(!e)throw new Error("modelId is required for get_tokenizer_files");return(await Xh(e,"tokenizer_config.json",{})).exists?["tokenizer.json","tokenizer_config.json"]:[]}async function uv(e,t){const r=await KE(e);return await Promise.all(r.map(n=>jr(e,n,!0,t)))}function tp(e){const t=e.dims;switch(t.length){case 1:return e.tolist();case 2:if(t[0]!==1)throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return e.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${t.length}.`)}}var ZE=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function ek(e,t,r,n){for(const s of Object.keys(e)){const a=t-e[s].length,i=r(s),c=new Array(a).fill(i);e[s]=n==="right"?Tr(e[s],c):Tr(c,e[s])}}function tk(e,t){for(const r of Object.keys(e))e[r].length=t}function Gn(e,...t){for(const r of t){if(!Object.hasOwn(e,r))continue;const n=e[r];if(n)if(typeof n=="object"){if(n.__type==="AddedToken")return n.content;throw Error(`Unknown token: ${n}`)}else return n}return null}function rk(e){const t=[];for(const r of e.get_added_tokens_decoder().values())r.special&&t.push(r);return t}var pe=class extends Yt{return_token_type_ids=!1;padding_side="right";constructor(e,t){if(super(),this._tokenizerJSON=e,this._tokenizerConfig=t,this._tokenizer=new m2(e,t),this.config=t,this.padding_side=t.padding_side??this.padding_side,this.mask_token=Gn(t,"mask_token"),this.mask_token_id=this._tokenizer.token_to_id(this.mask_token),this.pad_token=Gn(t,"pad_token","eos_token"),this.pad_token_id=this._tokenizer.token_to_id(this.pad_token),this.sep_token=Gn(t,"sep_token"),this.sep_token_id=this._tokenizer.token_to_id(this.sep_token),this.unk_token=Gn(t,"unk_token"),this.unk_token_id=this._tokenizer.token_to_id(this.unk_token),this.bos_token=Gn(t,"bos_token"),this.bos_token_id=this._tokenizer.token_to_id(this.bos_token),this.eos_token=Gn(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)){const n=Object.create(null);for(const{name:s,template:a}of this.chat_template){if(typeof s!="string"||typeof a!="string")throw new Error('Chat template must be a list of objects with "name" and "template" properties');n[s]=a}this.chat_template=n}this._compiled_template_cache=new Map;const r=rk(this._tokenizer);this.all_special_ids=r.map(n=>n.id),this.all_special_tokens=r.map(n=>n.content)}static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:n=null,local_files_only:s=!1,revision:a="main"}={}){const i=await uv(e,{progress_callback:t,config:r,cache_dir:n,local_files_only:s,revision:a});return new this(...i)}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(t=>this._tokenizer.token_to_id(t))}_call(e,t={}){const{text_pair:r=null,add_special_tokens:n=!0,padding:s=!1,return_token_type_ids:a=null}=t;let{truncation:i=null,max_length:c=null}=t;const u=t.return_tensor??!0,h=Array.isArray(e);let p;if(h){if(e.length===0)throw Error("text array must be non-empty");if(r!==null){if(Array.isArray(r)){if(e.length!==r.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");p=e.map((m,w)=>this._encode_plus(m,{text_pair:r[w],add_special_tokens:n,return_token_type_ids:a}))}else p=e.map(m=>this._encode_plus(m,{add_special_tokens:n,return_token_type_ids:a}))}else{if(e==null)throw Error("text may not be null or undefined");if(Array.isArray(r))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");p=[this._encode_plus(e,{text_pair:r,add_special_tokens:n,return_token_type_ids:a})]}if(c===null?c=this.model_max_length:i===null&&(s===!0?(be.warn("`max_length` is ignored when `padding: true` and there is no truncation strategy. To pad to max length, use `padding: 'max_length'`."),c=this.model_max_length):s===!1&&(be.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."),i=!0)),s===!0&&(c=Math.min(pt(p.map(m=>m.input_ids.length))[0],c??1/0)),c=Math.min(c,this.model_max_length??1/0),s||i)for(let m=0;m<p.length;++m)p[m].input_ids.length!==c&&(p[m].input_ids.length>c?i&&tk(p[m],c):s&&ek(p[m],c,w=>w==="input_ids"?this.pad_token_id:0,this.padding_side));const _={};if(u){if(!(s&&i)&&p.some(w=>{for(const b of Object.keys(w))if(w[b].length!==p[0][b]?.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.");const m=[p.length,p[0].input_ids.length];for(const w of Object.keys(p[0]))_[w]=new K("int64",BigInt64Array.from(p.flatMap(b=>b[w]).map(BigInt)),m)}else{for(const m of Object.keys(p[0]))_[m]=p.map(w=>w[m]);if(!h)for(const m of Object.keys(_))_[m]=_[m][0]}return _}_encode_text(e){return e===null?null:this._tokenizer.encode(e).tokens}_encode_plus(e,{text_pair:t=null,add_special_tokens:r=!0,return_token_type_ids:n=null}={}){const{ids:s,attention_mask:a,token_type_ids:i}=this._tokenizer.encode(e,{text_pair:t,add_special_tokens:r,return_token_type_ids:n??this.return_token_type_ids});return{input_ids:s,attention_mask:a,...i?{token_type_ids:i}:{}}}tokenize(e,{pair:t=null,add_special_tokens:r=!1}={}){return this._tokenizer.tokenize(e,{text_pair:t,add_special_tokens:r})}encode(e,{text_pair:t=null,add_special_tokens:r=!0,return_token_type_ids:n=null}={}){return this._tokenizer.encode(e,{text_pair:t,add_special_tokens:r,return_token_type_ids:n}).ids}batch_decode(e,t={}){return e instanceof K&&(e=e.tolist()),e.map(r=>this.decode(r,t))}decode(e,t={}){if(e instanceof K&&(e=tp(e)),!Array.isArray(e)||e.length===0||!sx(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:r=null}){return this._tokenizer.decode(e,{skip_special_tokens:t,clean_up_tokenization_spaces:r})}get_chat_template({chat_template:e=null,tools:t=null}={}){if(this.chat_template&&typeof this.chat_template=="object"){const r=this.chat_template;if(e!==null&&Object.hasOwn(r,e))e=r[e];else if(e===null)if(t!==null&&"tool_use"in r)e=r.tool_use;else if("default"in r)e=r.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(r).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:r=null,documents:n=null,chat_template:s=null,add_generation_prompt:a=!1,tokenize:i=!0,padding:c=!1,truncation:u=!1,max_length:h=null,return_tensor:p=!0,return_dict:_=!0,tokenizer_kwargs:m={},...w}=t;if(s=this.get_chat_template({chat_template:s,tools:r}),typeof s!="string")throw Error(`chat_template must be a string, but got ${typeof s}`);let b=this._compiled_template_cache.get(s);b===void 0&&(b=new dE(s),this._compiled_template_cache.set(s,b));const M=Object.create(null);for(const T of ZE){const C=Gn(this.config,T);C&&(M[T]=C)}const E=b.render({messages:e,add_generation_prompt:a,tools:r,documents:n,...M,...w});if(i){const T=this._call(E,{add_special_tokens:!1,padding:c,truncation:u,max_length:h,return_tensor:p,...m});return _?T:T.input_ids}return E}};function rp(e,t,r,n){if(!("language_codes"in e)||!Array.isArray(e.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in e)||!(e.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in e)||typeof e.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const s=n.src_lang,a=n.tgt_lang;if(!e.language_codes.includes(a))throw new Error(`Target language code "${a}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);if(s!==void 0){if(!e.language_codes.includes(s))throw new Error(`Source language code "${s}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);for(const i of e._tokenizer.post_processor.config.single)if("SpecialToken"in i&&e.languageRegex.test(i.SpecialToken.id)){i.SpecialToken.id=e.lang_to_token(s);break}}return n.forced_bos_token_id=e._tokenizer.token_to_id(e.lang_to_token(a)),e._call(t,r)}var dv={};Ss(dv,{AlbertTokenizer:()=>nk,AutoTokenizer:()=>Oe,BartTokenizer:()=>sk,BertTokenizer:()=>ak,BlenderbotSmallTokenizer:()=>ok,BlenderbotTokenizer:()=>ik,BloomTokenizer:()=>lk,CLIPTokenizer:()=>uk,CamembertTokenizer:()=>ck,CodeGenTokenizer:()=>fk,CodeLlamaTokenizer:()=>dk,CohereAsrTokenizer:()=>pk,CohereTokenizer:()=>hk,ConvBertTokenizer:()=>_k,DebertaTokenizer:()=>gk,DebertaV2Tokenizer:()=>mk,DistilBertTokenizer:()=>wk,ElectraTokenizer:()=>yk,EsmTokenizer:()=>vk,FalconTokenizer:()=>bk,GPT2Tokenizer:()=>Tk,GPTNeoXTokenizer:()=>xk,GemmaTokenizer:()=>Mk,HerbertTokenizer:()=>Ek,LlamaTokenizer:()=>kk,M2M100Tokenizer:()=>Ck,MBart50Tokenizer:()=>Sk,MBartTokenizer:()=>fv,MPNetTokenizer:()=>Ik,MarianTokenizer:()=>Ak,MgpstrTokenizer:()=>Pk,MobileBertTokenizer:()=>Fk,NllbTokenizer:()=>Lk,NougatTokenizer:()=>Ok,PreTrainedTokenizer:()=>pe,Qwen2Tokenizer:()=>Nk,RoFormerTokenizer:()=>$k,RobertaTokenizer:()=>Bk,SiglipTokenizer:()=>Dk,SpeechT5Tokenizer:()=>Rk,SqueezeBertTokenizer:()=>zk,T5Tokenizer:()=>Gk,TokenizersBackend:()=>pe,VitsTokenizer:()=>Vk,Wav2Vec2CTCTokenizer:()=>Wk,WhisperTokenizer:()=>Yk,XLMRobertaTokenizer:()=>Xk,XLMTokenizer:()=>Jk});var nk=class extends pe{return_token_type_ids=!0},sk=class extends pe{},ak=class extends pe{return_token_type_ids=!0},ok=class extends pe{},ik=class extends pe{},lk=class extends pe{},ck=class extends pe{},uk=class extends pe{},dk=class extends pe{},fk=class extends pe{},hk=class extends pe{},pk=class extends pe{},_k=class extends pe{return_token_type_ids=!0},mk=class extends pe{return_token_type_ids=!0},gk=class extends pe{return_token_type_ids=!0},wk=class extends pe{},yk=class extends pe{return_token_type_ids=!0},vk=class extends pe{},bk=class extends pe{},Mk=class extends pe{},xk=class extends pe{},Tk=class extends pe{},Ek=class extends pe{return_token_type_ids=!0},kk=class extends pe{padding_side="left"},Ck=class extends pe{constructor(e,t){super(e,t),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)).map(r=>r.slice(2,-2)),this.lang_to_token=r=>`__${r}__`}_build_translation_inputs(e,t,r){return rp(this,e,t,r)}},Ak=class extends pe{constructor(e,t){super(e,t),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=Array.from(this.get_vocab().keys()).filter(r=>this.languageRegex.test(r)),be.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(e){if(e===null)return null;const[t,...r]=e.trim().split(this.languageRegex);if(r.length===0)return super._encode_text(t);if(r.length===2){const[n,s]=r;return this.supported_language_codes.includes(n)||be.warn(`Unsupported language code "${n}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),Tr([n],super._encode_text(s))}}},fv=class extends pe{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)).map(r=>r),this.lang_to_token=r=>r}_build_translation_inputs(e,t,r){return rp(this,e,t,r)}},Sk=class extends fv{},Pk=class extends pe{},Fk=class extends pe{return_token_type_ids=!0},Ik=class extends pe{},Lk=class extends pe{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)),this.lang_to_token=r=>r}_build_translation_inputs(e,t,r){return rp(this,e,t,r)}},Ok=class extends pe{},Nk=class extends pe{},Bk=class extends pe{},$k=class extends pe{return_token_type_ids=!0},Dk=class extends pe{},Rk=class extends pe{},zk=class extends pe{return_token_type_ids=!0},Gk=class extends pe{},Uk=class extends _r{decode_chain(e){let t="";for(let r=1;r<e.length;r+=2)t+=e[r];return[t]}},Vk=class extends pe{constructor(e,t){super(e,t),this._tokenizer.decoder=new Uk({type:"VitsDecoder"})}},Wk=class extends pe{},hv=[["en","english"],["zh","chinese"],["de","german"],["es","spanish"],["ru","russian"],["ko","korean"],["fr","french"],["ja","japanese"],["pt","portuguese"],["tr","turkish"],["pl","polish"],["ca","catalan"],["nl","dutch"],["ar","arabic"],["sv","swedish"],["it","italian"],["id","indonesian"],["hi","hindi"],["fi","finnish"],["vi","vietnamese"],["he","hebrew"],["uk","ukrainian"],["el","greek"],["ms","malay"],["cs","czech"],["ro","romanian"],["da","danish"],["hu","hungarian"],["ta","tamil"],["no","norwegian"],["th","thai"],["ur","urdu"],["hr","croatian"],["bg","bulgarian"],["lt","lithuanian"],["la","latin"],["mi","maori"],["ml","malayalam"],["cy","welsh"],["sk","slovak"],["te","telugu"],["fa","persian"],["lv","latvian"],["bn","bengali"],["sr","serbian"],["az","azerbaijani"],["sl","slovenian"],["kn","kannada"],["et","estonian"],["mk","macedonian"],["br","breton"],["eu","basque"],["is","icelandic"],["hy","armenian"],["ne","nepali"],["mn","mongolian"],["bs","bosnian"],["kk","kazakh"],["sq","albanian"],["sw","swahili"],["gl","galician"],["mr","marathi"],["pa","punjabi"],["si","sinhala"],["km","khmer"],["sn","shona"],["yo","yoruba"],["so","somali"],["af","afrikaans"],["oc","occitan"],["ka","georgian"],["be","belarusian"],["tg","tajik"],["sd","sindhi"],["gu","gujarati"],["am","amharic"],["yi","yiddish"],["lo","lao"],["uz","uzbek"],["fo","faroese"],["ht","haitian creole"],["ps","pashto"],["tk","turkmen"],["nn","nynorsk"],["mt","maltese"],["sa","sanskrit"],["lb","luxembourgish"],["my","myanmar"],["bo","tibetan"],["tl","tagalog"],["mg","malagasy"],["as","assamese"],["tt","tatar"],["haw","hawaiian"],["ln","lingala"],["ha","hausa"],["ba","bashkir"],["jw","javanese"],["su","sundanese"]],sl=new Map(hv),jk=new Map([...hv.map(([e,t])=>[t,e]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);function qk(e){e=e.toLowerCase();let t=jk.get(e);if(t===void 0){const r=e.match(/^<\|([a-z]{2})\|>$/);if(r&&(e=r[1]),sl.has(e))t=e;else{const s=e.length===2?sl.keys():sl.values();throw new Error(`Language "${e}" is not supported. Must be one of: ${JSON.stringify(Array.from(s))}`)}}return t}var Hk="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",Vg=new RegExp(`^[${Hk}]+$`,"gu"),Qk=.1,Yk=class extends pe{get timestamp_begin(){return this._tokenizer.token_to_id("<|notimestamps|>")+1}_decode_asr(e,{return_timestamps:t=!1,return_language:r=!1,time_precision:n=null,force_full_sequences:s=!0}={}){if(n===null)throw Error("Must specify time_precision");let a=null;const i=t==="word";function c(){return{language:a,timestamp:[null,null],text:""}}const u=[];let h=c(),p=0;const _=this.timestamp_begin,w=_+1500;let b=[],M=[],E=!1,T=null;const C=new Set(this.all_special_ids);for(const F of e){const G=F.tokens,v=i?F.token_timestamps:null;let j=null,U=_;if("stride"in F){const[H,I,S]=F.stride;if(p-=I,T=H-S,I&&(U=I/n+_),S)for(let D=G.length-1;D>=0;--D){const Y=Number(G[D]);if(Y>=_){if(j!==null&&(Y-_)*n<T)break;j=Y}}}let q=[],ne=[];for(let H=0;H<G.length;++H){const I=Number(G[H]);if(C.has(I)){const S=this.decode([I]),D=sl.get(S.slice(2,-2));if(D!==void 0){if(a!==null&&D!==a&&!t){b.push(q);const Y=this.findLongestCommonSequence(b)[0],se=this.decode(Y);h.text=se,u.push(h),b=[],q=[],h=c()}a=h.language=D}}else if(I>=_&&I<=w){const S=(I-_)*n+p,D=Vi(S,2);if(j!==null&&I>=j)E=!0;else if(E||b.length>0&&I<U)E=!1;else if(h.timestamp[0]===null)h.timestamp[0]=D;else if(D!==h.timestamp[0]){h.timestamp[1]=D,b.push(q),i&&M.push(ne);const[Y,se]=this.findLongestCommonSequence(b,M),N=this.decode(Y);if(h.text=N,i&&(h.words=this.collateWordTimestamps(Y,se,a),h.words.length>0&&h.timestamp[1]!==null))for(const $ of h.words)$.timestamp[1]>h.timestamp[1]&&h.timestamp[1]>=$.timestamp[0]&&($.timestamp[1]=h.timestamp[1]);u.push(h),b=[],q=[],M=[],ne=[],h=c()}}else if(q.push(I),i){let S=Vi(v[H]+p,2),D;if(H+1<v.length){D=Vi(v[H+1]+p,2);const Y=this.decode([I]);Vg.test(Y)&&(D=Vi(Math.min(S+n,D),2))}else D=null;ne.push([S,D])}}if("stride"in F){const[H,I,S]=F.stride;p+=H-S}q.length>0?(b.push(q),i&&M.push(ne)):b.every(H=>H.length===0)&&(h=c(),b=[],q=[],M=[],ne=[])}if(b.length>0){if(s&&t)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[F,G]=this.findLongestCommonSequence(b,M),v=this.decode(F);h.text=v,i&&(h.words=this.collateWordTimestamps(F,G,a)),u.push(h)}let P=Object.create(null);const A=u.map(F=>F.text).join("");if(t||r){for(let F=0;F<u.length;++F){const G=u[F];t||delete G.timestamp,r||delete G.language}if(i){const F=[];for(const G of u)for(const v of G.words)F.push(v);P={chunks:F}}else P={chunks:u}}return[A,P]}findLongestCommonSequence(e,t=null){let r=e[0],n=r.length,s=[];const a=Array.isArray(t)&&t.length>0;let i=a?[]:null,c=a?t[0]:null;for(let u=1;u<e.length;++u){const h=e[u];let p=0,_=[n,n,0,0];const m=h.length;for(let P=1;P<n+m;++P){const A=Math.max(0,n-P),F=Math.min(n,n+m-P),G=r.slice(A,F),v=Math.max(0,P-n),j=Math.min(m,P),U=h.slice(v,j);if(G.length!==U.length)throw new Error("There is a bug within whisper `decode_asr` function, please report it. Dropping to prevent bad inference.");let q;a?q=G.filter((I,S)=>I===U[S]&&c[A+S][0]-Qk<=t[u][v+S][0]).length:q=G.filter((I,S)=>I===U[S]).length;const ne=P/1e4,H=q/P+ne;q>1&&H>p&&(p=H,_=[A,F,v,j])}const[w,b,M,E]=_,T=Math.floor((b+w)/2);let C=Math.floor((E+M)/2);if(a&&p===0&&n>0){const P=c[n-1][0],A=t[u].findIndex(F=>F[0]>=P);C=A===-1?h.length:A}s.push(...r.slice(0,T)),r=h.slice(C),n=r.length,a&&(i.push(...c.slice(0,T)),c=t[u].slice(C))}return s.push(...r),a?(i.push(...c),[s,i]):[s,[]]}collateWordTimestamps(e,t,r){const[n,s,a]=this.combineTokensIntoWords(e,r),i=[];for(let c=0;c<n.length;++c){const u=a[c];i.push({text:n[c],timestamp:[t[u.at(0)][0],t[u.at(-1)][1]]})}return i}combineTokensIntoWords(e,t,r=`"'“¡¿([{-`,n=`"'.。,，!！?？:：”)]}、`){t=t??"english";let s,a,i;return["chinese","japanese","thai","lao","myanmar"].includes(t)?[s,a,i]=this.splitTokensOnUnicode(e):[s,a,i]=this.splitTokensOnSpaces(e),this.mergePunctuations(s,a,i,r,n)}decode(e,t){let r;return t?.decode_with_timestamps?(e instanceof K&&(e=tp(e)),r=this.decodeWithTimestamps(e,t)):r=super.decode(e,t),r}decodeWithTimestamps(e,t){const r=t?.time_precision??.02,n=this.all_special_ids.at(-1)+1;let s=[[]];for(let a of e)if(a=Number(a),a>=n){const i=((a-n)*r).toFixed(2);s.push(`<|${i}|>`),s.push([])}else s[s.length-1].push(a);return s=s.map(a=>typeof a=="string"?a:super.decode(a,t)),s.join("")}splitTokensOnUnicode(e){const t=this.decode(e,{decode_with_timestamps:!0}),r="�",n=[],s=[],a=[];let i=[],c=[],u=0;for(let h=0;h<e.length;++h){const p=e[h];i.push(p),c.push(h);const _=this.decode(i,{decode_with_timestamps:!0});(!_.includes(r)||t[u+_.indexOf(r)]===r)&&(n.push(_),s.push(i),a.push(c),i=[],c=[],u+=_.length)}return[n,s,a]}splitTokensOnSpaces(e){const[t,r,n]=this.splitTokensOnUnicode(e),s=[],a=[],i=[];for(let c=0;c<t.length;++c){const u=t[c],h=r[c],p=n[c],_=h[0]>=this._tokenizer.token_to_id("<|endoftext|>"),m=u.startsWith(" "),w=u.trim(),b=Vg.test(w);if(_||m||b||s.length===0)s.push(u),a.push(h),i.push(p);else{const M=s.length-1;s[M]+=u,a[M].push(...h),i[M].push(...p)}}return[s,a,i]}mergePunctuations(e,t,r,n,s){const a=structuredClone(e),i=structuredClone(t),c=structuredClone(r);let u=a.length-2,h=a.length-1;for(;u>=0;)a[u].startsWith(" ")&&n.includes(a[u].trim())?(a[h]=a[u]+a[h],i[h]=Tr(i[u],i[h]),c[h]=Tr(c[u],c[h]),a[u]="",i[u]=[],c[u]=[]):h=u,--u;for(u=0,h=1;h<a.length;)!a[u].endsWith(" ")&&s.includes(a[h])?(a[u]+=a[h],i[u]=Tr(i[u],i[h]),c[u]=Tr(c[u],c[h]),a[h]="",i[h]=[],c[h]=[]):u=h,++h;return[a.filter(p=>p),i.filter(p=>p.length>0),c.filter(p=>p.length>0)]}},Xk=class extends pe{},Jk=class extends pe{return_token_type_ids=!0;constructor(e,t){super(e,t),be.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}},Oe=class{static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:n=null,local_files_only:s=!1,revision:a="main"}={}){const[i,c]=await uv(e,{progress_callback:t,config:r,cache_dir:n,local_files_only:s,revision:a}),u=c.tokenizer_class?.replace(/Fast$/,"")??"PreTrainedTokenizer";let h=dv[u];return h||(be.warn(`Unknown tokenizer class "${u}", attempting to construct from base class.`),h=pe),new h(i,c)}},Fl="https://github.com/huggingface/transformers.js/issues/new/choose",np="preprocessor_config.json",pv=np,_v="processor_config.json",mv="chat_template.jinja",De=class extends Yt{static classes=["image_processor_class","tokenizer_class","feature_extractor_class"];static uses_processor_config=!1;static uses_chat_template_file=!1;constructor(e,t,r){super(),this.config=e,this.components=t,this.chat_template=r}get image_processor(){return this.components.image_processor}get tokenizer(){return this.components.tokenizer}get feature_extractor(){return this.components.feature_extractor}apply_chat_template(e,t={}){if(!this.tokenizer)throw new Error("Unable to apply chat template without a tokenizer.");return this.tokenizer.apply_chat_template(e,{tokenize:!1,chat_template:this.chat_template??void 0,...t})}batch_decode(...e){if(!this.tokenizer)throw new Error("Unable to decode without a tokenizer.");return this.tokenizer.batch_decode(...e)}decode(...e){if(!this.tokenizer)throw new Error("Unable to decode without a tokenizer.");return this.tokenizer.decode(...e)}async _call(e,...t){for(const r of[this.image_processor,this.feature_extractor,this.tokenizer])if(r)return r(e,...t);throw new Error("No image processor, feature extractor, or tokenizer found.")}static async from_pretrained(e,t={}){const[r,n,s]=await Promise.all([this.uses_processor_config?jr(e,_v,!0,t):{},Promise.all(this.classes.filter(a=>a in this).map(async a=>{const i=await this[a].from_pretrained(e,t);return[a.replace(/_class$/,""),i]})).then(Object.fromEntries),this.uses_chat_template_file?Jh(e,mv,!0,t):null]);return new this(r,n,s)}},Kk={};Ss(Kk,{ChatterboxProcessor:()=>TC,CohereAsrProcessor:()=>kC,Florence2Processor:()=>CA,Gemma3Processor:()=>AA,Gemma3nProcessor:()=>SA,Gemma4Processor:()=>PA,Glm46VProcessor:()=>FA,GraniteSpeechProcessor:()=>IA,GroundingDinoProcessor:()=>OA,Idefics3Processor:()=>Xg,JinaCLIPProcessor:()=>RA,Lfm2VlProcessor:()=>zA,LlavaProcessor:()=>GA,MgpstrProcessor:()=>UA,MoonshineProcessor:()=>VA,OwlViTProcessor:()=>WA,PaliGemmaProcessor:()=>qA,Phi3VProcessor:()=>QA,PixtralProcessor:()=>YA,Processor:()=>De,PyAnnoteProcessor:()=>XA,Qwen2VLProcessor:()=>lp,Qwen2_5_VLProcessor:()=>Qv,Qwen3VLProcessor:()=>JA,Sam2Processor:()=>Xv,Sam2VideoProcessor:()=>KA,SamProcessor:()=>Yv,SmolVLMProcessor:()=>Xg,SpeechT5Processor:()=>ZA,UltravoxProcessor:()=>eS,VLChatProcessor:()=>DA,VoxtralProcessor:()=>sS,VoxtralRealtimeProcessor:()=>iS,Wav2Vec2Processor:()=>lS,Wav2Vec2ProcessorWithLM:()=>cS,WhisperProcessor:()=>uS});var St=class extends Yt{constructor(e){super(),this.config=e}static async from_pretrained(e,t={}){const r=await jr(e,np,!0,t);return new this(r)}};function Et(e,t){if(!(e instanceof Float32Array||e instanceof Float64Array))throw new Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${e?.constructor?.name??typeof e} instead. 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Mel spectrogram computation is not yet supported for complex-valued spectrogram. Specify `power` to fix this issue.");if(!p)throw new Error("`preemphasis_htk_flavor=false` is not currently supported.");if(i){const Q=Math.floor(r/2);switch(c){case"reflect":{e=iC(e,Q,Q);break}case"constant":{const _e=new e.constructor(e.length+2*Q);_e.set(e,Q),e=_e;break}case"semicausal":{const _e=new e.constructor(e.length+Q);_e.set(e,Q),e=_e;break}default:throw new Error(`pad_mode="${c}" not implemented yet.`)}}let q=Math.floor(1+Math.floor((e.length-r)/n));P!==null&&q<P&&(q=P);const ne=u?Math.floor(s/2)+1:s;let H=q,I=q;A!==null&&(A>q?F&&(I=A):I=H=A);const S=new IE(s),D=new Float64Array(s),Y=new Float64Array(S.outputBufferSize),se=new Float32Array(ne*I);for(let Q=0;Q<H;++Q){const _e=Q*n,me=Math.min(e.length-_e,r);me!==r&&D.fill(0,0,r);for(let de=0;de<me;++de)D[de]=e[_e+de];if(C){let de=0;for(let ye=0;ye<me;++ye)de+=D[ye];const nt=de/me;for(let ye=0;ye<me;++ye)D[ye]-=nt}if(h!==null){for(let de=me-1;de>=1;--de)D[de]-=h*D[de-1];D[0]*=1-h}for(let de=0;de<t.length;++de)D[de]*=t[de];S.realTransform(Y,D);for(let de=0;de<ne;++de){const nt=de<<1;se[de*I+Q]=Y[nt]**2+Y[nt+1]**2}}if(a!==null&&a!==2){const Q=a/2;for(let _e=0;_e<se.length;++_e)se[_e]**=Q}const N=_.length;let $=await YE(new K("float32",_.flat(),[N,ne]),new K("float32",se,[ne,I]));G&&($=$.transpose(1,0));const z=$.data;if(j==="add")for(let Q=0;Q<z.length;++Q)z[Q]=v+z[Q]+m;else for(let Q=0;Q<z.length;++Q)z[Q]=v+Math.max(m,z[Q]);if(a!==null&&w!==null){const Q=Math.min(z.length,H*N);switch(w){case"log":for(let _e=0;_e<Q;++_e)z[_e]=Math.log(z[_e]);break;case"log10":for(let _e=0;_e<Q;++_e)z[_e]=Math.log10(z[_e]);break;case"log10_max_norm":{for(let de=0;de<Q;++de)z[de]=Math.log10(z[de]);const me=(b??pt(z)[0])-8;for(let de=0;de<Q;++de)z[de]=(Math.max(z[de],me)+4)/4;break}case"dB":if(a===1)lC(z,M,E,T);else if(a===2)cC(z,M,E,T);else throw new Error(`Cannot use log_mel option '${w}' with power ${a}`);break;default:throw new Error(`log_mel must be one of null, 'log', 'log10', 'log10_max_norm', or 'dB'. Got '${w}'`)}}return $}function qr(e,t,{periodic:r=!0,frame_length:n=null,center:s=!0}={}){const a=r?e+1:e;let i;switch(t){case"boxcar":i=new Float64Array(a).fill(1);break;case"hann":case"hann_window":i=Wg(a);break;case"hamming":i=rC(a);break;case"povey":i=Wg(a).map(h=>Math.pow(h,.85));break;default:throw new Error(`Unknown window type ${t}.`)}if(r&&(i=i.subarray(0,e)),n===null||e===n)return i;if(e>n)throw new Error(`Length of the window (${e}) may not be larger than frame_length (${n})`);const c=new Float64Array(n),u=s?Math.floor((n-e)/2):0;return c.set(i,u),c}var uC=class extends St{constructor(e){super(e);const t=this.config.sampling_rate,r=kr(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=qr(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(e,t){return Ar(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){Et(e,"ASTFeatureExtractor");const t=await this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){const r=this.std*2,n=t.data;for(let s=0;s<n.length;++s)n[s]=(n[s]-this.mean)/r}return{input_values:t.unsqueeze_(0)}}},vv=class extends St{async _call(e){Et(e,"EncodecFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const t=this.config.feature_size;if(e.length%t!==0)throw new Error(`The length of the audio data must be a multiple of the number of channels (${t}).`);const r=[1,t,e.length/t];return{input_values:new K("float32",e,r)}}},dC=class extends St{async _call(e){Et(e,"ChatterboxFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const t=[1,e.length];return{input_values:new K("float32",e,t)}}},fC=class extends St{constructor(e){super(e),this.mel_filters=kr(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=kr(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=qr(this.config.fft_window_size,"hann")}async _get_input_mel(e,t,r,n){let s;const a=e.length-t;if(a>0)if(r==="rand_trunc"){const i=Math.floor(Qh.random()*(a+1));e=e.subarray(i,i+t),s=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${r}" not implemented`);else{if(a<0){let i=new Float64Array(t);if(i.set(e),n==="repeat")for(let c=e.length;c<t;c+=e.length)i.set(e.subarray(0,Math.min(e.length,t-c)),c);else if(n==="repeatpad")for(let c=e.length;c<-a;c+=e.length)i.set(e,c);e=i}if(r==="fusion")throw new Error(`Truncation strategy "${r}" not implemented`);s=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}return s.unsqueeze_(0)}async _extract_fbank_features(e,t,r=null){return Ar(e,this.window,this.config.fft_window_size,this.config.hop_length,{power:2,mel_filters:t,log_mel:"dB",max_num_frames:r,do_pad:!1,transpose:!0})}async _call(e,{max_length:t=null}={}){return Et(e,"ClapFeatureExtractor"),{input_features:(await this._get_input_mel(e,t??this.config.nb_max_samples,this.config.truncation,this.config.padding)).unsqueeze_(0)}}},hC=1e-5,bv=class extends St{constructor(e){super(e),this.config.mel_filters??=kr(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,this.config.sampling_rate/2,this.config.sampling_rate,"slaney","slaney");const t=qr(this.config.win_length,"hann",{periodic:!1});this.window=new Float64Array(this.config.n_fft);const r=Math.floor((this.config.n_fft-this.config.win_length)/2);this.window.set(t,r)}async _extract_fbank_features(e){const 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 Ar(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){Et(e,"ParakeetFeatureExtractor");const t=await this._extract_fbank_features(e),r=Math.floor((e.length+Math.floor(this.config.n_fft/2)*2-this.config.n_fft)/this.config.hop_length),n=t.data;n.fill(0,r*t.dims[1]);const[s,a]=t.dims,i=new Float64Array(a),c=new Float64Array(a);for(let p=0;p<r;++p){const _=p*a;for(let m=0;m<a;++m){const w=n[_+m];i[m]+=w,c[m]+=w*w}}const u=r>1?r-1:1;for(let p=0;p<a;++p){const _=i[p]/r,m=(c[p]-r*_*_)/u,b=1/(Math.sqrt(m)+hC);for(let M=0;M<r;++M){const E=M*a+p;n[E]=(n[E]-_)*b}}const h=new BigInt64Array(s);return h.fill(1n,0,r),{input_features:t.unsqueeze_(0),attention_mask:new K("int64",h,[1,s])}}},pC=class extends bv{_apply_dither(e){const t=this.config.dither??0;if(t<=0)return e;const r=new Pl(e.length);for(let n=0;n<e.length;++n)e[n]+=t*r.gauss();return e}split_audio(e){const t=this.config.max_audio_clip_s??35,r=this.config.overlap_chunk_second??5,n=this.config.min_energy_window_samples??1600,s=this.config.sampling_rate,a=Math.max(1,Math.round(t*s)),i=Math.max(1,Math.round(r*s));if(e.length<=a)return[e];const c=[];let u=0;const h=e.length;for(;u<h;){if(u+a>=h){c.push(e.slice(u,h));break}const p=Math.max(u,u+a-i),_=Math.min(u+a,h);let m;_<=p?m=u+a:m=this._find_split_point_energy(e,p,_,n),m=Math.max(u+1,Math.min(m,h)),c.push(e.slice(u,m)),u=m}return c}_find_split_point_energy(e,t,r,n){const s=r-t;if(s<=n)return Math.floor((t+r)/2);let a=1/0,i=t;const c=s-n;for(let u=0;u<=c;u+=n){let h=0;for(let p=0;p<n;++p){const _=e[t+u+p];h+=_*_}h=Math.sqrt(h/n),h<a&&(a=h,i=t+u)}return i}async _call(e){Et(e,"CohereAsrFeatureExtractor");const t=new Float64Array(e);return this._apply_dither(t),super._call(t)}},Mv=class extends vv{},xv=class extends St{constructor(e){super(e);const{fft_length:t,feature_size:r,min_frequency:n,max_frequency:s,sampling_rate:a,frame_length:i}=this.config,c=kr(Math.floor(1+t/2),r,n,s,a,null,"htk",!1);this.mel_filters=c,this.window=qr(i,"hann")}async _extract_fbank_features(e,t){return Ar(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:r=!0,padding:n=!0,pad_to_multiple_of:s=128}={}){if(Et(e,"Gemma3nAudioFeatureExtractor"),r&&e.length>t&&(e=e.slice(0,t)),n&&e.length%s!==0){const c=s-e.length%s,u=new Float64Array(e.length+c);u.set(e),this.config.padding_value!==0&&u.fill(this.config.padding_value,e.length),e=u}const a=await this._extract_fbank_features(e,this.config.max_length),i=At([1,a.dims[0]],!0);return{input_features:a.unsqueeze_(0),input_features_mask:i}}},Tv=class extends xv{async _extract_fbank_features(e,t){const{frame_length:r,hop_length:n,fft_length:s}=this.config,a=Math.floor(r/2),i=Math.floor((e.length+a-(r+1))/n)+1;return Ar(e,this.window,r,n,{fft_length:s,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:i})}async _call(e,t={}){Et(e,"Gemma4AudioFeatureExtractor");const r=e.length,n=await super._call(e,t),{input_features:s}=n,[,a,i]=s.dims,{frame_length:c,hop_length:u}=this.config,h=Math.floor(c/2),p=c+1,_=new Uint8Array(r+h+(t.pad_to_multiple_of??128));_.fill(1,h,h+r);const m=new Uint8Array(a);for(let b=0;b<a;++b)m[b]=_[b*u+p-1]?1:0;const w=s.data;for(let b=0;b<a;++b)m[b]||w.fill(0,b*i,(b+1)*i);return n.input_features_mask=new K("bool",m,[1,a]),n}},_C=class extends St{constructor(e){super(e);const{n_fft:t,win_length:r,n_mels:n,sample_rate:s}=e.melspec_kwargs;this.mel_filters=kr(Math.floor(1+t/2),n,0,s/2,s,null,"htk");const a=qr(r,"hann");this.window=new Float64Array(t);const i=Math.floor((t-r)/2);this.window.set(a,i)}async _call(e){Et(e,"GraniteSpeechFeatureExtractor");const{n_fft:t,hop_length:r,n_mels:n}=this.config.melspec_kwargs,s=1+Math.floor((e.length-1)/r),a=s-s%2;return{input_features:(await Ar(e,this.window,t,r,{power:2,mel_filters:this.mel_filters,log_mel:"log10_max_norm",transpose:!0,max_num_frames:a,do_pad:!1})).view(-1,2*n).unsqueeze_(0)}}},mC=class extends St{async _call(e){Et(e,"MoonshineFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const t=[1,e.length];return{input_values:new K("float32",e,t)}}},Ev=class extends St{async _call(e){Et(e,"PyAnnoteFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const t=[1,1,e.length];return{input_values:new K("float32",e,t)}}samples_to_frames(e){return(e-this.config.offset)/this.config.step}post_process_speaker_diarization(e,t){const r=t/this.samples_to_frames(t)/this.config.sampling_rate,n=[];for(const s of e.tolist()){const a=[];let i=-1;for(let c=0;c<s.length;++c){const u=Is(s[c]),[h,p]=pt(u),[_,m]=[c,c+1];p!==i?(i=p,a.push({id:p,start:_,end:m,score:h})):(a.at(-1).end=m,a.at(-1).score+=h)}n.push(a.map(({id:c,start:u,end:h,score:p})=>({id:c,start:u*r,end:h*r,confidence:p/(h-u)})))}return n}},gC=class extends St{constructor(e){super(e);const t=this.config.sampling_rate,r=kr(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=qr(400,"povey",{periodic:!1})}async _extract_fbank_features(e,t){return e=e.map(r=>r*32768),Ar(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e,{padding:t=!0,pad_to_multiple_of:r=2,do_normalize_per_mel_bins:n=!0,return_attention_mask:s=!0}={}){Et(e,"SeamlessM4TFeatureExtractor");let a=await this._extract_fbank_features(e,this.config.max_length);if(n){const[w,b]=a.dims,M=a.data;for(let E=0;E<b;++E){let T=0;for(let F=0;F<w;++F)T+=M[F*b+E];const C=T/w;let P=0;for(let F=0;F<w;++F)P+=(M[F*b+E]-C)**2;P/=w-1;const A=Math.sqrt(P+1e-7);for(let F=0;F<w;++F){const G=F*b+E;M[G]=(M[G]-C)/A}}}let i;if(t){const[w,b]=a.dims,M=a.data,E=w%r;if(E>0){const T=new Float32Array(b*(w+E));T.set(M),T.fill(this.config.padding_value,M.length);const C=w+E;a=new K(a.type,T,[C,b]),s&&(i=new K("int64",new BigInt64Array(C),[1,C]),i.data.fill(1n,0,w))}}const[c,u]=a.dims,h=this.config.stride;if(c%h!==0)throw new Error(`The number of frames (${c}) must be a multiple of the stride (${h}).`);const _=a.view(1,Math.floor(c/h),u*h),m={input_features:_};if(s){const w=_.dims[1],b=new BigInt64Array(w);if(i){const M=i.data;for(let E=1,T=0;E<c;E+=h,++T)b[T]=M[E]}else b.fill(1n);m.attention_mask=new K("int64",b,[1,w])}return m}},wC=class extends Mv{},yC=class extends St{},vC=class extends St{_zero_mean_unit_var_norm(e){const r=e.reduce((s,a)=>s+a,0)/e.length,n=e.reduce((s,a)=>s+(a-r)**2,0)/e.length;return e.map(s=>(s-r)/Math.sqrt(n+1e-7))}async _call(e){Et(e,"Wav2Vec2FeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));let t=e;this.config.do_normalize&&(t=this._zero_mean_unit_var_norm(t));const r=[1,t.length];return{input_values:new K("float32",t,r),attention_mask:new K("int64",new BigInt64Array(t.length).fill(1n),r)}}},bC=class extends St{constructor(e){super(e);const t=this.config.sampling_rate,r=kr(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=qr(400,"hamming",{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(e){return e=e.map(t=>t*32768),Ar(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(e){Et(e,"WeSpeakerFeatureExtractor");const t=(await this._extract_fbank_features(e)).unsqueeze_(0);if(this.config.fbank_centering_span===null){const r=t.mean(1).data,n=t.data,[s,a,i]=t.dims;for(let c=0;c<s;++c){const u=c*a*i,h=c*i;for(let p=0;p<a;++p){const _=u+p*i;for(let m=0;m<i;++m)n[_+m]-=r[h+m]}}}return{input_features:t}}},MC=class extends St{constructor(e){super(e),this.config.mel_filters??=kr(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney"),this.window=qr(this.config.n_fft,"hann")}async _extract_fbank_features(e,{center:t=!0}={}){const{n_fft:r,hop_length:n,mel_filters:s,global_log_mel_max:a}=this.config,i=Math.floor(t?e.length/n:(e.length-r)/n);return await Ar(e,this.window,r,n,{power:2,mel_filters:s,log_mel:"log10_max_norm",max_log_mel:a,center:t,max_num_frames:i,do_pad:!1})}async _call(e,{center:t=!0}={}){return Et(e,"VoxtralRealtimeFeatureExtractor"),{input_features:(await this._extract_fbank_features(e,{center:t})).unsqueeze_(0)}}},xC=class extends St{constructor(e){super(e),this.config.mel_filters??=kr(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,8e3,this.config.sampling_rate,"slaney","slaney"),this.window=qr(this.config.n_fft,"hann")}async _extract_fbank_features(e){return await Ar(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}={}){Et(e,"WhisperFeatureExtractor");let r;const n=t??this.config.n_samples;return e.length>n?(e.length>this.config.n_samples&&be.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`."),r=e.slice(0,n)):(r=new Float32Array(n),r.set(e)),{input_features:(await this._extract_fbank_features(r)).unsqueeze_(0)}}},rr=class{static async from_pretrained(e,t={}){const r=await jr(e,np,!0,t),n=r.feature_extractor_type,s=gv[n];if(!s)throw new Error(`Unknown feature_extractor_type: '${n}'. Please report this at ${Fl}.`);return new s(r)}},TC=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e,t=null){const r=this.tokenizer(e),n=t?await this.feature_extractor(t):{};return{...r,...n}}},EC=new Set(["ja","zh"]),kC=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;static uses_processor_config=!0;get_decoder_prompt_ids(e="en"){const t=["▁","<|startofcontext|>","<|startoftranscript|>","<|emo:undefined|>",`<|${e}|>`,`<|${e}|>`,"<|pnc|>","<|noitn|>","<|notimestamp|>","<|nodiarize|>"];return this.tokenizer.convert_tokens_to_ids(t)}static join_chunks(e,t="en"){const r=e.filter(a=>a&&a.trim());if(r.length===0)return"";const n=EC.has(t)?"":" ";return[r[0].trimEnd(),...r.slice(1).map(a=>a.trim())].join(n)}async _call(e){return await this.feature_extractor(e)}},fh={},jn,kv,nn;if(ve.IS_WEB_ENV)jn=(e,t)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this environment.");return new self.OffscreenCanvas(e,t)},nn=self.createImageBitmap,kv=self.ImageData;else if(fh)nn=async e=>{const r=(await e.metadata()).channels,{data:n,info:s}=await e.rotate().raw().toBuffer({resolveWithObject:!0}),a=new yi(new Uint8ClampedArray(n),s.width,s.height,s.channels);return r!==void 0&&r!==s.channels&&a.convert(r),a};else throw new Error("Unable to load image processing library.");var CC={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},AC=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]),yi=class vr{constructor(t,r,n,s){this.data=t,this.width=r,this.height=n,this.channels=s}get size(){return[this.width,this.height]}static async read(t){if(t instanceof vr)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 new Error(`Unsupported input type: ${typeof t}`)}static fromCanvas(t){if(!ve.IS_WEB_ENV)throw new Error("fromCanvas() is only supported in browser environments.");const n=t.getContext("2d").getImageData(0,0,t.width,t.height).data;return new vr(n,t.width,t.height,4)}static async fromURL(t){const r=await ml(t);if(r.status!==200)throw new Error(`Unable to read image from "${t}" (${r.status} ${r.statusText})`);const n=await r.blob();return this.fromBlob(n)}static async fromBlob(t){if(ve.IS_WEB_ENV){const r=await nn(t),n=jn(r.width,r.height).getContext("2d");return n.drawImage(r,0,0),new this(n.getImageData(0,0,r.width,r.height).data,r.width,r.height,4)}else{const r=fh(await t.arrayBuffer());return await nn(r)}}static fromTensor(t,r="CHW"){if(t.dims.length!==3)throw new Error(`Tensor should have 3 dimensions, but has ${t.dims.length} dimensions.`);if(r==="CHW")t=t.transpose(1,2,0);else if(r!=="HWC")throw new Error(`Unsupported channel format: ${r}`);if(!(t.data instanceof Uint8ClampedArray||t.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${t.type}`);switch(t.dims[2]){case 1:case 2:case 3:case 4:return new vr(t.data,t.dims[1],t.dims[0],t.dims[2]);default:throw new Error(`Unsupported number of channels: ${t.dims[2]}`)}}grayscale(){if(this.channels===1)return this;const t=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let r=0,n=0;r<this.data.length;r+=this.channels){const s=this.data[r],a=this.data[r+1],i=this.data[r+2];t[n++]=Math.round(.2989*s+.587*a+.114*i)}break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,1)}rgb(){if(this.channels===3)return this;const t=new Uint8ClampedArray(this.width*this.height*3);switch(this.channels){case 1:for(let r=0,n=0;r<this.data.length;++r)t[n++]=this.data[r],t[n++]=this.data[r],t[n++]=this.data[r];break;case 4:for(let r=0,n=0;r<this.data.length;r+=4)t[n++]=this.data[r],t[n++]=this.data[r+1],t[n++]=this.data[r+2];break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,3)}rgba(){if(this.channels===4)return this;const t=new Uint8ClampedArray(this.width*this.height*4);switch(this.channels){case 1:for(let r=0,n=0;r<this.data.length;++r)t[n++]=this.data[r],t[n++]=this.data[r],t[n++]=this.data[r],t[n++]=255;break;case 3:for(let r=0,n=0;r<this.data.length;r+=3)t[n++]=this.data[r],t[n++]=this.data[r+1],t[n++]=this.data[r+2],t[n++]=255;break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this._update(t,this.width,this.height,4)}putAlpha(t){if(t.width!==this.width||t.height!==this.height)throw new Error(`Expected mask size to be ${this.width}x${this.height}, but got ${t.width}x${t.height}`);if(t.channels!==1)throw new Error(`Expected mask to have 1 channel, but got ${t.channels}`);const r=this.data,n=t.data,s=this.width*this.height;if(this.channels===3){const a=new Uint8ClampedArray(s*4);for(let i=0,c=0,u=0;i<s;++i)a[u++]=r[c++],a[u++]=r[c++],a[u++]=r[c++],a[u++]=n[i];return this._update(a,this.width,this.height,4)}else if(this.channels===4){for(let a=0;a<s;++a)r[4*a+3]=n[a];return this}throw new Error(`Expected image to have 3 or 4 channels, but got ${this.channels}`)}async resize(t,r,{resample:n=2}={}){if(this.width===t&&this.height===r)return this;let s=CC[n]??n;const a=dg(t),i=dg(r);if(a&&i)return this;if(a?t=r/this.height*this.width:i&&(r=t/this.width*this.height),ve.IS_WEB_ENV){const c=this.channels,u=this.toCanvas(),h=jn(t,r).getContext("2d");return h.drawImage(u,0,0,t,r),new vr(h.getImageData(0,0,t,r).data,t,r,4).convert(c)}else{let c=this.toSharp();switch(s){case"box":case"hamming":(s==="box"||s==="hamming")&&(be.warn(`Resampling method ${s} is not yet supported. Using bilinear instead.`),s="bilinear");case"nearest":case"bilinear":case"bicubic":c=c.affine([t/this.width,0,0,r/this.height],{interpolator:s});break;case"lanczos":c=c.resize({width:t,height:r,fit:"fill",kernel:"lanczos3"});break;default:throw new Error(`Resampling method ${s} is not supported.`)}return await nn(c)}}async pad([t,r,n,s]){if(t=Math.max(t,0),r=Math.max(r,0),n=Math.max(n,0),s=Math.max(s,0),t===0&&r===0&&n===0&&s===0)return this;if(ve.IS_WEB_ENV){const a=this.channels,i=this.toCanvas(),c=this.width+t+r,u=this.height+n+s,h=jn(c,u).getContext("2d");return h.drawImage(i,0,0,this.width,this.height,t,n,this.width,this.height),new vr(h.getImageData(0,0,c,u).data,c,u,4).convert(a)}else{const a=this.toSharp().extend({left:t,right:r,top:n,bottom:s});return await nn(a)}}async crop([t,r,n,s]){if(t=Math.max(t,0),r=Math.max(r,0),n=Math.min(n,this.width-1),s=Math.min(s,this.height-1),t===0&&r===0&&n===this.width-1&&s===this.height-1)return this;const a=n-t+1,i=s-r+1;if(ve.IS_WEB_ENV){const c=this.channels,u=this.toCanvas(),h=jn(a,i).getContext("2d");return h.drawImage(u,t,r,a,i,0,0,a,i),new vr(h.getImageData(0,0,a,i).data,a,i,4).convert(c)}else{const c=this.toSharp().extract({left:t,top:r,width:a,height:i});return await nn(c)}}async center_crop(t,r){if(this.width===t&&this.height===r)return this;const n=(this.width-t)/2,s=(this.height-r)/2;if(ve.IS_WEB_ENV){const a=this.channels,i=this.toCanvas(),c=jn(t,r).getContext("2d");let u=0,h=0,p=0,_=0;return n>=0?u=n:p=-n,s>=0?h=s:_=-s,c.drawImage(i,u,h,t,r,p,_,t,r),new vr(c.getImageData(0,0,t,r).data,t,r,4).convert(a)}else{let a=this.toSharp();if(n>=0&&s>=0)a=a.extract({left:Math.floor(n),top:Math.floor(s),width:t,height:r});else if(n<=0&&s<=0){const i=Math.floor(-s),c=Math.floor(-n);a=a.extend({top:i,left:c,right:t-this.width-c,bottom:r-this.height-i})}else{let i=[0,0],c=0;s<0?(i[0]=Math.floor(-s),i[1]=r-this.height-i[0]):c=Math.floor(s);let u=[0,0],h=0;n<0?(u[0]=Math.floor(-n),u[1]=t-this.width-u[0]):h=Math.floor(n),a=a.extend({top:i[0],bottom:i[1],left:u[0],right:u[1]}).extract({left:h,top:c,width:t,height:r})}return await nn(a)}}async toBlob(t="image/png",r=1){if(!ve.IS_WEB_ENV)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:t,quality:r})}toTensor(t="CHW"){let r=new K("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if(t!=="HWC")if(t==="CHW")r=r.permute(2,0,1);else throw new Error(`Unsupported channel format: ${t}`);return r}toCanvas(){if(!ve.IS_WEB_ENV)throw new Error("toCanvas() is only supported in browser environments.");const t=this.clone().rgba(),r=jn(t.width,t.height),n=new kv(t.data,t.width,t.height);return r.getContext("2d").putImageData(n,0,0),r}split(){const{data:t,width:r,height:n,channels:s}=this,a=t.constructor,i=t.length/s,c=Array.from({length:s},()=>new a(i));for(let u=0;u<i;++u){const h=s*u;for(let p=0;p<s;++p)c[p][u]=t[h+p]}return c.map(u=>new vr(u,r,n,1))}_update(t,r,n,s=null){return this.data=t,this.width=r,this.height=n,s!==null&&(this.channels=s),this}clone(){return new vr(this.data.slice(),this.width,this.height,this.channels)}convert(t){if(this.channels===t)return this;switch(t){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(t){if(ve.IS_WEB_ENV){if(ve.IS_WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const r=t.split(".").pop().toLowerCase(),n=AC.get(r)??"image/png",s=await this.toBlob(n);return tC(t,s)}else if(ve.IS_FS_AVAILABLE)await this.toSharp().toFile(t);else throw new Error("Unable to save the image because filesystem is disabled in this environment.")}toSharp(){if(ve.IS_WEB_ENV)throw new Error("toSharp() is only supported in server-side environments.");return fh(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}};yi.read.bind(yi);function qg(e,t,r=0,n=null){const s=e/t;let a=OE(s)*t;return n!==null&&a>n&&(a=Math.floor(s)*t),a<r&&(a=Math.ceil(s)*t),a}function Hg([e,t],r){return[Math.max(Math.floor(e/r),1)*r,Math.max(Math.floor(t/r),1)*r]}function Cv([e,t,r,n]){return[e-r/2,t-n/2,e+r/2,t+n/2]}function Il(e,t=.5,r=null,n=!1){const s=e.logits,a=e.pred_boxes,[i,c,u]=s.dims;if(r!==null&&r.length!==i)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let h=[];for(let p=0;p<i;++p){let _=r!==null?r[p]:null,m={boxes:[],classes:[],scores:[]},w=s[p],b=a[p];for(let M=0;M<c;++M){let E=w[M],T=[],C;if(n){C=E.sigmoid().data;for(let P=0;P<C.length;++P)C[P]>t&&T.push(P)}else{let P=pt(E.data)[1];if(P===u-1||(C=Is(E.data),C[P]<t))continue;T.push(P)}for(const P of T){let A=b[M].data;A=Cv(A),_!==null&&(A=A.map((F,G)=>F*_[(G+1)%2])),m.boxes.push(A),m.classes.push(P),m.scores.push(C[P])}}h.push(m)}return h}function Av(e,t=null){const r=e.logits,n=r.dims[0];if(t!==null&&t.length!==n)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const s=[];for(let a=0;a<n;++a){const i=t!==null?t[a]:null;let c=r[a];i!==null&&(c=sv(c,i,"bilinear",!1));const[u,h]=i??c.dims.slice(-2),p=new K("int32",new Int32Array(u*h),[u,h]),_=c[0].data,m=p.data;for(let M=1;M<c.dims[0];++M){const E=c[M].data;for(let T=0;T<E.length;++T)E[T]>_[T]&&(_[T]=E[T],m[T]=M)}const w=new Array(c.dims[0]);for(let M=0;M<m.length;++M){const E=m[M];w[E]=E}const b=w.filter(M=>M!==void 0);s.push({segmentation:p,labels:b})}return s}function SC(e,t,r,n){const s=[],a=[],i=[];for(let c=0;c<e.dims[0];++c){const u=e[c],h=t[c],p=pt(u.data)[1];if(p===n)continue;const m=Is(u.data)[p];m>r&&(s.push(h),a.push(m),i.push(p))}return[s,a,i]}function PC(e,t,r,n=.5,s=.8){const a=[];let i=0,c=0;const u=t[r].data;for(let p=0;p<e.length;++p)e[p]===r&&(a.push(p),++i),u[p]>=n&&++c;let h=i>0&&c>0;return h&&(h=i/c>s),[h,a]}function FC(e,t,r,n,s,a=null,i=null){const[c,u]=i??e[0].dims,h=new K("int32",new Int32Array(c*u),[c,u]),p=[];if(i!==null)for(let M=0;M<e.length;++M)e[M]=sv(e[M],i,"bilinear",!1);const _=new Int32Array(e[0].data.length),m=new Float32Array(e[0].data.length);for(let M=0;M<e.length;++M){let E=t[M];const T=e[M].data;for(let C=0;C<T.length;++C)T[C]*=E,T[C]>m[C]&&(_[C]=M,m[C]=T[C])}let w=0;const b=h.data;for(let M=0;M<r.length;++M){const E=r[M],[T,C]=PC(_,e,M,n,s);if(T){++w;for(const P of C)b[P]=w;p.push({id:w,label_id:E,score:t[M]})}}return[h,p]}function sp(e,t,r=28,n=3136,s=784*1280,a=1){if(e<r||t<r){const u=Math.max(r/e,r/t);e=Math.round(e*u),t=Math.round(t*u)}if(Math.max(e,t)/Math.min(e,t)>200)throw new Error(`absolute aspect ratio must be smaller than 200, got ${Math.max(e,t)/Math.min(e,t)}`);let i=Math.round(e/r)*r,c=Math.round(t/r)*r;if(a*i*c>s){const u=Math.sqrt(a*e*t/s);i=Math.max(r,Math.floor(e/u/r)*r),c=Math.max(r,Math.floor(t/u/r)*r)}else if(a*i*c<n){const u=Math.sqrt(n/(a*e*t));i=Math.ceil(e*u/r)*r,c=Math.ceil(t*u/r)*r}return[c,i]}function Sv(e,t=.5,r=.5,n=.8,s=null,a=null){s===null&&(be.warn("`label_ids_to_fuse` unset. No instance will be fused."),s=new Set);const i=e.class_queries_logits??e.logits,u=(e.masks_queries_logits??e.pred_masks).sigmoid();let[h,p,_]=i.dims;if(_-=1,a!==null&&a.length!==h)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");let m=[];for(let w=0;w<h;++w){let b=a!==null?a[w]:null,M=i[w],E=u[w],[T,C,P]=SC(M,E,t,_);if(P.length===0){let[G,v]=b??E.dims.slice(-2),j=new K("int32",new Int32Array(G*v).fill(-1),[G,v]);m.push({segmentation:j,segments_info:[]});continue}let[A,F]=FC(T,C,P,r,n,s,b);m.push({segmentation:A,segments_info:F})}return m}function Pv(e,t=.5,r=null){throw new Error("`post_process_instance_segmentation` is not yet implemented.")}var ge=class extends Yt{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,r=2){const n=e.height,s=e.width,a=t.height,i=t.width;let c=Math.min(n,a),u=Math.min(s,i);return c===n&&u===s?e:(n>s?u=Math.floor(s*c/n):s>n&&(c=Math.floor(n*u/s)),await e.resize(u,c,{resample:r}))}async crop_margin(e,t=200){const r=e.clone().grayscale(),n=lh(r.data)[0],a=pt(r.data)[0]-n;if(a===0)return e;const i=t/255;let c=r.width,u=r.height,h=0,p=0;const _=r.data;for(let m=0;m<r.height;++m){const w=m*r.width;for(let b=0;b<r.width;++b)(_[w+b]-n)/a<i&&(c=Math.min(c,b),u=Math.min(u,m),h=Math.max(h,b),p=Math.max(p,m))}return e=await e.crop([c,u,h,p]),e}pad_image(e,t,r,{mode:n="constant",center:s=!1,constant_values:a=0}={}){const[i,c,u]=t;let h,p;if(typeof r=="number"?(h=r,p=r):r==="square"?h=p=Math.max(i,c):(h=r.width,p=r.height),h!==c||p!==i){const _=new Float32Array(h*p*u);if(Array.isArray(a))for(let b=0;b<_.length;++b)_[b]=a[b%u];else a!==0&&_.fill(a);const[m,w]=s?[Math.floor((h-c)/2),Math.floor((p-i)/2)]:[0,0];for(let b=0;b<i;++b){const M=(b+w)*h,E=b*c;for(let T=0;T<c;++T){const C=(M+T+m)*u,P=(E+T)*u;for(let A=0;A<u;++A)_[C+A]=e[P+A]}}if(n==="symmetric"){if(s)throw new Error("`center` padding is not supported when `mode` is set to `symmetric`.");const b=i-1,M=c-1;for(let E=0;E<p;++E){const T=E*h,C=hl(E,b)*c;for(let P=0;P<h;++P){if(E<i&&P<c)continue;const A=(T+P)*u,F=(C+hl(P,M))*u;for(let G=0;G<u;++G)_[A+G]=e[F+G]}}}e=_,t=[p,h,u]}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){const[r,n]=e.size;let s,a;if(this.do_thumbnail){const{height:i,width:c}=t;s=Math.min(i,c)}else Number.isInteger(t)?(s=t,a=this.config.max_size??s):t!==void 0&&(s=t.shortest_edge,a=t.longest_edge);if(s!==void 0||a!==void 0){const i=s===void 0?1:Math.max(s/r,s/n),c=r*i,u=n*i,h=a===void 0?1:Math.min(a/c,a/u);let p=Math.floor(Number((c*h).toFixed(2))),_=Math.floor(Number((u*h).toFixed(2)));return this.size_divisibility!==void 0&&([p,_]=Hg([p,_],this.size_divisibility)),[p,_]}else if(t!==void 0&&t.width!==void 0&&t.height!==void 0){let i=t.width,c=t.height;if(this.config.keep_aspect_ratio&&this.config.ensure_multiple_of){let u=c/n,h=i/r;Math.abs(1-h)<Math.abs(1-u)?u=h:h=u,c=qg(u*n,this.config.ensure_multiple_of),i=qg(h*r,this.config.ensure_multiple_of)}return[i,c]}else{if(this.size_divisibility!==void 0)return Hg([r,n],this.size_divisibility);throw new Error(`Could not resize image due to unsupported \`this.size\` option in config: ${JSON.stringify(t)}`)}}async resize(e){const[t,r]=this.get_resize_output_image_size(e,this.size);return await e.resize(t,r,{resample:this.resample})}async preprocess(e,{do_normalize:t=null,do_pad:r=null,do_convert_rgb:n=null,do_convert_grayscale:s=null,do_flip_channel_order:a=null}={}){this.do_crop_margin&&(e=await this.crop_margin(e));const[i,c]=e.size;if(n??this.do_convert_rgb?e=e.rgb():s&&(e=e.grayscale()),this.do_resize&&(e=await this.resize(e)),this.do_thumbnail&&(e=await this.thumbnail(e,this.size,this.resample)),this.do_center_crop){let m,w;Number.isInteger(this.crop_size)?(m=this.crop_size,w=this.crop_size):(m=this.crop_size.width,w=this.crop_size.height),e=await e.center_crop(m,w)}const u=[e.height,e.width];let h=Float32Array.from(e.data),p=[e.height,e.width,e.channels];if(this.do_rescale&&this.rescale(h),t??this.do_normalize){let m=this.image_mean;Array.isArray(this.image_mean)||(m=new Array(e.channels).fill(m));let w=this.image_std;if(Array.isArray(this.image_std)||(w=new Array(e.channels).fill(w)),m.length!==e.channels||w.length!==e.channels)throw new Error(`When set to arrays, the length of \`image_mean\` (${m.length}) and \`image_std\` (${w.length}) must match the number of channels in the image (${e.channels}).`);for(let b=0;b<h.length;b+=e.channels)for(let M=0;M<e.channels;++M)h[b+M]=(h[b+M]-m[M])/w[M]}if(r??this.do_pad){if(this.pad_size)[h,p]=this.pad_image(h,[e.height,e.width,e.channels],this.pad_size);else if(this.size_divisibility){const m=Math.ceil(p[1]/this.size_divisibility)*this.size_divisibility,w=Math.ceil(p[0]/this.size_divisibility)*this.size_divisibility;[h,p]=this.pad_image(h,p,{width:m,height:w})}}if(a??this.do_flip_channel_order){if(p[2]!==3)throw new Error("Flipping channel order is only supported for RGB images.");for(let m=0;m<h.length;m+=3){const w=h[m];h[m]=h[m+2],h[m+2]=w}}const _=new K("float32",h,p).permute(2,0,1);return{original_size:[c,i],reshaped_input_size:u,pixel_values:_}}async _call(e,...t){Array.isArray(e)||(e=[e]);const r=await Promise.all(e.map(s=>this.preprocess(s)));return{pixel_values:Gr(r.map(s=>s.pixel_values),0),original_sizes:r.map(s=>s.original_size),reshaped_input_sizes:r.map(s=>s.reshaped_input_size)}}static async from_pretrained(e,t={}){const r=await jr(e,pv,!0,t);return new this(r)}},Fv={};Ss(Fv,{BeitFeatureExtractor:()=>IC,BitImageProcessor:()=>LC,CHMv2ImageProcessor:()=>NC,CLIPFeatureExtractor:()=>BC,CLIPImageProcessor:()=>Iv,ChineseCLIPFeatureExtractor:()=>OC,ConvNextFeatureExtractor:()=>$C,ConvNextImageProcessor:()=>Lv,DINOv3ViTImageProcessor:()=>zC,DPTFeatureExtractor:()=>UC,DPTImageProcessor:()=>Bv,DeiTFeatureExtractor:()=>DC,DeiTImageProcessor:()=>Ov,DetrFeatureExtractor:()=>RC,DetrImageProcessor:()=>Nv,DonutFeatureExtractor:()=>GC,DonutImageProcessor:()=>ap,EfficientNetImageProcessor:()=>VC,GLPNFeatureExtractor:()=>QC,Gemma3ImageProcessor:()=>WC,Gemma4ImageProcessor:()=>$v,Glm46VImageProcessor:()=>HC,GroundingDinoImageProcessor:()=>YC,Idefics3ImageProcessor:()=>Qg,ImageFeatureExtractor:()=>ge,ImageProcessor:()=>ge,JinaCLIPImageProcessor:()=>JC,Lfm2VlImageProcessor:()=>rA,LlavaOnevisionImageProcessor:()=>nA,Mask2FormerImageProcessor:()=>aA,MaskFormerFeatureExtractor:()=>sA,MaskFormerImageProcessor:()=>op,MobileNetV1FeatureExtractor:()=>oA,MobileNetV1ImageProcessor:()=>Rv,MobileNetV2FeatureExtractor:()=>iA,MobileNetV2ImageProcessor:()=>zv,MobileNetV3FeatureExtractor:()=>lA,MobileNetV3ImageProcessor:()=>Gv,MobileNetV4FeatureExtractor:()=>cA,MobileNetV4ImageProcessor:()=>Uv,MobileViTFeatureExtractor:()=>uA,MobileViTImageProcessor:()=>Vv,NougatImageProcessor:()=>dA,OwlViTFeatureExtractor:()=>fA,OwlViTImageProcessor:()=>ip,Owlv2ImageProcessor:()=>hA,Phi3VImageProcessor:()=>_A,PixtralImageProcessor:()=>mA,PvtImageProcessor:()=>gA,Qwen2VLImageProcessor:()=>Dv,RTDetrImageProcessor:()=>wA,Sam2ImageProcessor:()=>Pf,Sam3ImageProcessor:()=>Pf,SamImageProcessor:()=>Pf,SapiensFeatureExtractor:()=>yA,SapiensImageProcessor:()=>Wv,SegformerFeatureExtractor:()=>vA,SegformerImageProcessor:()=>jv,SiglipImageProcessor:()=>bA,SmolVLMImageProcessor:()=>Qg,Swin2SRImageProcessor:()=>MA,VLMImageProcessor:()=>XC,ViTFeatureExtractor:()=>xA,ViTImageProcessor:()=>qv,VitMatteImageProcessor:()=>TA,VitPoseImageProcessor:()=>EA,YolosFeatureExtractor:()=>kA,YolosImageProcessor:()=>Hv});var IC=class extends ge{},LC=class extends ge{},OC=class extends ge{},NC=class extends ge{},Iv=class extends ge{},BC=class extends Iv{},Lv=class extends ge{constructor(e){super(e),this.crop_pct=this.config.crop_pct??224/256}async resize(e){const t=this.size?.shortest_edge;if(t===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(t<384){const r=Math.floor(t/this.crop_pct),[n,s]=this.get_resize_output_image_size(e,{shortest_edge:r});e=await e.resize(n,s,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}},$C=class extends Lv{},Ov=class extends ge{},DC=class extends Ov{},Nv=class extends ge{async _call(e){const t=await super._call(e),r=[t.pixel_values.dims[0],64,64],n=At(r,1n);return{...t,pixel_mask:n}}post_process_object_detection(...e){return Il(...e)}post_process_panoptic_segmentation(...e){return Sv(...e)}post_process_instance_segmentation(...e){return Pv(...e)}},RC=class extends Nv{},zC=class extends ge{},ap=class extends ge{pad_image(e,t,r,n={}){const[s,a,i]=t;let c=this.image_mean;Array.isArray(this.image_mean)||(c=new Array(i).fill(c));let u=this.image_std;Array.isArray(u)||(u=new Array(i).fill(c));const h=c.map((p,_)=>-p/u[_]);return super.pad_image(e,t,r,{center:!0,constant_values:h,...n})}},GC=class extends ap{},Bv=class extends ge{},UC=class extends Bv{},VC=class extends ge{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(t=>t*t))}},WC=class extends ge{};function jC(e,t,r,n,s){const a=n*r**2,i=Math.sqrt(a/(e*t)),c=s*r;let u=Math.floor(i*e/c)*c,h=Math.floor(i*t/c)*c;if(u===0&&h===0)throw new Error(`Attempting to resize to a 0 x 0 image. Resized height should be divisible by \`pooling_kernel_size * patch_size\`=${c}.`);const p=Math.floor(n/s**2)*c;return u===0?(u=c,h=Math.min(Math.floor(t/e)*c,p)):h===0&&(h=c,u=Math.min(Math.floor(e/t)*c,p)),[u,h]}function qC(e,t,r,n,s,a,i){const c=Math.floor(t/s),u=Math.floor(r/s),h=c*u,p=s*s*n,_=new Float32Array(a*p);let m=0;for(let M=0;M<c;++M)for(let E=0;E<u;++E)for(let T=0;T<s;++T){const C=(M*s+T)*r*n+E*s*n;for(let P=0;P<s;++P){const A=C+P*n;for(let F=0;F<n;++F)_[m++]=e[A+F]}}const w=new BigInt64Array(a*2).fill(-1n);let b=0;for(let M=0;M<c;++M)for(let E=0;E<u;++E)w[b++]=BigInt(E),w[b++]=BigInt(M);return{patches:new K("float32",_,[a,p]),positions:new K("int64",w,[a,2]),num_soft_tokens:Math.floor(h/i**2)}}var $v=class extends Yt{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]);const{patch_size:t,pooling_kernel_size:r}=this,n=this.max_soft_tokens*r**2,s=[],a=[],i=[];for(let c of e){if(this.do_convert_rgb&&(c=c.rgb()),this.do_resize){const[m,w]=jC(c.height,c.width,t,n,r);(m!==c.height||w!==c.width)&&(c=await c.resize(w,m,{resample:this.resample}))}const u=Float32Array.from(c.data);if(this.do_rescale)for(let m=0;m<u.length;++m)u[m]*=this.rescale_factor;const{patches:h,positions:p,num_soft_tokens:_}=qC(u,c.height,c.width,c.channels,t,n,r);s.push(h),a.push(p),i.push(_)}return{pixel_values:Gr(s,0),image_position_ids:Gr(a,0),num_soft_tokens_per_image:i}}},Dv=class extends ge{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){const r=this.patch_size*this.merge_size;return sp(e.height,e.width,r,this.min_pixels,this.max_pixels)}async _call(e,...t){const{pixel_values:r,original_sizes:n,reshaped_input_sizes:s}=await super._call(e,...t);let a=r;const{temporal_patch_size:i,merge_size:c,patch_size:u}=this.config;a.dims[0]===1&&(a=je(Array.from({length:i},()=>a),0));const h=a.dims[0]/i,p=a.dims[1],_=Math.floor(a.dims[2]/u),m=Math.floor(a.dims[3]/u),w=a.view(h,i,p,Math.floor(_/c),c,u,Math.floor(m/c),c,u).permute(0,3,6,4,7,2,1,5,8).view(h*_*m,p*i*u*u),b=new K("int64",[h,_,m],[1,3]);return{pixel_values:w,image_grid_thw:b,original_sizes:n,reshaped_input_sizes:s}}},HC=class extends Dv{get_resize_output_image_size(e,t){const r=this.patch_size*this.merge_size,n=this.config.temporal_patch_size??2;return sp(e.height,e.width,r,this.min_pixels,this.max_pixels,n)}},QC=class extends ge{},YC=class extends ge{async _call(e){const t=await super._call(e),r=t.pixel_values.dims,n=Ot([r[0],r[2],r[3]]);return{...t,pixel_mask:n}}},Qg=class extends ge{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[r,n]=e.dims.slice(-2);const s=n/r;return n>=r?(n=Math.ceil(n/t)*t,r=Math.floor(n/s),r=Math.ceil(r/t)*t):(r=Math.ceil(r/t)*t,n=Math.floor(r*s),n=Math.ceil(n/t)*t),{height:r,width:n}}async _call(e,{do_image_splitting:t=null,return_row_col_info:r=!1}={}){let n;if(!Array.isArray(e))n=[[e]];else{if(e.length===0||!e[0])throw new Error("No images provided.");Array.isArray(e[0])?n=e:n=[e]}let s=[],a=[],i=[];const c=[],u=[];for(const E of n){let T=await Promise.all(E.map(A=>this.preprocess(A)));c.push(...T.map(A=>A.original_size)),u.push(...T.map(A=>A.reshaped_input_size)),T.forEach(A=>A.pixel_values.unsqueeze_(0));const{longest_edge:C}=this.max_image_size;let P;if(t??this.do_image_splitting){let A=new Array(T.length),F=new Array(T.length);P=await Promise.all(T.map(async(G,v)=>{const j=this.get_resize_for_vision_encoder(G.pixel_values,C),U=await Er(G.pixel_values,{size:[j.height,j.width]}),{frames:q,num_splits_h:ne,num_splits_w:H}=await this.split_image(U,this.max_image_size);return A[v]=ne,F[v]=H,je(q,0)})),a.push(A),i.push(F)}else{const A=[C,C];P=await Promise.all(T.map(F=>Er(F.pixel_values,{size:A}))),a.push(new Array(T.length).fill(0)),i.push(new Array(T.length).fill(0))}s.push(je(P,0))}const h=s.length,[p,_,m,w]=s[0].dims;let b,M;if(h===1)b=s[0].unsqueeze_(0),M=At([h,p,m,w],!0);else{const E=Math.max(...s.map(P=>P.dims.at(0)));M=At([h,E,m,w],!0);const T=M.data,C=E*m*w;for(let P=0;P<h;++P){const A=s[P].dims[0];if(A<E){s[P]=je([s[P],At([E-A,_,m,w],0)],0);const F=P*C+A*m*w,G=(P+1)*C;T.fill(!1,F,G)}}b=Gr(s,0)}return{pixel_values:b,pixel_attention_mask:M,original_sizes:c,reshaped_input_sizes:u,...r?{rows:a,cols:i}:{}}}async split_image(e,{longest_edge:t}){const r=t,n=t,s=[],[a,i]=e.dims.slice(-2);let c=0,u=0;if(a>r||i>n){c=Math.ceil(a/r),u=Math.ceil(i/n);const h=Math.ceil(a/c),p=Math.ceil(i/u);for(let w=0;w<c;++w)for(let b=0;b<u;++b){let M,E,T,C;w===c-1?(E=a-h,C=a):(E=w*h,C=(w+1)*h),b===u-1?(M=i-p,T=i):(M=b*p,T=(b+1)*p);const F=await ov(e,[E,M],[C,T],[2,3]);s.push(F)}const _=r,m=n;(a!==_||i!==m)&&(e=await Er(e,{size:[_,m]}))}return s.push(e),{frames:s,num_splits_h:c,num_splits_w:u}}},XC=class extends ge{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(t=>t*this.rescale_factor)}pad_image(e,t,r,n){return super.pad_image(e,t,r,{constant_values:this.constant_values,center:!0,...n})}},JC=class extends ge{constructor(e){const{resize_mode:t,fill_color:r,interpolation:n,size:s,...a}=e,i=t==="squash"?{width:s,height:s}:t==="shortest"?{shortest_edge:s}:{longest_edge:s},c=n==="bicubic"?3:2;super({...a,size:i,resample:c,do_center_crop:!0,crop_size:s,do_normalize:!0})}};function Yg(e,t){return Math.round(e/t)*t}function KC(e,t,r,n,s){let a=1/0,i=[1,1];const c=r*n;for(const u of t){const h=Math.abs(e-u[0]/u[1]);h<a?(a=h,i=u):h===a&&c>.5*s*s*u[0]*u[1]&&(i=u)}return i}function ZC(e,t){const r=[],n=new Set;for(let s=e;s<=t;++s)for(let a=1;a<=s;++a)for(let i=1;i<=s;++i){const c=a*i;if(c>=e&&c<=t){const u=a<<16|i;n.has(u)||(n.add(u),r.push([a,i]))}}return r.sort((s,a)=>s[0]*s[1]-a[0]*a[1])}function eA(e,t){const[r,n,s,a]=e.dims,i=Math.floor(s/t),c=Math.floor(a/t),u=t*t*n,h=e.data,p=new Float32Array(r*i*c*u),_=s*a;for(let m=0;m<r;++m){const w=m*n*_,b=m*i*c*u;for(let M=0;M<i;++M)for(let E=0;E<c;++E){let T=b+(M*c+E)*u;for(let C=0;C<t;++C){const P=(M*t+C)*a+E*t;for(let A=0;A<t;++A){const F=P+A;for(let G=0;G<n;++G)p[T++]=h[w+G*_+F]}}}}return new K("float32",p,[r,i*c,u])}function tA(e,t){const[,r,n]=e.dims,s=new BigInt64Array(t);s.fill(1n,0,r);let a=e;if(r<t){const i=new Float32Array(t*n);i.set(e.data),a=new K("float32",i,[1,t,n])}return{padded:a,mask:new K("int64",s,[t])}}var rA=class extends ge{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;const t=this.max_image_tokens*this.downsample_factor**2,r=this.do_image_splitting?(this.tile_size/this.encoder_patch_size)**2:0;this.max_num_patches=Math.max(t,r)}_is_image_too_large(e,t){const r=this.encoder_patch_size*this.downsample_factor,n=Math.max(this.encoder_patch_size,Yg(e,r)),s=Math.max(this.encoder_patch_size,Yg(t,r));return n*s>this.max_image_tokens*(this.encoder_patch_size*this.downsample_factor)**2*this.max_pixels_tolerance}_get_grid_layout(e,t){const r=ZC(this.min_tiles,this.max_tiles),[n,s]=KC(t/e,r,t,e,this.tile_size);return{grid_width:n,grid_height:s,target_width:this.tile_size*n,target_height:this.tile_size*s}}async _call(e,{return_row_col_info:t=null}={}){let r;Array.isArray(e)?Array.isArray(e[0])?r=e:r=[e]:r=[[e]];const n=[],s=[],a=[],i=[],c=[],u=[];for(const p of r){const _=await Promise.all(p.map(m=>this.preprocess(m,{do_pad:!1})));for(const{pixel_values:m}of _){const[,w,b]=m.dims,M=m.unsqueeze_(0),E=this.encoder_patch_size*this.downsample_factor,T=E**2,[C,P]=sp(Math.max(E,w),Math.max(E,b),E,this.min_image_tokens*T,this.max_image_tokens*T).map(U=>Math.max(E,U));let A,F=1,G=1;const v=this._is_image_too_large(w,b),j=this.do_image_splitting&&!(this.min_tiles===1&&this.max_tiles===1);if(v&&j){const{grid_width:U,grid_height:q,target_width:ne,target_height:H}=this._get_grid_layout(w,b);F=q,G=U;const I=await Er(M,{size:[H,ne]});A=[];for(let S=0;S<q;++S)for(let D=0;D<U;++D){const Y=S*this.tile_size,se=D*this.tile_size;A.push(I.slice(null,null,[Y,Y+this.tile_size],[se,se+this.tile_size]))}this.use_thumbnail&&U*q!==1&&A.push(await Er(M,{size:[P,C]}))}else A=[await Er(M,{size:[P,C]})];for(const U of A){const[,,q,ne]=U.dims,H=eA(U,this.encoder_patch_size),{padded:I,mask:S}=tA(H,this.max_num_patches);n.push(I),s.push(S),a.push([Math.floor(q/this.encoder_patch_size),Math.floor(ne/this.encoder_patch_size)])}i.push(F),c.push(G),u.push([P,C])}}const h={pixel_values:je(n,0),pixel_attention_mask:Gr(s,0),spatial_shapes:new K("int64",BigInt64Array.from(a.flat(),BigInt),[a.length,2])};return(t??this.return_row_col_info)&&(h.image_rows=i,h.image_cols=c,h.image_sizes=u),h}},nA=class extends ge{},op=class extends ge{post_process_panoptic_segmentation(...e){return Sv(...e)}post_process_instance_segmentation(...e){return Pv(...e)}},sA=class extends op{},aA=class extends op{},Rv=class extends ge{},oA=class extends Rv{},zv=class extends ge{},iA=class extends zv{},Gv=class extends ge{},lA=class extends Gv{},Uv=class extends ge{},cA=class extends Uv{},Vv=class extends ge{},uA=class extends Vv{},dA=class extends ap{},ip=class extends ge{post_process_object_detection(...e){return Il(...e)}},fA=class extends ip{},hA=class extends ip{},zt=336,pA=[2,3],{ceil:Af,floor:fs,sqrt:Sf}=Math,_A=class extends ge{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){const{num_img_tokens:r}=this.config;return fs((fs(t/zt)*fs(e/zt)+1)*r+1+(fs(t/zt)+1)*Sf(r))}get_resize_output_image_size(e,t){const r=this._num_crops,[n,s]=e.size;let a=n/s,i=1;for(;i*Math.ceil(i/a)<=r;)i+=1;i-=1;const c=Math.floor(i*336),u=Math.floor(c/a);return[c,u]}pad_image(e,t,r,n={}){const[s,a]=t,i=zt*Af(s/zt),c=zt*Af(a/zt),u=[1,1,1].map((h,p)=>(h-this.image_mean[p])/this.image_std[p]);return super.pad_image(e,t,{width:c,height:i},{center:!0,constant_values:u,...n})}async _call(e,{num_crops:t=null}={}){if(this._num_crops=t??=this.config.num_crops,t<4||Sf(t)%1!==0)throw new Error("num_crops must be a square number >= 4");Array.isArray(e)||(e=[e]);const r=e.length,n=await Promise.all(e.map(_=>this.preprocess(_))),s=n.map(_=>_.original_size),a=n.map(_=>_.reshaped_input_size),i=[];for(const{pixel_values:_}of n){_.unsqueeze_(0);const[m,w]=_.dims.slice(-2),b=await Er(_,{size:[zt,zt],mode:"bicubic"});if(t>0){const M=[],E=Sf(t),T=fs(w/E),C=fs(m/E);for(let A=0;A<E;++A)for(let F=0;F<E;++F){let G,v,j,U;A===E-1?(v=m-C,U=m):(v=A*C,U=(A+1)*C),F===E-1?(G=w-T,j=w):(G=F*T,j=(F+1)*T);const H=await ov(_,[v,G],[U,j],pA);M.push(H)}const P=await Er(je(M,0),{size:[zt,zt],mode:"bicubic"});i.push(je([b,P],0))}else i.push(b)}const c=Gr(i,0),u=a.map(_=>_.map(m=>zt*Af(m/zt))),h=new K("int64",u.flat(),[r,2]),p=u.map(([_,m])=>this.calc_num_image_tokens_from_image_size(m,_));return{pixel_values:c,original_sizes:s,reshaped_input_sizes:a,image_sizes:h,num_img_tokens:p}}},mA=class extends ge{get_resize_output_image_size(e,t){const{longest_edge:r}=t;if(r===void 0)throw new Error("size must contain 'longest_edge'");const[n,s]=e.size,a=Math.max(n,s)/r;let i=n,c=s;a>1&&(i=Math.floor(n/a),c=Math.floor(s/a));const{patch_size:u,spatial_merge_size:h}=this.config;if(!h)throw new Error("config must contain 'spatial_merge_size'");const p=u*h,_=Math.floor((i-1)/p)+1,m=Math.floor((c-1)/p)+1;return[_*p,m*p]}},gA=class extends ge{},wA=class extends ge{post_process_object_detection(...e){return Il(...e)}},Pf=class extends ge{reshape_input_points(e,t,r,n=!1){e=structuredClone(e);let s=fg(e);if(s.length===3)n||(s=[1,...s]),e=[e];else if(s.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 a=0;a<e.length;++a){const[i,c]=t[a],[u,h]=r[a],p=[h/c,u/i];for(let _=0;_<e[a].length;++_)for(let m=0;m<e[a][_].length;++m)for(let w=0;w<e[a][_][m].length;++w)e[a][_][m][w]*=p[w%2]}return new K("float32",Float32Array.from(e.flat(1/0)),s)}add_input_labels(e,t){let r=fg(e);if(r.length===2)r=[1,...r],e=[e];else if(r.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(r.some((n,s)=>n!==t.dims[s]))throw Error(`The first ${r.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new K("int64",e.flat(1/0).map(BigInt),r)}async _call(e,{input_points:t=null,input_labels:r=null,input_boxes:n=null}={}){const s=await super._call(e);if(t&&(s.input_points=this.reshape_input_points(t,s.original_sizes,s.reshaped_input_sizes)),r){if(!s.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");s.input_labels=this.add_input_labels(r,s.input_points)}return n&&(s.input_boxes=this.reshape_input_points(n,s.original_sizes,s.reshaped_input_sizes,!0)),s}async post_process_masks(e,t,r,{mask_threshold:n=0,binarize:s=!0,pad_size:a=null}={}){const i=[];a=a??this.pad_size??this.size;const c=[a.height,a.width];for(let u=0;u<t.length;++u){const h=t[u],p=r[u];let _=await Er(e[u],{mode:"bilinear",size:c});if(_=_.slice(null,null,[0,p[0]],[0,p[1]]),_=await Er(_,{mode:"bilinear",size:h}),s){const m=_.data,w=new Uint8Array(m.length);for(let b=0;b<m.length;++b)m[b]>n&&(w[b]=1);_=new K("bool",w,_.dims)}i.push(_)}return i}generate_crop_boxes(e,t,{crop_n_layers:r=0,overlap_ratio:n=512/1500,points_per_crop:s=32,crop_n_points_downscale_factor:a=1}={}){}},Wv=class extends ge{post_process_semantic_segmentation(...e){return Av(...e)}},yA=class extends Wv{},jv=class extends ge{post_process_semantic_segmentation(...e){return Av(...e)}},vA=class extends jv{},bA=class extends ge{},MA=class extends ge{pad_image(e,t,r,n={}){const[s,a,i]=t;return super.pad_image(e,t,{width:a+(r-a%r)%r,height:s+(r-s%r)%r},{mode:"symmetric",center:!1,constant_values:-1,...n})}},qv=class extends ge{},xA=class extends qv{},TA=class extends ge{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);const r=await Promise.all(e.map(a=>this.preprocess(a))),n=await Promise.all(t.map(a=>this.preprocess(a,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:Gr(r.map((a,i)=>je([a.pixel_values,n[i].pixel_values],0)),0),original_sizes:r.map(a=>a.original_size),reshaped_input_sizes:r.map(a=>a.reshaped_input_size)}}},EA=class extends ge{post_process_pose_estimation(e,t,{threshold:r=null}={}){const n=e.tolist(),[s,a,i,c]=e.dims,u=[];for(let h=0;h<s;++h){const p=n[h],_=t[h],m=[];for(let w=0;w<_.length;++w){const b=_[w],M=[],E=[],T=[],C=b.at(-2)/c,P=b.at(-1)/i;for(let A=0;A<p.length;++A){let[F,G]=[0,0],v=0,j=-1/0;const U=p[A];for(let ne=0;ne<U.length;++ne){const H=U[ne];for(let I=0;I<H.length;++I){const S=H[I];v+=S,j=Math.max(j,S),F+=(I+.5)*S,G+=ne*S}}if(r!=null&&j<r)continue;const q=[C*F/v,P*G/v];M.push(q),T.push(A),E.push(j)}m.push({bbox:b,scores:E,labels:T,keypoints:M})}u.push(m)}return u}},Hv=class extends ge{post_process_object_detection(...e){return Il(...e)}},kA=class extends Hv{},Pt=class{static async from_pretrained(e,t={}){const r=await jr(e,pv,!0,t),n=r.image_processor_type??r.feature_extractor_type;let s=Fv[n?.replace(/Fast$/,"")];return s||(n!==void 0&&be.warn(`Image processor type '${n}' not found, assuming base ImageProcessor. Please report this at ${Fl}.`),s=ge),new s(r)}},CA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;constructor(e,t,r){super(e,t,r);const{tasks_answer_post_processing_type:n,task_prompts_without_inputs:s,task_prompts_with_input:a}=this.image_processor.config;this.tasks_answer_post_processing_type=new Map(Object.entries(n??{})),this.task_prompts_without_inputs=new Map(Object.entries(s??{})),this.task_prompts_with_input=new Map(Object.entries(a??{})),this.regexes={quad_boxes:/(.+?)<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm,bboxes:/([^<]+)?<loc_(\d+)><loc_(\d+)><loc_(\d+)><loc_(\d+)>/gm},this.size_per_bin=1e3}construct_prompts(e){typeof e=="string"&&(e=[e]);const t=[];for(const r of e)if(this.task_prompts_without_inputs.has(r))t.push(this.task_prompts_without_inputs.get(r));else{for(const[n,s]of this.task_prompts_with_input)if(r.includes(n)){t.push(s.replaceAll("{input}",r).replaceAll(n,""));break}t.length!==e.length&&t.push(r)}return t}post_process_generation(e,t,r){const n=this.tasks_answer_post_processing_type.get(t)??"pure_text";e=e.replaceAll("<s>","").replaceAll("</s>","");let s;switch(n){case"pure_text":s=e;break;case"description_with_bboxes":case"bboxes":case"phrase_grounding":case"ocr":const a=n==="ocr"?"quad_boxes":"bboxes",i=e.matchAll(this.regexes[a]),c=[],u=[];for(const[h,p,..._]of i)c.push(p?p.trim():c.at(-1)??""),u.push(_.map((m,w)=>(Number(m)+.5)/this.size_per_bin*r[w%2]));s={labels:c,[a]:u};break;default:throw new Error(`Task "${t}" (of type "${n}") not yet implemented.`)}return{[t]:s}}async _call(e,t=null,r={}){if(!e&&!t)throw new Error("Either text or images must be provided");const n=await this.image_processor(e,r),s=t?this.tokenizer(this.construct_prompts(t),r):{};return{...n,...s}}},AA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,r){super(e,t,r),this.image_seq_length=this.config.image_seq_length;const{boi_token:n,image_token:s,eoi_token:a}=this.tokenizer.config;this.boi_token=n,this.image_token=s,this.eoi_token=a;const i=s.repeat(this.image_seq_length);this.full_image_sequence=`

${n}${i}${a}

`}async _call(e,t=null,r={}){typeof e=="string"&&(e=[e]);let n;return t&&(n=await this.image_processor(t,r),e=e.map(a=>a.replaceAll(this.boi_token,this.full_image_sequence))),{...this.tokenizer(e,r),...n}}},SA=class extends De{static image_processor_class=Pt;static feature_extractor_class=rr;static tokenizer_class=Oe;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,r){super(e,t,r),this.audio_seq_length=this.config.audio_seq_length,this.image_seq_length=this.config.image_seq_length;const{audio_token_id:n,boa_token:s,audio_token:a,eoa_token:i,image_token_id:c,boi_token:u,image_token:h,eoi_token:p}=this.tokenizer.config;this.audio_token_id=n,this.boa_token=s,this.audio_token=a;const _=a.repeat(this.audio_seq_length);this.full_audio_sequence=`

${s}${_}${i}

`,this.image_token_id=c,this.boi_token=u,this.image_token=h;const m=h.repeat(this.image_seq_length);this.full_image_sequence=`

${u}${m}${p}

`}async _call(e,t=null,r=null,n={}){typeof e=="string"&&(e=[e]);let s;r&&(s=await this.feature_extractor(r,n),e=e.map(c=>c.replaceAll(this.audio_token,this.full_audio_sequence)));let a;return t&&(a=await this.image_processor(t,n),e=e.map(c=>c.replaceAll(this.image_token,this.full_image_sequence))),{...this.tokenizer(e,n),...a,...s}}},PA=class extends De{static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,r){super(e,t,r),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;const{audio_token:n,boa_token:s,eoa_token:a,image_token:i,boi_token:c,eoi_token:u}=this.tokenizer.config;this.audio_token=n,this.boa_token=s,this.eoa_token=a,this.image_token=i,this.boi_token=c,this.eoi_token=u}static async from_pretrained(e,t={}){const[r,n,s]=await Promise.all([jr(e,_v,!0,t),Oe.from_pretrained(e,t),Jh(e,mv,!1,t)]),a={tokenizer:n};return r.image_processor&&(a.image_processor=new $v(r.image_processor)),r.feature_extractor&&(a.feature_extractor=new Tv(r.feature_extractor)),new this(r,a,s)}_compute_audio_num_tokens(e,t){const r=Math.round(t*20/1e3),n=Math.round(t*10/1e3),s=Math.floor(r/2);let a=Math.floor((e+s-r-1)/n)+1;if(a<=0)return 0;for(let i=0;i<2;++i)a=Math.floor((a-1)/2)+1;return Math.min(a,this.audio_seq_length)}async _call(e,t=null,r=null,n={}){typeof e=="string"&&(e=[e]);let s;if(t){s=await this.image_processor(t,n);const i=s.num_soft_tokens_per_image;let c=0;e=e.map(u=>u.replaceAll(this.image_token,()=>`

${this.boi_token}${this.image_token.repeat(i[c++])}${this.eoi_token}

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

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

`))}return{...this.tokenizer(e,n),...s,...a}}},lp=class extends De{static image_processor_class=Pt;static tokenizer_class=Oe;static image_token="<|image_pad|>";async _call(e,t=null,...r){Array.isArray(e)||(e=[e]);let n,s;if(t&&(n=await this.image_processor(t),s=n.image_grid_thw),s){let i=this.image_processor.config.merge_size**2,c=0;const u=this.constructor.image_token,h=s.tolist();e=e.map(p=>{for(;p.includes(u);){const _=Number(h[c++].reduce((m,w)=>m*w,1n));p=p.replace(u,"<|placeholder|>".repeat(Math.floor(_/i)))}return p.replaceAll("<|placeholder|>",u)})}return{...this.tokenizer(e),...n}}},FA=class extends lp{static image_token="<|image|>"},IA=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;static uses_processor_config=!0;_get_num_audio_features(e){const{hop_length:t}=this.feature_extractor.config.melspec_kwargs,{projector_window_size:r,projector_downsample_rate:n}=this.feature_extractor.config,s=Math.floor(r/n),a=Math.floor(e/t)+1,i=Math.floor(a/2);return Math.ceil(i/r)*s}async _call(e,t=null,r={}){if(Array.isArray(e))throw new Error("Batched inputs are not supported yet.");let n={};if(t){const{input_features:a}=await this.feature_extractor(t);n.input_features=a;const i=this._get_num_audio_features(t.length),c=new Uint8Array(i).fill(1);n.input_features_mask=new K("bool",c,[1,i]);const u=this.config.audio_token??"<|audio|>";if(!e.includes(u))throw new Error(`The input text does not contain the audio token ${u}.`);e=e.replaceAll(u,u.repeat(i))}return{...this.tokenizer(e,{add_special_tokens:!1,...r}),...n}}};function LA(e,t){const n=e.dims.at(-1)-1,s=e.tolist();s.fill(!1,0,1),s.fill(!1,n);const a=t.tolist();return s.map((i,c)=>i?c:null).filter(i=>i!==null).map(i=>a[i])}var OA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;async _call(e,t,r={}){const n=e?await this.image_processor(e,r):{};return{...t?this.tokenizer(t,r):{},...n}}post_process_grounded_object_detection(e,t,{box_threshold:r=.25,text_threshold:n=.25,target_sizes:s=null}={}){const{logits:a,pred_boxes:i}=e,c=a.dims[0];if(s!==null&&s.length!==c)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const u=a.dims.at(1),h=a.sigmoid(),p=h.max(-1).tolist(),_=i.tolist().map(w=>w.map(b=>Cv(b))),m=[];for(let w=0;w<c;++w){const b=s!==null?s[w]:null;b!==null&&(_[w]=_[w].map(P=>P.map((A,F)=>A*b[(F+1)%2])));const M=p[w],E=[],T=[],C=[];for(let P=0;P<u;++P){const A=M[P];if(A<=r)continue;const F=_[w][P],G=h[w][P];E.push(A),C.push(F);const v=LA(G.gt(n),t[w]);T.push(v)}m.push({scores:E,boxes:C,labels:this.batch_decode(T)})}return m}};function NA(e,t,r,n,s,a){let i="";for(let c=0;c<t;++c){for(let u=0;u<r;++u)i+=n+`<row_${c+1}_col_${u+1}>`+s.repeat(e);i+=`
`}return i+=`
${n}${a}`+s.repeat(e)+`${n}`,i}function BA(e,t,r,n){return`${t}${n}`+r.repeat(e)+`${t}`}function $A(e,t,r,n,s,a){return e===0&&t===0?BA(r,n,s,a):NA(r,e,t,n,s,a)}var Xg=class extends De{static image_processor_class=Pt;static tokenizer_class=Oe;static uses_processor_config=!0;fake_image_token="<fake_token_around_image>";image_token="<image>";global_img_token="<global-img>";async _call(e,t=null,r={}){r.return_row_col_info??=!0;let n;t&&(n=await this.image_processor(t,r)),Array.isArray(e)||(e=[e]);const s=n.rows??[new Array(e.length).fill(0)],a=n.cols??[new Array(e.length).fill(0)],i=this.config.image_seq_len,c=[],u=[];for(let p=0;p<e.length;++p){const _=e[p],m=s[p],w=a[p];c.push(ax(_,this.image_token));const b=m.map((T,C)=>$A(T,w[C],i,this.fake_image_token,this.image_token,this.global_img_token)),M=_.split(this.image_token);if(M.length===0)throw new Error("The image token should be present in the text.");let E=M[0];for(let T=0;T<b.length;++T)E+=b[T]+M[T+1];u.push(E)}return{...this.tokenizer(u),...n}}},DA=class extends De{static image_processor_class=Pt;static tokenizer_class=Oe;static uses_processor_config=!0;constructor(e,t,r){super(e,t,r),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:r="default"}={}){t?Array.isArray(t)||(t=[t]):t=await Promise.all(e.filter(M=>M.images).flatMap(M=>M.images).map(M=>yi.read(M)));const n=this.tokenizer,s=n.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0,chat_template:r}),a=M=>n.encode(M,{add_special_tokens:!1}),i=s.split(this.image_tag),c=i.length-1;if(t.length!==c)throw new Error(`Number of images provided (${t.length}) does not match number of "${this.image_tag}" image tags (${c})`);const[u,h,p]=n.convert_tokens_to_ids([this.image_tag,this.image_start_tag,this.image_end_tag]);let _=a(i[0]),m=new Array(_.length).fill(!1);for(let M=1;M<i.length;++M){const E=new Array(this.num_image_tokens).fill(u),T=a(i[M]);_=Tr(_,[h],E,[p],T);const C=new Array(this.num_image_tokens).fill(!0);m=Tr(m,[!1],C,[!1],new Array(T.length).fill(!1))}const w=[1,_.length],b={input_ids:new K("int64",_,w),attention_mask:new K("int64",new Array(_.length).fill(1),w),images_seq_mask:new K("bool",m,w),images_emb_mask:new K("bool",new Array(c*this.num_image_tokens).fill(!0),[1,c,this.num_image_tokens])};if(t&&t.length>0){const M=await this.image_processor(t);return M.pixel_values.unsqueeze_(0),{...b,...M}}return b}},RA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;async _call(e=null,t=null,r={}){if(!e&&!t)throw new Error("Either text or images must be provided");const n=e?this.tokenizer(e,r):{},s=t?await this.image_processor(t,r):{};return{...n,...s}}},zA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;async _call(e,t=null,r={}){const{image_rows:n,image_cols:s,image_sizes:a,...i}=await this.image_processor(e,{...r,return_row_col_info:!0});if(t){const c=this.config.image_token??"<image>",{tile_size:u=512,downsample_factor:h=2,encoder_patch_size:p=16,use_thumbnail:_=!0}=this.image_processor.config,m=C=>Math.ceil(Math.floor(C/p)/h),w=m(u)**2,b=this.config.image_start_token??"<|image_start|>",M=this.config.image_end_token??"<|image_end|>",E=this.config.image_thumbnail??"<|img_thumbnail|>";Array.isArray(t)||(t=[t]);let T=0;t=t.map(C=>{const P=C.split(c);return P[0]+P.slice(1).map(A=>{const F=T++,[G,v]=a[F],j=n[F],U=s[F],q=m(G)*m(v);let ne=b;if(j>1||U>1){const H=c.repeat(w);for(let I=0;I<j;++I)for(let S=0;S<U;++S)ne+=`<|img_row_${I+1}_col_${S+1}|>`+H;_&&(ne+=E+c.repeat(q))}else ne+=c.repeat(q);return ne+M+A}).join("")})}return{...i,...t?this.tokenizer(t,r):{}}}},GA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;static uses_processor_config=!0;async _call(e,t=null,r={}){const n=await this.image_processor(e,r);if(t){const[a,i]=n.pixel_values.dims.slice(-2),{image_token:c,patch_size:u,num_additional_image_tokens:h}=this.config,p=Math.floor(a/u)*Math.floor(i/u)+h;t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let _=0;_<t.length;++_)t[_]=t[_].replace(c,c.repeat(p))}const s=t?this.tokenizer(t,r):{};return{...n,...s}}},Jg={char:["char_decode",1],bpe:["bpe_decode",2],wp:["wp_decode",102]},UA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;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(!Jg.hasOwnProperty(t))throw new Error(`Format ${t} is not supported.`);const[r,n]=Jg[t],s=this[r].bind(this),[a,i]=e.dims,c=[],u=[],h=e.tolist();for(let _=0;_<a;++_){const m=h[_],w=[],b=[];for(let E=1;E<i;++E){const[T,C]=pt(Is(m[E]));if(b.push(T),C==n)break;w.push(C)}const M=b.length>0?b.reduce((E,T)=>E*T,1):0;u.push(w),c.push(M)}return[s(u),c]}char_decode(e){return this.char_tokenizer.batch_decode(e).map(t=>t.replaceAll(" ",""))}bpe_decode(e){return this.bpe_tokenizer.batch_decode(e)}wp_decode(e){return this.wp_tokenizer.batch_decode(e).map(t=>t.replaceAll(" ",""))}batch_decode([e,t,r]){const[n,s]=this._decode_helper(e,"char"),[a,i]=this._decode_helper(t,"bpe"),[c,u]=this._decode_helper(r,"wp"),h=[],p=[];for(let _=0;_<n.length;++_){const[m,w]=pt([s[_],i[_],u[_]]);h.push([n[_],a[_],c[_]][w]),p.push(m)}return{generated_text:h,scores:p,char_preds:n,bpe_preds:a,wp_preds:c}}static async from_pretrained(...e){const t=await super.from_pretrained(...e),r=await Oe.from_pretrained("Xenova/gpt2"),n=await Oe.from_pretrained("Xenova/bert-base-uncased");return t.components={image_processor:t.image_processor,char_tokenizer:t.tokenizer,bpe_tokenizer:r,wp_tokenizer:n},t}async _call(e,t=null){const r=await this.image_processor(e);return t&&(r.labels=this.tokenizer(t).input_ids),r}},VA=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e){return await this.feature_extractor(e)}},WA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt},hs="<image>";function jA(e,t,r,n,s){return`${n.repeat(r*s)}${t}${e}
`}var qA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;static uses_processor_config=!1;async _call(e,t=null,r={}){t||(be.warn("You are using PaliGemma without a text prefix. It will perform as a picture-captioning model."),t=""),Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);const n=this.tokenizer.bos_token,s=this.image_processor.config.image_seq_length;let a;t.some(u=>u.includes(hs))?a=t.map(u=>{const h=u.replaceAll(hs,hs.repeat(s)),p=h.lastIndexOf(hs),_=p===-1?0:p+hs.length;return h.slice(0,_)+n+h.slice(_)+`
`}):(be.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(u=>jA(u,n,s,hs,e.length)));const i=this.tokenizer(a,r);return{...await this.image_processor(e,r),...i}}},Kg="<|image|>",HA=/<\|image_\d+\|>/g,QA=class extends De{static image_processor_class=Pt;static tokenizer_class=Oe;async _call(e,t=null,{padding:r=!0,truncation:n=!0,num_crops:s=null}={}){Array.isArray(e)||(e=[e]);let a,i;if(t){i=await this.image_processor(t,{num_crops:s});const{num_img_tokens:c}=i,u=e.map((p,_)=>p.split(HA).join(Kg.repeat(c[_])));a=this.tokenizer(u,{padding:r,truncation:n});const h=this.tokenizer._tokenizer.token_to_id(Kg);a.input_ids.map_(p=>p==h?-p:p)}else a=this.tokenizer(e);return{...a,...i}}},YA=class extends De{static tokenizer_class=Oe;static image_processor_class=Pt;static uses_processor_config=!0;async _call(e,t=null,r={}){const n=await this.image_processor(e,r);if(t){const[a,i]=n.pixel_values.dims.slice(-2),{image_token:c,image_break_token:u,image_end_token:h,patch_size:p,spatial_merge_size:_}=this.config,m=p*_,w=Math.floor(a/m),b=Math.floor(i/m);t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let M=0;M<t.length;++M){const E=c.repeat(b),T=E+u,C=E+h,P=T.repeat(w-1)+C;t[M]=t[M].replace(c,P)}}const s=t?this.tokenizer(t,r):{};return{...n,...s}}},XA=class extends De{static feature_extractor_class=Ev;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}},Qv=class extends lp{},JA=class extends Qv{},Yv=class extends De{static image_processor_class=Pt;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)}},Xv=class extends Yv{},KA=class extends Xv{},ZA=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e){return await this.feature_extractor(e)}},eS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;static uses_processor_config=!0;async _call(e,t=null,r={}){if(Array.isArray(e))throw new Error("Batched inputs are not supported yet.");let n={};if(t){const a=t.length,{input_features:i}=await this.feature_extractor(t,{...r,max_length:a}),c=Math.round(a/this.config.encoder_ds_factor+1e-4),u=1+Math.ceil(c/this.config.stack_factor);n.audio_token_len=[u],n.audio_values=i;const h=this.config.audio_placeholder;if(!e.includes(h))throw new Error(`The input text does not contain the image token ${h}.`);e=e.replaceAll(h,h.repeat(u))}return{...this.tokenizer(e,{add_special_tokens:!1,...r}),...n}}},ji="[AUDIO]",tS="[BEGIN_AUDIO]",rS=375;function nS(e,t){const r=[];for(let n=0;n<e.length;n+=t)r.push(e.subarray(n,Math.min(n+t,e.length)));return r}var sS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;static uses_processor_config=!1;async _call(e,t=null,r={}){if(Array.isArray(e))throw new Error("Batched inputs are not supported yet.");const n={};if(t){if(!e.includes(ji))throw new Error(`The input text does not contain the audio token ${ji}.`);Array.isArray(t)||(t=[t]);const a=e.split(ji),i=a.length-1;if(i!==t.length)throw new Error(`The number of audio inputs (${t.length}) does not match the number of audio tokens in the text (${i}).`);const c=this.feature_extractor.config.n_samples,u=t.map(w=>nS(w,c)),h=u.map(w=>w.length),p=u.flat(),_=(await Promise.all(p.map(w=>this.feature_extractor(w,r)))).map(w=>w.input_features);n.audio_values=_.length>1?je(_,0):_[0];let m=a[0];for(let w=0;w<h.length;++w){m+=tS;for(let b=0;b<h[w];++b)m+=ji.repeat(rS);m+=a[w+1]}e=m}return{...this.tokenizer(e,{add_special_tokens:!1,...r}),...n}}},Zg=32,Ff=6,qi=8,aS=10,oS=32,iS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;static uses_processor_config=!1;get num_mel_frames_first_audio_chunk(){return(Ff+1)*qi}get num_samples_first_audio_chunk(){const{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(){const{hop_length:e,n_fft:t}=this.feature_extractor.config;return qi*e+t}get num_right_pad_tokens(){return Ff+1+aS}get audio_length_per_tok(){return qi}get raw_audio_length_per_tok(){return qi*this.feature_extractor.config.hop_length}async _call(e,{is_streaming:t=!1,is_first_audio_chunk:r=!0}={}){if(Et(e,"VoxtralRealtimeProcessor"),!t&&!r)throw new Error("In non-streaming mode (`is_streaming=false`), `is_first_audio_chunk` must be `true`.");if(r)if(t){const n=Zg*this.raw_audio_length_per_tok,s=new Float32Array(n+e.length);s.set(e,n);const a=await this.feature_extractor(s,{center:!0}),c=1+(Zg+Ff),u=new BigInt64Array(c).fill(BigInt(oS));return u[0]=1n,{input_ids:new K("int64",u,[1,c]),...a}}else{const n=this.num_right_pad_tokens*this.raw_audio_length_per_tok,s=new Float32Array(e.length+n);return s.set(e),await this.feature_extractor(s,{center:!0})}else return await this.feature_extractor(e,{center:!1})}},lS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e){return await this.feature_extractor(e)}},cS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e){return await this.feature_extractor(e)}},uS=class extends De{static tokenizer_class=Oe;static feature_extractor_class=rr;async _call(e){return await this.feature_extractor(e)}};async function dS(e,t){return await jr(e,"config.json",!0,t)}function ms(e){const t={};let r={};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":r=ms(e.text_config);break;case"moondream1":r=ms(e.phi_config);break;case"musicgen":r=ms(e.decoder);break;case"multi_modality":r=ms(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";const{num_hidden_layers:s,num_attention_heads:a,hidden_size:i}=e.encoder_config;r={num_encoder_layers:s,num_encoder_heads:a,encoder_hidden_size:i,encoder_dim_kv:e.head_dim};break;case"vision-encoder-decoder":const c=ms(e.decoder),u="num_decoder_layers"in c,h=xt(e,["model_type","is_encoder_decoder"]);return u?(h.num_decoder_layers=c.num_decoder_layers,h.num_decoder_heads=c.num_decoder_heads,h.decoder_hidden_size=c.decoder_hidden_size,h.num_encoder_layers=c.num_encoder_layers,h.num_encoder_heads=c.num_encoder_heads,h.encoder_hidden_size=c.encoder_hidden_size):(h.num_layers=c.num_layers,h.num_heads=c.num_heads,h.hidden_size=c.hidden_size),h}const n={...r,...xt(e,["model_type","multi_query","is_encoder_decoder"])};for(const s in t)n[s]=e[t[s]];return n}function Ll(e,t){e instanceof hh||(e=new hh(e));const r=t?.prefix??"past_key_values",n=r==="present"?"present":"past",s=new Set;if(["lfm2","lfm2_moe"].includes(e.model_type)){const{layer_types:a}=e;for(let i=0;i<a.length;++i)if(a[i]==="full_attention")s.add(`${r}.${i}.key`),s.add(`${r}.${i}.value`);else if(a[i]==="conv")s.add(`${n}_conv.${i}`);else throw new Error(`Unsupported layer type: ${a[i]}`);return s}else if(["granitemoehybrid","falcon_h1","nemotron_h"].includes(e.model_type)){const a=e,i=a.layer_types??a.layers_block_type,c=a.num_hidden_layers??i?.length;for(let u=0;u<c;++u)(!i||i[u]==="mamba")&&(s.add(`${n}_conv.${u}`),s.add(`${n}_ssm.${u}`)),(!i||i[u]==="attention")&&(s.add(`${r}.${u}.key`),s.add(`${r}.${u}.value`));return s}else if(["qwen3_next","qwen3_5_text","qwen3_5_moe_text","olmo_hybrid"].includes(e.model_type)){const{layer_types:a}=e;for(let i=0;i<a.length;++i)if(a[i]==="full_attention")s.add(`${r}.${i}.key`),s.add(`${r}.${i}.value`);else if(a[i]==="linear_attention")e.model_type==="olmo_hybrid"?(s.add(`${n}_conv.${i}.key`),s.add(`${n}_conv.${i}.value`),s.add(`${n}_conv.${i}.query`)):s.add(`${n}_conv.${i}`),s.add(`${n}_recurrent.${i}`);else throw new Error(`Unsupported layer type: ${a[i]}`);return s}else if(["gemma4","gemma4_text"].includes(e.model_type)){const a=e.model_type==="gemma4"?e.text_config:e,i=a.num_hidden_layers,c=a.num_kv_shared_layers??0,u=i-c;for(let h=0;h<u;++h)s.add(`${r}.${h}.key`),s.add(`${r}.${h}.value`);return s}else if(["lfm2_vl","qwen3_5","qwen3_5_moe","voxtral_realtime"].includes(e.model_type)){let a;return e.model_type==="voxtral_realtime"&&t?.session_name==="audio_encoder"?a=e.audio_config:a=e.text_config,Ll(a,t)}return fS(e,{prefix:r})}function fS(e,{prefix:t="past_key_values"}={}){const r=new Set,n=e.normalized_config;if(n.is_encoder_decoder&&"num_encoder_heads"in n&&"num_decoder_heads"in n)for(let s=0;s<n.num_decoder_layers;++s)r.add(`${t}.${s}.encoder.key`),r.add(`${t}.${s}.encoder.value`),r.add(`${t}.${s}.decoder.key`),r.add(`${t}.${s}.decoder.value`);else if(n.multi_query)for(let s=0;s<n.num_layers;++s)r.add(`${t}.${s}.key_value`);else for(let s=0;s<n.num_layers;++s)r.add(`${t}.${s}.key`),r.add(`${t}.${s}.value`);return r}var hh=class ph{model_type=null;is_encoder_decoder=!1;max_position_embeddings;"transformers.js_config";constructor(t){Object.assign(this,t),this.normalized_config=ms(this)}static async from_pretrained(t,{progress_callback:r=null,config:n=null,cache_dir:s=null,local_files_only:a=!1,revision:i="main"}={}){n&&!(n instanceof ph)&&(n=new ph(n));const c=n??await dS(t,{progress_callback:r,config:n,cache_dir:s,local_files_only:a,revision:i});return new this(c)}},wl=class{static async from_pretrained(...e){return hh.from_pretrained(...e)}};function Jv(e,t,r){return e?typeof e=="object"&&e!==null?e.hasOwnProperty(t)?+e[t]:e.hasOwnProperty(r)?+e[r]:0:+e:0}function Kv(e,t){const r=[];for(let n=0;n<t;++n)r.push(`${e}_data${n===0?"":"_"+n}`);return r}async function hS(e,t,r,n){const s=`${t}${n}.onnx`,a=`${r.subfolder??""}/${s}`;return await gl(e,a,!0,r,ve.IS_NODE_ENV)}async function pS(e,t,r,n,s,a={}){const i=`${t}${r}.onnx`,c=ve.IS_NODE_ENV;let u=[];const h=Jv(s,i,t);if(h>0){if(h>Fg)throw new Error(`The number of external data chunks (${h}) exceeds the maximum allowed value (${Fg}).`);const p=Kv(i,h);for(const _ of p){const m=`${n.subfolder??""}/${_}`;u.push(new 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n={...sn[Z.VoxtralRealtime].text_only_sessions};return r||(n.audio_encoder="audio_encoder"),n},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 $S(e,t,r={}){const n=sn[e]??sn.default;return{sessions:n.sessions(t,r,r.textOnly??!1),cache_sessions:n.cache_sessions,optional_configs:n.optional_configs}}function DS(e,{warn:t=!0}={}){const r=e.architectures||[];for(const n of r){const s=zr.get(n);if(s!==void 0)return s}if(e.model_type){const n=zr.get(e.model_type);if(n!==void 0)return n;for(const s of Object.values(ys))if(s.has(e.model_type)){const a=zr.get(s.get(e.model_type));if(a!==void 0)return a}}if(t){const n=r.length>0?r.join(", "):"(none)";be.warn(`[resolve_model_type] Architecture(s) not found in MODEL_TYPE_MAPPING: [${n}] for model type '${e.model_type}'. Falling back to EncoderOnly (single model.onnx file). If you encounter issues, please report at: ${Fl}`)}return Z.EncoderOnly}function RS(e,{config:t=null,cache_dir:r=null,local_files_only:n=!1,revision:s="main"}={}){if(t!==null)return wl.from_pretrained(e,{config:t,cache_dir:r,local_files_only:n,revision:s});const a=JSON.stringify([e,r,n,s]);return Wy(a,()=>wl.from_pretrained(e,{config:t,cache_dir:r,local_files_only:n,revision:s}))}async function zS(e,{config:t=null,dtype:r=null,device:n=null,model_file_name:s=null}={}){t=await RS(e,{config:t});const a=["config.json"],i=t["transformers.js_config"]??{},c=i.use_external_data_format,u="onnx",h=n??i.device;let p=r??i.dtype;const _=DS(t),m=(M,E=null)=>{E=E??M;const T=rv(h,M),C=nv(p,M,T),P=uh[C]??"",A=`${E}${P}.onnx`,F=`${u}/${A}`;a.push(F);const G=Jv(c,A,M);for(const v of Kv(A,G)){const j=`${u}/${v}`;a.push(j)}},{sessions:w,optional_configs:b}=$S(_,t,{model_file_name:s});for(const[M,E]of Object.entries(w))m(M,E);if(b)for(const M of Object.values(b))a.push(M);return a}var ys=null;function GS(e){ys=e}function _h(e){if(e instanceof K)return e;if(e.length===0)throw Error("items must be non-empty");if(Array.isArray(e[0])){if(e.some(t=>t.length!==e[0].length))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' and/or 'truncation=True' to have batched tensors with the same length.");return new K("int64",BigInt64Array.from(e.flat().map(t=>BigInt(t))),[e.length,e[0].length])}else return new K("int64",BigInt64Array.from(e.map(t=>BigInt(t))),[1,e.length])}function s0(e){return new K("bool",[e],[1])}var ew={[Z.DecoderOnly]:{can_generate:!0,forward:Ur,prepare_inputs:mi},[Z.DecoderOnlyWithoutHead]:{can_generate:!1,forward:Ur,prepare_inputs:mi},[Z.Seq2Seq]:{can_generate:!0,forward:Hi,prepare_inputs:vl},[Z.Vision2Seq]:{can_generate:!0,forward:Hi,prepare_inputs:vl},[Z.Musicgen]:{can_generate:!0,forward:Hi},[Z.EncoderDecoder]:{can_generate:!1,forward:Hi},[Z.ImageTextToText]:{can_generate:!0,forward:jS,prepare_inputs:Qi},[Z.AudioTextToText]:{can_generate:!0,forward:WS,prepare_inputs:Qi},[Z.ImageAudioTextToText]:{can_generate:!0,prepare_inputs:Qi},[Z.Phi3V]:{can_generate:!0,prepare_inputs:Qi},[Z.MultiModality]:{can_generate:!0},[Z.AutoEncoder]:{can_generate:!1,forward:US},[Z.Chatterbox]:{can_generate:!0,forward:ln},[Z.VoxtralRealtime]:{can_generate:!0,prepare_inputs:mi},default:{can_generate:!1,forward:ln}};function tw(e,t){let r=zr.get(e),n=!1;const s=t?.architectures?.[0];if(s&&s!==e&&e?.endsWith("ForCausalLM")&&s.endsWith("ForConditionalGeneration")){const c=zr.get(s);c!==void 0&&(r=c,n=!0)}const a=ew[r]??ew.default,i=sn[r]??sn.default;return{typeConfig:{...a,...i},textOnly:n,modelType:r}}var zr=new Map,up=new Map,Es=new Map,O=class extends Yt{main_input_name="input_ids";forward_params=["input_ids","attention_mask"];_return_dict_in_generate_keys=null;constructor(e,t,r){super(),this.config=e,this.sessions=t,this.configs=r;const n=Es.get(this.constructor),{typeConfig:s}=tw(n,e);this.can_generate=s.can_generate,this._forward=s.forward,this._prepare_inputs_for_generation=s.prepare_inputs,this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){const e=[];for(const t of Object.values(this.sessions))e.push(t.release?.());return await Promise.all(e)}static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:n=null,local_files_only:s=!1,revision:a="main",model_file_name:i=null,subfolder:c="onnx",device:u=null,dtype:h=null,use_external_data_format:p=null,session_options:_={}}={}){const m={progress_callback:t,config:r,cache_dir:n,local_files_only:s,revision:a,model_file_name:i,subfolder:c,device:u,dtype:h,use_external_data_format:p,session_options:_},w=Es.get(this);r=m.config=await wl.from_pretrained(e,m);const{typeConfig:b,textOnly:M,modelType:E}=tw(w,r);if(E===void 0){const A=w??r?.model_type;A!=="custom"&&be.warn(`Model type for '${A}' not found, assuming encoder-only architecture. Please report this at ${Fl}.`)}if(t&&!(t instanceof ug)){const A={};try{const F=await zS(e,{config:r,dtype:h,device:u,model_file_name:i});(await Promise.all(F.map(v=>Xh(e,v,m)))).forEach((v,j)=>{if(v.exists){const U=F[j]==="config.json";A[F[j]]={loaded:U?v.size??0:0,total:v.size??0}}})}catch(F){be.warn(`Unable to fetch model file metadata for total progress tracking: ${F}`)}Object.keys(A).length>0&&(m.progress_callback=new ug(t,A))}const T=b.sessions(r,m,M),C=[mS(e,T,m,b.cache_sessions)];b.optional_configs&&C.push(HS(e,b.optional_configs,m));const P=await Promise.all(C);return new this(r,...P)}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,r=null){const n=new yl;if(e.repetition_penalty!==null&&e.repetition_penalty!==1&&n.push(new ES(e.repetition_penalty)),e.no_repeat_ngram_size!==null&&e.no_repeat_ngram_size>0&&n.push(new TS(e.no_repeat_ngram_size)),e.bad_words_ids!==null&&n.push(new AS(e.bad_words_ids,e.eos_token_id)),e.min_length!==null&&e.eos_token_id!==null&&e.min_length>0&&n.push(new kS(e.min_length,e.eos_token_id)),e.min_new_tokens!==null&&e.eos_token_id!==null&&e.min_new_tokens>0&&n.push(new CS(t,e.min_new_tokens,e.eos_token_id)),e.forced_bos_token_id!==null&&n.push(new vS(e.forced_bos_token_id)),e.forced_eos_token_id!==null&&n.push(new bS(e.max_length,e.forced_eos_token_id)),e.suppress_tokens!==null&&n.push(new MS(e.suppress_tokens)),e.begin_suppress_tokens!==null){const s=t>1||e.forced_bos_token_id===null?t:t+1;n.push(new e0(e.begin_suppress_tokens,s))}return e.guidance_scale!==null&&e.guidance_scale>1&&n.push(new SS(e.guidance_scale)),e.temperature===0&&e.do_sample&&(be.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&&n.push(new PS(e.temperature)),r!==null&&n.extend(r),n}_prepare_generation_config(e,t,r=t0){const n={...this.config};for(const a of["decoder","generator","text_config"])a in n&&Object.assign(n,n[a]);const s=new r(n);return Object.assign(s,this.generation_config??{}),e&&Object.assign(s,e),t&&Object.assign(s,xt(t,Object.getOwnPropertyNames(s))),s}_get_stopping_criteria(e,t=null){const r=new r0;return e.max_length!==null&&r.push(new FS(e.max_length,this.config.max_position_embeddings??null)),e.eos_token_id!==null&&r.push(new IS(e.eos_token_id)),t&&r.extend(t),r}_validate_model_class(){if(!this.can_generate){const e=[ys.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,ys.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,ys.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,ys.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES].filter(Boolean),t=Es.get(this.constructor),r=new Set,n=this.config.model_type;for(const a of e){const i=a?.get(n);i&&r.add(i)}let s=`The current model class (${t}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw r.size>0&&(s+=` Please use the following class instead: ${[...r].join(", ")}`),Error(s)}}prepare_inputs_for_generation(...e){if(!this._prepare_inputs_for_generation)throw new Error("prepare_inputs_for_generation is not implemented for this model.");return this._prepare_inputs_for_generation(this,...e)}_update_model_kwargs_for_generation({generated_input_ids:e,outputs:t,model_inputs:r,is_encoder_decoder:n}){return r.past_key_values=mh(t,r.past_key_values),r.input_ids=new K("int64",e.flat(),[e.length,1]),n?"decoder_attention_mask"in r&&(r.decoder_attention_mask=je([r.decoder_attention_mask,Ot([r.decoder_attention_mask.dims[0],1])],1)):r.attention_mask=je([r.attention_mask,Ot([r.attention_mask.dims[0],1])],1),r.position_ids=null,r}_prepare_model_inputs({inputs:e,bos_token_id:t,model_kwargs:r}){const n=xt(r,this.forward_params),s=this.main_input_name;if(s in n){if(e)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else n[s]=e;return{inputs_tensor:n[s],model_inputs:n,model_input_name:s}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:e,model_inputs:t,model_input_name:r,generation_config:n}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!t.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:a,pixel_values:i,attention_mask:c,...u}=t,h=await this._prepare_inputs_embeds(t);t={...u,...xt(h,["inputs_embeds","attention_mask"])}}let{last_hidden_state:s}=await ln(this,t);if(n.guidance_scale!==null&&n.guidance_scale>1)s=je([s,dh(s,0)],0),"attention_mask"in t&&(t.attention_mask=je([t.attention_mask,cv(t.attention_mask)],0));else if(t.decoder_input_ids){const a=_h(t.decoder_input_ids).dims[0];if(a!==s.dims[0]){if(s.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${s.dims[0]}) than the decoder inputs (${a}).`);s=je(Array.from({length:a},()=>s),0)}}return t.encoder_outputs=s,t}_prepare_decoder_input_ids_for_generation({batch_size:e,model_input_name:t,model_kwargs:r,decoder_start_token_id:n,bos_token_id:s,generation_config:a}){let{decoder_input_ids:i,...c}=r;if(!(i instanceof K)){if(i)Array.isArray(i[0])||(i=Array.from({length:e},()=>i));else if(n??=s,this.config.model_type==="musicgen")i=Array.from({length:e*this.config.decoder.num_codebooks},()=>[n]);else if(Array.isArray(n)){if(n.length!==e)throw new Error(`\`decoder_start_token_id\` expcted to have length ${e} but got ${n.length}`);i=n}else i=Array.from({length:e},()=>[n]);i=_h(i)}return c.decoder_attention_mask=iv(i),{input_ids:i,model_inputs:c}}async generate({inputs:e=null,generation_config:t=null,logits_processor:r=null,stopping_criteria:n=null,streamer:s=null,...a}){this._validate_model_class(),t=this._prepare_generation_config(t,a);let{inputs_tensor:i,model_inputs:c,model_input_name:u}=this._prepare_model_inputs({inputs:e,model_kwargs:a});const h=this.config.is_encoder_decoder;h&&("encoder_outputs"in c||(c=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:i,model_inputs:c,model_input_name:u,generation_config:t})));let p;h?{input_ids:p,model_inputs:c}=this._prepare_decoder_input_ids_for_generation({batch_size:c[u].dims.at(0),model_input_name:u,model_kwargs:c,decoder_start_token_id:t.decoder_start_token_id,bos_token_id:t.bos_token_id,generation_config:t}):p=c[u];let _=p.dims.at(-1);t.max_new_tokens!==null&&(t.max_length=_+t.max_new_tokens);const m=this._get_logits_processor(t,_,r),w=this._get_stopping_criteria(t,n),b=c[u].dims.at(0),M=Nl.getSampler(t),E=new Array(b).fill(0),T=p.tolist();s&&s.put(T);let C,P={},A={};for(;;){if(c=this.prepare_inputs_for_generation(T,c,t),C=await this.forward(c),t.return_dict_in_generate)if(t.output_attentions){const I=VS(C);for(const S in I)S in P||(P[S]=[]),P[S].push(I[S])}else this._return_dict_in_generate_keys&&Object.assign(A,xt(C,this._return_dict_in_generate_keys));const U=C.logits.slice(null,-1,null).to("float32"),q=m(T,U),ne=[];for(let I=0;I<q.dims.at(0);++I){const S=q[I],D=await M(S);for(const[Y,se]of D){const N=BigInt(Y);E[I]+=se,T[I].push(N),ne.push([N]);break}}if(s&&s.put(ne),w(T).every(I=>I))break;c=this._update_model_kwargs_for_generation({generated_input_ids:ne,outputs:C,model_inputs:c,is_encoder_decoder:h})}s&&s.end();const F=new K("int64",T.flat(),[T.length,T[0].length]),G=mh(C,c.past_key_values),v=new Set(Object.values(G));for(const U of Object.values(C))U.location==="gpu-buffer"&&!v.has(U)&&U.dispose();return"past_key_values"in a||t.return_dict_in_generate||await G.dispose(),t.return_dict_in_generate?{sequences:F,past_key_values:G,...P,...A}:F}async _encode_input(e,t,r){if(!Object.hasOwn(this.sessions,e))throw new Error(`Model does not have a ${e} session.`);const n=this.sessions[e];return(await Pe(n,xt(t,n.inputNames)))[r]}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 Hi(e,t){let{encoder_outputs:r,input_ids:n,decoder_input_ids:s,decoder_attention_mask:a,...i}=t;if(!r){const c=xt(t,e.sessions.model.inputNames);r=(await ln(e,c)).last_hidden_state}return i.input_ids=s,i.encoder_hidden_states=r,e.sessions.decoder_model_merged.inputNames.includes("encoder_attention_mask")&&(i.encoder_attention_mask=t.attention_mask),a&&!i.attention_mask&&(i.attention_mask=a),await Ur(e,i,!0)}async function ln(e,t){const r=e.sessions.model,n=xt(t,r.inputNames);if(r.inputNames.includes("inputs_embeds")&&!n.inputs_embeds){if(!t.input_ids)throw new Error("Both `input_ids` and `inputs_embeds` are missing in the model inputs.");n.inputs_embeds=await e.encode_text({input_ids:t.input_ids})}if(r.inputNames.includes("token_type_ids")&&!n.token_type_ids){if(!n.input_ids)throw new Error("Both `input_ids` and `token_type_ids` are missing in the model inputs.");n.token_type_ids=cv(n.input_ids)}if(r.inputNames.includes("pixel_mask")&&!n.pixel_mask){if(!n.pixel_values)throw new Error("Both `pixel_values` and `pixel_mask` are missing in the model inputs.");const s=n.pixel_values.dims;n.pixel_mask=Ot([s[0],s[2],s[3]])}return await Pe(r,n)}async function US(e,t){const r=await e.encode(t);return await e.decode(r)}function mh(e,t){const r=Object.create(null);for(const n in e)if(n.startsWith("present")){const s=n.replace("present_ssm","past_ssm").replace("present_conv","past_conv").replace("present_recurrent","past_recurrent").replace("present","past_key_values");n.includes("encoder")&&t?r[s]=t[s]:r[s]=e[n]}return t?(t.update(r),t):new cp(r)}function VS(e){const t={};for(const r of["cross_attentions","encoder_attentions","decoder_attentions"])for(const n in e)n.startsWith(r)&&(r in t||(t[r]=[]),t[r].push(e[n]));return t}function a0(e,t){return e.map(r=>typeof r=="number"?r:t[r]??0)}function dp(e,t,r){if(r&&Object.keys(r).length>0)return Object.assign(t,r),r;const n=e.sessions.decoder_model_merged??e.sessions.model,s=(t[e.main_input_name]??t.attention_mask)?.dims?.[0]??1,a=Ll(e.config),i=e.config?.normalized_config?.num_heads,c={batch_size:s};typeof i=="number"&&(c["batch_size x num_heads"]=s*i);const u=Object.create(null);for(const h of n.inputMetadata){if(!a.has(h.name))continue;const p=a0(h.shape,c),_=p.reduce((b,M)=>b*M,1),m=wi[h.type],w=new K(h.type,new m(_),p);t[h.name]=w,u[h.name]=w}return r?(r.update(u),r):new cp(u)}async function Ur(e,t,r=!1){const n=e.sessions[r?"decoder_model_merged":"model"],{past_key_values:s,...a}=t;if(n.inputNames.includes("use_cache_branch")&&(a.use_cache_branch=s0(s!=null&&Object.keys(s).length>0)),n.inputNames.includes("position_ids")&&a.attention_mask&&!a.position_ids){const c=["paligemma","gemma3_text","gemma3"].includes(e.config.model_type)?1:0;a.position_ids=qS(a,s,c)}n.inputNames.includes("num_logits_to_keep")&&!a.num_logits_to_keep&&(a.num_logits_to_keep=new K("int64",[0n],[])),dp(e,a,s);const i=xt(a,n.inputNames);return await Pe(n,i)}async function o0(e,{encode_function:t,merge_function:r,modality_input_names:n,modality_output_name:s,input_ids:a=null,attention_mask:i=null,position_ids:c=null,inputs_embeds:u=null,past_key_values:h=null,generation_config:p=null,logits_processor:_=null,...m}){if(!u){u=await e.encode_text({input_ids:a,...m});const b=xt(m,n);if(Object.keys(b).length>0){if(a.dims[1]!==1){const M=await t({...b,...m});({inputs_embeds:u,attention_mask:i}=r({[s]:M,inputs_embeds:u,input_ids:a,attention_mask:i}))}else if(h&&a.dims[1]===1){const M=a.dims[1],E=h.get_seq_length();i=je([Ot([a.dims[0],E]),i.slice(null,[i.dims[1]-M,i.dims[1]])],1)}}}if(!c&&["qwen2_vl","qwen2_vl_text","qwen2_5_vl","qwen2_5_vl_text","qwen3_vl","qwen3_vl_text","qwen3_vl_moe","qwen3_vl_moe_text","qwen3_5","qwen3_5_text","qwen3_5_moe","qwen3_5_moe_text","glm_ocr","glm_ocr_text"].includes(e.config.model_type)){const{image_grid_thw:b,video_grid_thw:M}=m;[c]=e.get_rope_index(a,b,M,i)}return await Ur(e,{inputs_embeds:u,past_key_values:h,attention_mask:i,position_ids:c,generation_config:p,logits_processor:_},!0)}async function WS(e,t){return await o0(e,{...t,modality_input_names:["audio_values","input_features"],modality_output_name:"audio_features",encode_function:e.encode_audio.bind(e),merge_function:e._merge_input_ids_with_audio_features.bind(e)})}async function jS(e,t){return await o0(e,{...t,modality_input_names:["pixel_values"],modality_output_name:"image_features",encode_function:e.encode_image.bind(e),merge_function:e._merge_input_ids_with_image_features.bind(e)})}function i0(e,t=0){const[r,n]=e.dims,s=e.data,a=new BigInt64Array(s.length);for(let i=0;i<r;++i){const c=i*n;let u=BigInt(t);for(let h=0;h<n;++h){const p=c+h;s[p]===0n?a[p]=BigInt(1):(a[p]=u,u+=s[p])}}return{data:a,dims:e.dims}}function qS(e,t=null,r=0){const{input_ids:n,inputs_embeds:s,attention_mask:a}=e,{data:i,dims:c}=i0(a,r);let u=new K("int64",i,c);if(t){const h=-(n??s).dims.at(1);u=u.slice(null,[h,null])}return u}function mi(e,t,r,n){const s=r.past_key_values?r.past_key_values.get_seq_length():0;if((e.sessions.decoder_model_merged??e.sessions.model)?.inputNames.includes("num_logits_to_keep")&&!r.num_logits_to_keep&&(r.num_logits_to_keep=new K("int64",[1n],[])),!r.attention_mask){let i;for(const c of["input_ids","inputs_embeds","position_ids"])if(r[c]){i=r[c].dims;break}if(!i)throw new 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Ti=class extends O{},QS=class extends Ti{},YS=class extends Ti{async _call(e){return new fe(await super._call(e))}},XS=class extends Ti{async _call(e){return new Ft(await super._call(e))}},JS=class extends Ti{async _call(e){return new mt(await super._call(e))}},pp=class extends O{},KS=class extends pp{},ZS=class extends pp{},_p=class extends O{},eP=class extends _p{},tP=class extends _p{},mp=class extends O{},rP=class extends mp{},nP=class extends mp{},gp=class extends O{},sP=class extends gp{},aP=class extends gp{},Bl=class extends O{},oP=class extends Bl{},iP=class extends Bl{},lP=class extends Bl{async _call(e){return new fe(await super._call(e))}},wp=class extends O{},cP=class extends wp{},uP=class extends wp{async _call(e){return new fe(await super._call(e))}},Ls=class extends O{},dP=class extends Ls{},fP=class extends Ls{async _call(e){return new mt(await super._call(e))}},hP=class extends Ls{async _call(e){return new fe(await super._call(e))}},pP=class extends Ls{async _call(e){return new at(await super._call(e))}},_P=class extends Ls{async _call(e){return new Ft(await super._call(e))}},yp=class extends O{},mP=class extends yp{},gP=class extends yp{},vp=class extends O{},wP=class extends vp{},yP=class extends vp{},bp=class extends O{},vP=class extends bp{},bP=class extends bp{},Os=class extends O{},MP=class extends Os{},xP=class extends Os{async _call(e){return new mt(await super._call(e))}},TP=class extends Os{async _call(e){return new fe(await super._call(e))}},EP=class extends Os{async _call(e){return new at(await super._call(e))}},kP=class extends Os{async _call(e){return new Ft(await super._call(e))}},CP=4299n,rw=6561n,u0=class extends O{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"]},d0=class extends u0{async encode_speech(e){return Pe(this.sessions.speech_encoder,{audio_values:e})}async forward({input_ids:e=null,attention_mask:t=null,audio_values:r=null,exaggeration:n=null,position_ids:s=null,inputs_embeds:a=null,past_key_values:i=null,generation_config:c=null,logits_processor:u=null,audio_features:h=null,audio_tokens:p=null,speaker_embeddings:_=null,speaker_features:m=null,...w}){let b;if(!a){const E=this.sessions.embed_tokens.inputNames,T={input_ids:e};if(E.includes("exaggeration")){if(!(n instanceof K)){const C=e.dims[0];if(n==null)n=At([C],.5);else if(typeof n=="number")n=At([C],n);else if(Array.isArray(n))n=new K("float32",n,[C]);else throw new Error("Unsupported type for `exaggeration` input")}T.exaggeration=n}if(E.includes("position_ids")&&(T.position_ids=s),{inputs_embeds:a}=await Pe(this.sessions.embed_tokens,T),h&&p&&_&&m&&(b={audio_features:h,audio_tokens:p,speaker_embeddings:_,speaker_features:m}),b||r)b??=await this.encode_speech(r),a=je([b.audio_features,a],1),t=Ot([a.dims[0],a.dims[1]]);else{const C=a.dims[1];if(!i||C!==1)throw new Error("Incorrect state encountered during generation.");const P=i.get_seq_length();t=Ot([a.dims[0],P+C])}}return{...await Ur(this,{inputs_embeds:a,past_key_values:i,attention_mask:t,generation_config:c,logits_processor:u},!1),...b}}prepare_inputs_for_generation(e,t,r){if(!t.position_ids&&this.sessions.embed_tokens.inputNames.includes("position_ids"))if(t.input_ids.dims[1]===1){const n=Array.from({length:e.length},(s,a)=>e[a].length-e[a].findLastIndex(i=>i==rw)-1);t.position_ids=new K("int64",n,[e.length,1])}else{const s=t.input_ids.tolist().map(a=>{let i=0;return a.map(c=>c>=rw?0:i++)});t.position_ids=new K("int64",s.flat(),t.input_ids.dims)}return t.input_ids.dims[1]===1&&(delete t.audio_values,delete t.audio_features,delete t.audio_tokens,delete t.speaker_embeddings,delete t.speaker_features),mi(this,e,t)}async generate(e){const{sequences:t,audio_tokens:r,speaker_embeddings:n,speaker_features:s}=await super.generate({...e,return_dict_in_generate:!0}),a=t.slice(null,[e.input_ids.dims[1],-1]),i=At([a.dims[0],3],CP),c=je([r,a,i],1),{waveform:u}=await Pe(this.sessions.conditional_decoder,{speech_tokens:c,speaker_features:s,speaker_embeddings:n});return u}},f0=class extends O{},AP=class extends f0{},h0=class extends O{},SP=class extends h0{},$l=class extends O{},PP=class extends $l{},p0=class extends $l{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},_0=class extends $l{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"audio_model"})}},os=class extends O{},FP=class extends os{},IP=class extends os{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},m0=class extends os{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},LP=class extends os{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},OP=class extends os{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},Mp=class extends O{},NP=class extends Mp{},BP=class extends Mp{},xp=class extends O{},$P=class extends xp{},DP=class extends xp{},Tp=class extends O{},RP=class extends Tp{},zP=class extends Tp{},Ep=class extends O{},GP=class extends Ep{},UP=class extends Ep{},kp=class extends O{requires_attention_mask=!1;main_input_name="input_features";forward_params=["input_features","decoder_input_ids","decoder_attention_mask","past_key_values"]},VP=class extends kp{},WP=class extends kp{},Ns=class extends O{},jP=class extends Ns{},qP=class extends Ns{async _call(e){return new mt(await super._call(e))}},HP=class extends Ns{async _call(e){return new fe(await super._call(e))}},QP=class extends Ns{async _call(e){return new at(await super._call(e))}},YP=class extends Ns{async _call(e){return new Ft(await super._call(e))}},Cp=class extends O{},XP=class extends Cp{},JP=class extends Cp{async _call(e){return new fe(await super._call(e))}},Ap=class extends O{},KP=class extends Ap{},ZP=class extends Ap{async _call(e){return new fe(await super._call(e))}},Sp=class extends O{},eF=class extends Sp{},tF=class extends Sp{async _call(e){return new Ei(await super._call(e))}},Ei=class extends _t{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},Pp=class extends O{},rF=class extends Pp{},nF=class extends Pp{async _call(e){return new Ei(await super._call(e))}},g0=class extends _t{constructor({audio_codes:e}){super(),this.audio_codes=e}},w0=class extends _t{constructor({audio_values:e}){super(),this.audio_values=e}},Dl=class extends O{main_input_name="input_values";forward_params=["input_values"]},sF=class extends Dl{async encode(e){return new g0(await Pe(this.sessions.encoder_model,e))}async decode(e){return new w0(await Pe(this.sessions.decoder_model,e))}},y0=class extends Dl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},v0=class extends Dl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},Bs=class extends O{},aF=class extends Bs{},oF=class extends Bs{async _call(e){return new mt(await super._call(e))}},iF=class extends Bs{async _call(e){return new fe(await super._call(e))}},lF=class extends Bs{async _call(e){return new at(await super._call(e))}},cF=class extends Bs{async _call(e){return new Ft(await super._call(e))}},Fp=class extends O{},uF=class extends Fp{},dF=class extends Fp{},$s=class extends O{},fF=class extends $s{},hF=class extends $s{async _call(e){return new mt(await super._call(e))}},pF=class extends $s{async _call(e){return new fe(await super._call(e))}},_F=class extends $s{async _call(e){return new at(await super._call(e))}},mF=class extends $s{async _call(e){return new Ft(await super._call(e))}},b0=class extends O{},gF=class extends b0{},Ip=class extends O{},wF=class extends Ip{},yF=class extends Ip{async _call(e){return new fe(await super._call(e))}},M0=class extends O{},vF=class extends M0{},x0=class extends O{},bF=class extends x0{},Rl=class extends O{},MF=class extends Rl{},xF=class extends Rl{async _call(e){return new Lp(await super._call(e))}},TF=class extends Rl{async _call(e){return new T0(await super._call(e))}},Lp=class extends _t{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},T0=class extends _t{constructor({logits:e,pred_boxes:t,pred_masks:r}){super(),this.logits=e,this.pred_boxes=t,this.pred_masks=r}},Op=class extends O{},EF=class extends Op{},kF=class extends Op{async _call(e){return new fe(await super._call(e))}},Np=class extends O{},CF=class extends Np{},AF=class extends Np{async _call(e){return new fe(await super._call(e))}},E0=class extends O{},SF=class extends E0{},k0=class extends O{},PF=class extends k0{},Ds=class extends O{},FF=class extends Ds{},IF=class extends Ds{async _call(e){return new fe(await super._call(e))}},LF=class extends Ds{async _call(e){return new at(await super._call(e))}},OF=class extends Ds{async _call(e){return new Ft(await super._call(e))}},NF=class extends Ds{async _call(e){return new mt(await super._call(e))}},C0=class extends O{},BF=class extends C0{},Bp=class extends O{},$F=class extends Bp{},DF=class extends Bp{},$p=class extends O{},RF=class extends $p{},zF=class extends $p{async _call(e){return new fe(await super._call(e))}},Rs=class extends O{},GF=class extends Rs{},UF=class extends Rs{async _call(e){return new mt(await super._call(e))}},VF=class extends Rs{async _call(e){return new fe(await super._call(e))}},WF=class extends Rs{async _call(e){return new at(await super._call(e))}},jF=class extends Rs{async _call(e){return new Ft(await super._call(e))}},Dp=class extends O{},qF=class extends Dp{},HF=class extends Dp{},ki=class extends O{},QF=class extends ki{},YF=class extends ki{async _call(e){return new mt(await super._call(e))}},XF=class extends ki{async _call(e){return new fe(await super._call(e))}},JF=class extends ki{async _call(e){return new at(await super._call(e))}},Ci=class extends O{},KF=class extends Ci{},ZF=class extends Ci{async _call(e){return new mt(await super._call(e))}},eI=class extends Ci{async _call(e){return new fe(await super._call(e))}},tI=class extends Ci{async _call(e){return new at(await super._call(e))}},Rp=class extends O{},rI=class extends Rp{},nI=class extends Rp{},zp=class extends O{},sI=class extends zp{},aI=class extends zp{},Gp=class extends O{},oI=class extends Gp{},iI=class extends Gp{},Up=class extends O{},lI=class extends Up{},cI=class extends Up{async _call(e){return new fe(await super._call(e))}},A0=class extends O{forward_params=["input_ids","inputs_embeds","attention_mask","pixel_values","encoder_outputs","decoder_input_ids","decoder_inputs_embeds","decoder_attention_mask","past_key_values"];main_input_name="inputs_embeds"},uI=class extends A0{_merge_input_ids_with_image_features({inputs_embeds:e,image_features:t,input_ids:r,attention_mask:n}){return{inputs_embeds:je([t,e],1),attention_mask:je([Ot(t.dims.slice(0,2)),n],1)}}async _prepare_inputs_embeds({input_ids:e,pixel_values:t,inputs_embeds:r,attention_mask:n}){if(!e&&!t)throw new Error("Either `input_ids` or `pixel_values` should be provided.");let s,a;return e&&(s=await this.encode_text({input_ids:e})),t&&(a=await this.encode_image({pixel_values:t})),s&&a?{inputs_embeds:r,attention_mask:n}=this._merge_input_ids_with_image_features({inputs_embeds:s,image_features:a,input_ids:e,attention_mask:n}):r=s||a,{inputs_embeds:r,attention_mask:n}}async forward({input_ids:e,pixel_values:t,attention_mask:r,decoder_input_ids:n,decoder_attention_mask:s,encoder_outputs:a,past_key_values:i,inputs_embeds:c,decoder_inputs_embeds:u}){if(c||({inputs_embeds:c,attention_mask:r}=await this._prepare_inputs_embeds({input_ids:e,pixel_values:t,inputs_embeds:c,attention_mask:r})),!a){let{last_hidden_state:p}=await ln(this,{inputs_embeds:c,attention_mask:r});a=p}if(!u){if(!n)throw new Error("Either `decoder_input_ids` or `decoder_inputs_embeds` should be provided.");u=await this.encode_text({input_ids:n})}return await Ur(this,{inputs_embeds:u,attention_mask:s,encoder_attention_mask:r,encoder_hidden_states:a,past_key_values:i},!0)}},Vp=class extends O{},dI=class extends Vp{},fI=class extends Vp{},Wp=class extends O{},hI=class extends Wp{},pI=class extends Wp{},S0=class extends O{forward_params=["input_ids","attention_mask","pixel_values","position_ids","past_key_values"]},Vr=class extends S0{_merge_input_ids_with_image_features(e){const t=e.image_features.dims.at(-1),r=e.image_features.view(-1,t);return fp({image_token_id:this.config.image_token_index??this.config.image_token_id,...e,image_features:r})}},_I=class extends Vr{},mI=class extends Vr{},P0=class extends O{},gI=class extends P0{},F0=class extends Vr{},wI=class extends F0{},I0=class extends O{forward_params=["input_ids","attention_mask","inputs_embeds","per_layer_inputs","position_ids","pixel_values","input_features","input_features_mask","past_key_values"]},zl=class extends I0{async forward({input_ids:e=null,attention_mask:t=null,pixel_values:r=null,input_features:n=null,input_features_mask:s=null,position_ids:a=null,inputs_embeds:i=null,per_layer_inputs:c=null,past_key_values:u=null,generation_config:h=null,logits_processor:p=null,..._}){if((!i||!c)&&({inputs_embeds:i,per_layer_inputs:c}=await Pe(this.sessions.embed_tokens,{input_ids:e}),e.dims[1]!==1)){if(r){const{image_features:w}=await this._encode_vision({pixel_values:r,..._});({inputs_embeds:i,attention_mask:t}=this._merge_input_ids_with_image_features({image_features:w,inputs_embeds:i,input_ids:e,attention_mask:t}))}if(n){const{audio_features:w}=await Pe(this.sessions.audio_encoder,{input_features:n,input_features_mask:s});({inputs_embeds:i,attention_mask:t}=this._merge_input_ids_with_audio_features({audio_features:w,inputs_embeds:i,input_ids:e,attention_mask:t}))}}return await Ur(this,{inputs_embeds:i,per_layer_inputs:c,past_key_values:u,attention_mask:t,position_ids:a,generation_config:h,logits_processor:p},!0)}_encode_vision(e){return Pe(this.sessions.vision_encoder,{pixel_values:e.pixel_values})}_merge_input_ids_with_image_features(e){const t=e.image_features.dims.at(-1),r=e.image_features.view(-1,t);return fp({image_token_id:this.config.image_token_id,...e,image_features:r})}_merge_input_ids_with_audio_features(e){const t=e.audio_features.dims.at(-1),r=e.audio_features.view(-1,t);return c0({audio_token_id:this.config.audio_token_id,...e,audio_features:r})}},yI=class extends zl{},jp=class extends zl{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 Pe(this.sessions.vision_encoder,{pixel_values:e.pixel_values,pixel_position_ids:e.image_position_ids})}},vI=class extends jp{},qp=class extends O{},bI=class extends qp{},MI=class extends qp{},Hp=class extends O{},xI=class extends Hp{},TI=class extends Hp{},L0=class extends O{forward_params=["input_ids","attention_mask","position_ids","past_key_values","pixel_values","image_grid_thw"]},Qp=class extends L0{image_grid_thw_name="grid_thw";_get_text_only_rope_index(e,t){if(t){const{data:r,dims:n}=i0(t),s=BigInt64Array.from({length:3*r.length},(i,c)=>r[c%r.length]),a=Array.from({length:n[0]},(i,c)=>pt(r.subarray(n[1]*c,n[1]*(c+1)))[0]+1n+BigInt(n[1]));return[new K("int64",s,[3,...n]),new K("int64",a,[a.length,1])]}else{const[r,n]=e.dims,s=BigInt64Array.from({length:3*r*n},(a,i)=>BigInt(Math.floor(i%n/r)));return[new K("int64",s,[3,...e.dims]),lv([r,1])]}}_reorder_and_write_positions(e,t,r,n){const s=e.reduce((u,h)=>u+h.length,0),a=new Array(s);let i=0;for(let u=0;u<3;++u)for(const h of e){const p=h.length/3;for(let _=u*p;_<(u+1)*p;++_)a[i++]=h[_]}let c=0;for(let u=0;u<t.length;++u)if(t[u]==1){for(let h=0;h<3;++h)r[h][n][u]=a[h*s/3+c];++c}return a}_get_multimodal_rope_positions({filtered_ids:e,image_grid_thw_list:t,video_grid_thw_list:r,spatial_merge_size:n,state:s}){const{image_token_id:a,video_token_id:i,vision_start_token_id:c}=this.config,u=e,p=u.reduce((T,C,P)=>(C==c&&T.push(P),T),[]).map(T=>u[T+1]),_=p.filter(T=>T==a).length,m=p.filter(T=>T==i).length,w=[];let b=0,M=_,E=m;for(let T=0;T<p.length;++T){const C=u.findIndex((z,Q)=>Q>b&&z==a),P=u.findIndex((z,Q)=>Q>b&&z==i),A=M>0&&C!==-1?C:u.length+1,F=E>0&&P!==-1?P:u.length+1;let G,v,j,U;A<F?([v,j,U]=t[s.image_index],++s.image_index,--M,G=A):([v,j,U]=r[s.video_index],++s.video_index,--E,G=F);const[q,ne,H]=[Number(v),Math.floor(Number(j)/n),Math.floor(Number(U)/n)],I=G-b,S=w.length>0?pt(w.at(-1))[0]+1:0;w.push(Array.from({length:3*I},(z,Q)=>S+Q%I));const D=I+S,Y=q*ne*H,se=Array.from({length:Y},(z,Q)=>D+Math.floor(Q/(ne*H))),N=Array.from({length:Y},(z,Q)=>D+Math.floor(Q/H)%ne),$=Array.from({length:Y},(z,Q)=>D+Q%H);w.push([se,N,$].flat()),b=G+Y}if(b<u.length){const T=w.length>0?pt(w.at(-1))[0]+1:0,C=u.length-b;w.push(Array.from({length:3*C},(P,A)=>T+A%C))}return w}get_rope_index(e,t,r,n){const{vision_config:s}=this.config,a=s.spatial_merge_size??2;if(t||r){const i=e.tolist();n||(n=iv(e));const c=n.tolist(),u=Array.from({length:3},()=>Array.from({length:e.dims[0]},()=>Array.from({length:e.dims[1]},()=>0))),h=t?t.tolist():[],p=r?r.tolist():[],_={image_index:0,video_index:0},m=[];for(let w=0;w<i.length;++w){const b=i[w].filter((T,C)=>c[w][C]==1),M=this._get_multimodal_rope_positions({filtered_ids:b,image_grid_thw_list:h,video_grid_thw_list:p,spatial_merge_size:a,state:_}),E=this._reorder_and_write_positions(M,c[w],u,w);m.push(pt(E)[0]+1-i[w].length)}return[new K("int64",u.flat(1/0),[3,e.dims[0],e.dims[1]]),new K("int64",m,[m.length,1])]}else return this._get_text_only_rope_index(e,n)}async encode_image({pixel_values:e,image_grid_thw:t}){return(await Pe(this.sessions.vision_encoder,{pixel_values:e,[this.image_grid_thw_name]:t})).image_features}_merge_input_ids_with_image_features(e){return fp({image_token_id:this.config.image_token_id,...e})}prepare_inputs_for_generation(e,t,r){if(!t.attention_mask||t.position_ids||!(this.sessions.decoder_model_merged??this.sessions.model).inputNames.includes("position_ids"))return t;if(!t.past_key_values)[t.position_ids,t.rope_deltas]=this.get_rope_index(t.input_ids,t.image_grid_thw,t.video_grid_thw,t.attention_mask);else{t.pixel_values=null;const s=t.past_key_values.get_seq_length();if(s<t.input_ids.dims[1]){const[a,i]=this.get_rope_index(t.input_ids,t.image_grid_thw,t.video_grid_thw,t.attention_mask);t.rope_deltas=i,t.position_ids=a.slice(null,null,[s,null]),t.input_ids=t.input_ids.slice(null,[s,null])}else{t.rope_deltas||([,t.rope_deltas]=this.get_rope_index(t.input_ids,t.image_grid_thw,t.video_grid_thw,t.attention_mask));const a=BigInt(s),i=t.rope_deltas.map(c=>a+c);t.position_ids=Gr([i,i,i],0)}}return t}},O0=class extends Qp{},Yp=class extends Qp{image_grid_thw_name="image_grid_thw"},N0=class extends O0{image_grid_thw_name="image_grid_thw"},EI=class extends Yp{get_vision_position_ids(e,t,r,n){const s=Math.floor(t[0]/r),a=Math.floor(t[1]/n),i=Math.floor(t[2]/n),c=a*i*s,u=Array.from({length:c},()=>e),h=Array.from({length:c},(_,m)=>e+Math.floor(m/(i*s))),p=Array.from({length:c},(_,m)=>e+m%i);return[...u,...h,...p]}_get_multimodal_rope_positions({filtered_ids:e,image_grid_thw_list:t,video_grid_thw_list:r,spatial_merge_size:n,state:s}){const{image_token_id:a}=this.config,i=[];let c=0,u=e[0]==a?1:0;for(let _=1;_<=e.length;++_){const m=_<e.length?e[_]==a?1:0:-1;m!==u&&(i.push([u,c,_]),c=_,u=m)}let h=0;const p=[];for(const[_,m,w]of i)if(_===0){const b=w-m;p.push(Array.from({length:3*b},(M,E)=>h+E%b)),h+=b}else{const b=t[s.image_index++].map(Number),M=b[0];p.push(this.get_vision_position_ids(h,b,M,n)),h+=Math.max(b[1],b[2])/n}return p}},Xp=class extends O{},kI=class extends Xp{},CI=class extends Xp{},Jp=class extends O{},AI=class extends Jp{},SI=class extends Jp{},Kp=class extends O{},PI=class extends Kp{},FI=class extends Kp{},Zp=class extends O{},II=class extends Zp{},LI=class extends Zp{},e_=class extends O{},OI=class extends e_{},NI=class extends e_{},t_=class extends O{},BI=class extends t_{},$I=class extends t_{},r_=class extends O{},DI=class extends r_{},RI=class extends r_{},n_=class extends O{},zI=class extends n_{},GI=class extends n_{},s_=class extends O{},UI=class extends s_{},VI=class extends s_{},B0=class extends O{forward_params=["input_ids","attention_mask","position_ids","audio_values","past_key_values"]},a_=class extends B0{_merge_input_ids_with_audio_features(e){const t=e.audio_features.dims.at(-1),r=e.audio_features.view(-1,t);return c0({audio_token_id:this.config.ignore_index??this.config.audio_token_id??this.config.audio_token_index,...e,audio_features:r})}},WI=class extends a_{forward_params=["input_ids","attention_mask","input_features","past_key_values"]},$0=class extends O{},jI=class extends $0{},D0=class extends O{},qI=class extends D0{},o_=class extends O{},HI=class extends o_{},QI=class extends o_{},i_=class extends O{},YI=class extends i_{},XI=class extends i_{async _call(e){return new fe(await super._call(e))}},cn=class extends O{},JI=class extends cn{},KI=class extends cn{async _call(e){return new as(await super._call(e))}},ZI=class extends cn{async _call(e){return new fe(await super._call(e))}},eL=class extends cn{async _call(e){return new at(await super._call(e))}},tL=class extends O{},rL=class extends cn{},nL=class extends cn{async _call(e){return new as(await super._call(e))}},sL=class extends cn{async _call(e){return new fe(await super._call(e))}},l_=class extends O{},aL=class extends l_{},oL=class extends l_{},R0=class extends Vr{forward_params=["input_ids","attention_mask","pixel_values","pixel_attention_mask","position_ids","past_key_values"]},c_=class extends O{},iL=class extends c_{},lL=class extends c_{async _call(e){return new fe(await super._call(e))}},u_=class extends O{},cL=class extends u_{},uL=class extends u_{},Gl=class extends O{},dL=class extends Gl{async forward(e){const t=!e.input_ids,r=!e.pixel_values;if(t&&r)throw new Error("Either `input_ids` or `pixel_values` should be provided.");if(t&&(e.input_ids=Ot([e.pixel_values.dims[0],1])),r){const{image_size:u}=this.config.vision_config;e.pixel_values=At([0,3,u,u],0)}const{text_embeddings:n,image_embeddings:s,l2norm_text_embeddings:a,l2norm_image_embeddings:i}=await super.forward(e),c={};return t||(c.text_embeddings=n,c.l2norm_text_embeddings=a),r||(c.image_embeddings=s,c.l2norm_image_embeddings=i),c}},z0=class extends Gl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},fL=class extends Gl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},d_=class extends O{},hL=class extends d_{},pL=class extends d_{},_L=class extends Vr{},f_=class extends O{},mL=class extends f_{},gL=class extends f_{},wL=class extends Vr{forward_params=["input_ids","attention_mask","pixel_values","pixel_attention_mask","spatial_shapes","position_ids","past_key_values"]},h_=class extends O{},yL=class extends h_{},vL=class extends h_{},G0=class extends O{},bL=class extends G0{},p_=class extends O{},ML=class extends p_{},xL=class extends p_{},__=class extends O{},TL=class extends __{},EL=class extends __{},m_=class extends O{},kL=class extends m_{},CL=class extends m_{},g_=class extends O{},AL=class extends g_{},SL=class extends g_{},Ai=class extends O{},PL=class extends Ai{},FL=class extends Ai{},IL=class extends Ai{async _call(e){return new fe(await super._call(e))}},LL=class extends Ai{},U0=class extends O{},OL=class extends U0{},V0=class extends O{},NL=class extends V0{},W0=class extends _t{constructor({char_logits:e,bpe_logits:t,wp_logits:r}){super(),this.char_logits=e,this.bpe_logits=t,this.wp_logits=r}get logits(){return[this.char_logits,this.bpe_logits,this.wp_logits]}},j0=class extends O{},BL=class extends j0{async _call(e){return new W0(await super._call(e))}},q0=class extends _t{constructor({audio_codes:e}){super(),this.audio_codes=e}},H0=class extends _t{constructor({audio_values:e}){super(),this.audio_values=e}},Ul=class extends O{main_input_name="input_values";forward_params=["input_values"]},$L=class extends Ul{async encode(e){return new q0(await Pe(this.sessions.encoder_model,e))}async decode(e){return new H0(await Pe(this.sessions.decoder_model,e))}},Q0=class extends Ul{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},Y0=class extends Ul{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},w_=class extends O{},DL=class extends w_{},RL=class extends w_{},y_=class extends O{},zL=class extends y_{},GL=class extends y_{},Si=class extends O{},UL=class extends Si{},VL=class extends Si{async _call(e){return new mt(await super._call(e))}},WL=class extends Si{async _call(e){return new fe(await super._call(e))}},jL=class extends Si{async _call(e){return new Ft(await super._call(e))}},v_=class extends O{},qL=class extends v_{},HL=class extends v_{},Vl=class extends O{},QL=class extends Vl{},YL=class extends Vl{async _call(e){return new fe(await super._call(e))}},XL=class extends Vl{},Wl=class extends O{},JL=class extends Wl{},KL=class extends Wl{async _call(e){return new fe(await super._call(e))}},ZL=class extends Wl{},jl=class extends O{},eO=class extends jl{},tO=class extends jl{async _call(e){return new fe(await super._call(e))}},rO=class extends jl{},ql=class extends O{},nO=class extends ql{},sO=class extends ql{async _call(e){return new fe(await super._call(e))}},aO=class extends ql{},b_=class extends O{},oO=class extends b_{},iO=class extends b_{async _call(e){return new fe(await super._call(e))}},M_=class extends O{},lO=class extends M_{},cO=class extends M_{async _call(e){return new fe(await super._call(e))}},Pi=class extends O{},uO=class extends Pi{},dO=class extends Pi{async _call(e){return new mt(await super._call(e))}},fO=class extends Pi{async _call(e){return new fe(await super._call(e))}},hO=class extends Pi{async _call(e){return new at(await super._call(e))}},x_=class extends O{},pO=class extends x_{},_O=class extends x_{},T_=class extends O{requires_attention_mask=!1;main_input_name="input_values";forward_params=["input_values","decoder_input_ids","past_key_values"]},mO=class extends T_{},gO=class extends T_{},zs=class extends O{},wO=class extends zs{},yO=class extends zs{async _call(e){return new mt(await super._call(e))}},vO=class extends zs{async _call(e){return new fe(await super._call(e))}},bO=class extends zs{async _call(e){return new at(await super._call(e))}},MO=class extends zs{async _call(e){return new Ft(await super._call(e))}},E_=class extends O{},xO=class extends E_{},TO=class extends E_{},k_=class extends O{},EO=class extends k_{},kO=class extends k_{},X0=class extends O{},CO=class extends X0{forward_params=["input_ids","pixel_values","images_seq_mask","images_emb_mask","attention_mask","position_ids","past_key_values"];constructor(...e){super(...e),this._generation_mode="text"}async forward(e){const t=this._generation_mode??"text";let r;if(t==="text"||!e.past_key_values){const c=this.sessions.prepare_inputs_embeds,u=xt(e,c.inputNames);r=await Pe(c,u)}else{const c=this.sessions.gen_img_embeds,u=xt({image_ids:e.input_ids},c.inputNames);r=await Pe(c,u)}const n={...e,...r},s=await Ur(this,n),a=this.sessions[t==="text"?"lm_head":"gen_head"];if(!a)throw new Error(`Unable to find "${a}" generation head`);const i=await Pe(a,xt(s,a.inputNames));return{...r,...s,...i}}prepare_inputs_for_generation(e,t,r){const n=!!t.past_key_values;return r.guidance_scale!==null&&r.guidance_scale>1&&(n?t.input_ids=je([t.input_ids,t.input_ids],0):(t.input_ids=je([t.input_ids,dh(t.input_ids,BigInt(r.pad_token_id))],0),t.attention_mask=je([t.attention_mask,dh(t.attention_mask,0n)],0))),(n||!t.pixel_values)&&(t.pixel_values=At([0,0,3,384,384],1)),n&&(t.images_seq_mask=new K("bool",new Array(1).fill(!0).fill(!1,0,1),[1,1]),t.images_emb_mask=new K("bool",new Array(0).fill(!1),[1,1,0])),t}async generate(e){return this._generation_mode="text",super.generate(e)}async generate_images(e){this._generation_mode="image";const t=(e.inputs??e[this.main_input_name]).dims[1],n=(await super.generate(e)).slice(null,[t,null]),s=this.sessions.image_decode,{decoded_image:a}=await Pe(s,{generated_tokens:n}),i=a.add_(1).mul_(255/2).clamp_(0,255).to("uint8"),c=[];for(const u of i){const h=yi.fromTensor(u);c.push(h)}return c}},C_=class extends O{},AO=class extends C_{},SO=class extends C_{},J0=class extends O{forward_params=["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"];_apply_and_filter_by_delay_pattern_mask(e){const[t,r]=e.dims,n=this.config.decoder.num_codebooks,s=r-n;let a=0;for(let u=0;u<e.size;++u){if(e.data[u]==this.config.decoder.pad_token_id)continue;const h=u%r,p=Math.floor(u/r)%n,_=h-p;_>0&&_<=s&&(e.data[a++]=e.data[u])}const i=Math.floor(t/n),c=a/(i*n);return new K(e.type,e.data.slice(0,a),[i,n,c])}prepare_inputs_for_generation(e,t,r){const n=BigInt(this.config.decoder.pad_token_id);let s=structuredClone(e);for(let a=0;a<s.length;++a)for(let i=0;i<s[a].length;++i)a%this.config.decoder.num_codebooks>=i&&(s[a][i]=n);return r.guidance_scale!==null&&r.guidance_scale>1&&(s=s.concat(s)),vl(this,s,t)}async generate(e){const t=await super.generate(e),r=this._apply_and_filter_by_delay_pattern_mask(t).unsqueeze_(0),{audio_values:n}=await Pe(this.sessions.encodec_decode,{audio_codes:r});return n}},A_=class extends O{},PO=class extends A_{},FO=class extends A_{},S_=class extends O{},IO=class extends S_{},LO=class extends S_{},Gs=class extends O{},OO=class extends Gs{},NO=class extends Gs{async _call(e){return new mt(await super._call(e))}},BO=class extends Gs{async _call(e){return new fe(await super._call(e))}},$O=class extends Gs{async _call(e){return new at(await super._call(e))}},DO=class extends Gs{async _call(e){return new Ft(await super._call(e))}},K0=class extends O{},RO=class extends K0{},P_=class extends O{},zO=class extends P_{},GO=class extends P_{},F_=class extends O{},UO=class extends F_{},VO=class extends F_{},I_=class extends O{},WO=class extends I_{},jO=class extends I_{},L_=class extends O{},qO=class extends L_{},HO=class extends L_{},O_=class extends O{},QO=class extends O_{},YO=class extends O_{async _call(e){return new fe(await super._call(e))}},N_=class extends O{},XO=class extends N_{},JO=class extends N_{},B_=class extends O{},KO=class extends B_{},ZO=class extends B_{},$_=class extends O{},e3=class extends $_{},t3=class extends $_{},D_=class extends O{},r3=class extends D_{},n3=class extends D_{},s3=class extends Vr{},Z0=class extends O{},a3=class extends Z0{async _call(e){return new as(await super._call(e))}},R_=class extends O{},o3=class extends R_{},i3=class extends R_{},z_=class extends O{},l3=class extends z_{},c3=class extends z_{},G_=class extends O{},u3=class extends G_{},d3=class extends G_{},U_=class extends O{},f3=class extends U_{},h3=class extends U_{},eb=class extends O{forward_params=["input_ids","inputs_embeds","attention_mask","position_ids","pixel_values","image_sizes","past_key_values"]},tb=class extends eb{async forward({input_ids:e=null,attention_mask:t=null,pixel_values:r=null,image_sizes:n=null,position_ids:s=null,inputs_embeds:a=null,past_key_values:i=null,generation_config:c=null,logits_processor:u=null,...h}){if(!a){let _;if(r&&e.dims[1]!==1){if(!n)throw new Error("`image_sizes` must be provided when `pixel_values` is provided.");({image_features:_}=await Pe(this.sessions.vision_encoder,{pixel_values:r,image_sizes:n}))}else{const m=this.config.normalized_config.hidden_size;_=new K("float32",[],[0,m])}({inputs_embeds:a}=await Pe(this.sessions.prepare_inputs_embeds,{input_ids:e,image_features:_}))}return await Ur(this,{inputs_embeds:a,past_key_values:i,attention_mask:t,position_ids:s,generation_config:c,logits_processor:u},!1)}},V_=class extends O{},p3=class extends V_{},_3=class extends V_{async _call(e){return new fe(await super._call(e))}},W_=class extends O{},m3=class extends W_{},g3=class extends W_{async _call(e){return new at(await super._call(e))}},j_=class extends O{},w3=class extends j_{},y3=class extends j_{},q_=class extends O{},v3=class extends q_{},b3=class extends q_{},H_=class extends O{},M3=class extends H_{},x3=class extends H_{},Q_=class extends O{},T3=class extends Q_{},E3=class extends Q_{},Y_=class extends O{},k3=class extends Y_{},C3=class extends Y_{},X_=class extends Yp{},rb=class extends N0{},A3=class extends X_{},S3=class extends rb{},J_=class extends X_{},nb=class extends J_{},P3=class extends J_{},F3=class extends nb{},K_=class extends O{},I3=class extends K_{},L3=class extends K_{async _call(e){return new fe(await super._call(e))}},Z_=class extends O{},O3=class extends Z_{},N3=class extends Z_{async _call(e){return new sb(await super._call(e))}},sb=class extends Ei{},Us=class extends O{},B3=class extends Us{},$3=class extends Us{async _call(e){return new mt(await super._call(e))}},D3=class extends Us{async _call(e){return new fe(await super._call(e))}},R3=class extends Us{async _call(e){return new at(await super._call(e))}},z3=class extends Us{async _call(e){return new Ft(await super._call(e))}},Vs=class extends O{},G3=class extends Vs{},U3=class extends Vs{async _call(e){return new mt(await super._call(e))}},V3=class extends Vs{async _call(e){return new fe(await super._call(e))}},W3=class extends Vs{async _call(e){return new at(await super._call(e))}},j3=class extends Vs{async _call(e){return new Ft(await super._call(e))}},em=class extends O{},q3=class extends em{},H3=class extends em{async _call(e){return new ab(await super._call(e))}},ab=class extends Ei{},ob=class extends _t{constructor({iou_scores:e,pred_masks:t}){super(),this.iou_scores=e,this.pred_masks=t}},ib=class extends O{},Q3=class extends ib{async get_image_embeddings({pixel_values:e}){return await ln(this,{pixel_values:e})}async forward(e){!e.image_embeddings||!e.image_positional_embeddings?e={...e,...await this.get_image_embeddings(e)}:e={...e},e.input_labels??=Ot(e.input_points.dims.slice(0,-1));const t={image_embeddings:e.image_embeddings,image_positional_embeddings:e.image_positional_embeddings};return e.input_points&&(t.input_points=e.input_points),e.input_labels&&(t.input_labels=e.input_labels),e.input_boxes&&(t.input_boxes=e.input_boxes),await Pe(this.sessions.prompt_encoder_mask_decoder,t)}async _call(e){return new ob(await super._call(e))}},lb=class extends _t{constructor({iou_scores:e,pred_masks:t,object_score_logits:r}){super(),this.iou_scores=e,this.pred_masks=t,this.object_score_logits=r}},cb=class extends O{},tm=class extends cb{async get_image_embeddings({pixel_values:e}){return await ln(this,{pixel_values:e})}async forward(e){const{num_feature_levels:t}=this.config.vision_config;if(Array.from({length:t},(a,i)=>`image_embeddings.${i}`).some(a=>!e[a])?e={...e,...await this.get_image_embeddings(e)}:e={...e},e.input_points){if(e.input_boxes&&e.input_boxes.dims[1]!==1)throw new Error("When both `input_points` and `input_boxes` are provided, the number of boxes per image must be 1.");const a=e.input_points.dims;e.input_labels??=Ot(a.slice(0,-1)),e.input_boxes??=At([a[0],0,4],0)}else if(e.input_boxes){const a=e.input_boxes.dims;e.input_labels=At([a[0],a[1],0],-1n),e.input_points=At([a[0],1,0,2],0)}else throw new Error("At least one of `input_points` or `input_boxes` must be provided.");const n=this.sessions.prompt_encoder_mask_decoder,s=xt(e,n.inputNames);return await Pe(n,s)}async _call(e){return new lb(await super._call(e))}},Y3=class extends tm{},X3=class extends tm{},Hl=class extends O{},J3=class extends Hl{},K3=class extends Hl{},Z3=class extends Hl{},Ql=class extends O{},eN=class extends Ql{},tN=class extends Ql{},rN=class extends Ql{},rm=class extends O{},nN=class extends rm{},ub=class extends rm{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},sN=class extends os{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},nm=class extends O{},aN=class extends nm{},oN=class extends nm{},iN=class extends R0{},Yl=class extends O{main_input_name="input_values";forward_params=["input_values"]},lN=class extends Yl{async encode(e){return await Pe(this.sessions.encoder_model,e)}async decode(e){return await Pe(this.sessions.decoder_model,e)}},db=class extends Yl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},fb=class extends Yl{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},sm=class extends O{},cN=class extends sm{},uN=class extends sm{},Xl=class extends O{},dN=class extends Xl{},fN=class extends Xl{},hN=class extends Xl{async generate_speech(e,t,{threshold:r=.5,minlenratio:n=0,maxlenratio:s=20,vocoder:a=null}={}){const i={input_ids:e},{encoder_outputs:c,encoder_attention_mask:u}=await ln(this,i),h=c.dims[1]/this.config.reduction_factor,p=Math.floor(h*s),_=Math.floor(h*n),m=this.config.num_mel_bins;let w=[],b=null,M=null,E=0;for(;;){++E;const P=s0(!!M);let A;M?A=M.output_sequence_out:A=new K("float32",new Float32Array(m),[1,1,m]);let F={use_cache_branch:P,output_sequence:A,encoder_attention_mask:u,speaker_embeddings:t,encoder_hidden_states:c};dp(this,F,b),M=await Pe(this.sessions.decoder_model_merged,F),b=mh(M,b);const{prob:G,spectrum:v}=M;if(w.push(v),E>=_&&(Array.from(G.data).filter(j=>j>=r).length>0||E>=p))break}const T=je(w),{waveform:C}=await Pe(a.sessions.model,{spectrogram:T});return{spectrogram:T,waveform:C}}},pN=class extends O{main_input_name="spectrogram"},Fi=class extends O{},_N=class extends Fi{},mN=class extends Fi{async _call(e){return new mt(await super._call(e))}},gN=class extends Fi{async _call(e){return new fe(await super._call(e))}},wN=class extends Fi{async _call(e){return new Ft(await super._call(e))}},am=class extends O{},yN=class extends am{},vN=class extends am{},om=class extends O{},bN=class extends om{},MN=class extends om{},hb=class extends O{},xN=class extends hb{},pb=class extends O{},_b=class extends pb{async generate_speech({input_ids:e,attention_mask:t,style:r,num_inference_steps:n=5,speed:s=1.05}){const{sampling_rate:a,chunk_compress_factor:i,base_chunk_size:c,latent_dim:u}=this.config,{last_hidden_state:h,durations:p}=await Pe(this.sessions.text_encoder,{input_ids:e,attention_mask:t,style:r}),_=p.div(s).mul_(a),m=c*i,w=_.data,b=Int32Array.from(w,U=>Math.ceil(U/m)),M=Math.max(...b),E=e.dims[0],T=new BigInt64Array(E*M);for(let U=0;U<E;++U)T.fill(1n,U*M,U*M+b[U]);const C=new K("int64",T,[E,M]),P=u*i,A=P*M;let F=JE([E,P,M]);const G=F.data;for(let U=0;U<E;++U)if(b[U]!==M)for(let q=0;q<P;++q)G.fill(0,U*A+q*M+b[U],U*A+(q+1)*M);const v=At([E],n);for(let U=0;U<n;++U){const q=At([E],U);({denoised_latents:F}=await Pe(this.sessions.latent_denoiser,{style:r,noisy_latents:F,latent_mask:C,encoder_outputs:h,attention_mask:t,timestep:q,num_inference_steps:v}))}const{waveform:j}=await Pe(this.sessions.voice_decoder,{latents:F});return{waveform:j,durations:_}}},Jl=class extends O{},TN=class extends Jl{},EN=class extends Jl{async _call(e){return new fe(await super._call(e))}},kN=class extends Jl{},im=class extends O{},CN=class extends im{},AN=class extends im{},lm=class extends O{forward_params=["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"]},SN=class extends lm{},PN=class extends lm{},cm=class extends O{},FN=class extends cm{},IN=class extends cm{async _call(e){return new mb(await super._call(e))}},mb=class extends Lp{},gb=class extends O{},LN=class extends gb{},Kl=class extends O{},ON=class extends Kl{},NN=class extends Kl{async _call(e){return new as(await super._call(e))}},BN=class extends Kl{async _call(e){return new fe(await super._call(e))}},Ii=class extends O{},$N=class extends Ii{},DN=class extends Ii{async _call(e){return new as(await super._call(e))}},RN=class extends Ii{async _call(e){return new fe(await super._call(e))}},zN=class extends Ii{async _call(e){return new at(await super._call(e))}},um=class extends O{},GN=class extends um{},UN=class extends um{},VN=class extends O{main_input_name="pixel_values";forward_params=["pixel_values","decoder_input_ids","encoder_hidden_states","past_key_values"]},dm=class extends O{},WN=class extends dm{},jN=class extends dm{async _call(e){return new fe(await super._call(e))}},wb=class extends O{},qN=class extends wb{},fm=class extends O{},HN=class extends fm{},QN=class extends fm{async _call(e){return new fe(await super._call(e))}},yb=class extends O{},YN=class extends yb{async _call(e){return new wS(await super._call(e))}},vb=class extends O{},XN=class extends vb{},bb=class extends _t{constructor({waveform:e,spectrogram:t}){super(),this.waveform=e,this.spectrogram=t}},Mb=class extends O{},JN=class extends Mb{async _call(e){return new bb(await super._call(e))}},KN=class extends a_{},nw=2,ZN=1,If=new WeakMap;function e4(e,t){const{text_config:r,audio_config:n}=e.config,s=e.sessions.audio_encoder,{num_mel_bins:a,hidden_size:i}=n,c=a+i,u=new cp,h=Ll(n),p={batch_size:1};let _="float32";for(const M of s.inputMetadata){if(M.name==="past_padding_cache"){_=M.type;continue}if(!h.has(M.name))continue;const E=a0(M.shape,p),T=E.reduce((P,A)=>P*A,1),C=wi[M.type];u[M.name]=new K(M.type,new C(T),E)}const m=wi[_],w=new K(_,new m(c*nw),[1,c,nw]),b=t[Symbol.asyncIterator]?.()??t[Symbol.iterator]?.();if(!b)throw new Error("input_features must be iterable or async iterable");return{encoder_session:s,enc_kv_cache:u,enc_padding_cache:w,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:b,text_hidden_size:r.hidden_size}}async function t4(e,t){const r=t.dims[2],n=Math.floor((ZN+r-3)/2)+1,s=new K("int64",BigInt64Array.from({length:n},(p,_)=>BigInt(e.enc_past_seq_len+_)),[1,n]),a=e.enc_past_seq_len+n,i=Ot([1,a]),{audio_embeds:c,present_padding_cache:u,...h}=await Pe(e.encoder_session,{input_features:t,attention_mask:i,position_ids:s,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=u;for(const p in h)if(p.startsWith("present.")){const _=p.replace("present","past_key_values"),m=e.enc_kv_cache[_];m?.location==="gpu-buffer"&&m.dispose(),e.enc_kv_cache[_]=h[p]}return e.enc_past_seq_len=a,c}async function r4(e,t){for(;e.audio_embed_total_tokens<t&&!e.stream_exhausted;){const r=await e.chunks_iter.next();if(r.done){e.stream_exhausted=!0;break}const n=await t4(e,r.value);e.audio_embed_queue.push({data:n.data,tokens:n.dims[1]}),e.audio_embed_total_tokens+=n.dims[1]}}function n4(e,t,r){if(e.audio_embed_queue.length===0)return;const n=t.data;let s=0,a=r;for(;a>0&&e.audio_embed_queue.length>0;){const i=e.audio_embed_queue[0],c=i.tokens-e.audio_queue_offset,u=Math.min(a,c),h=e.audio_queue_offset*e.text_hidden_size;for(let p=0;p<u*e.text_hidden_size;++p)n[s*e.text_hidden_size+p]+=i.data[h+p];s+=u,a-=u,e.audio_queue_offset+=u,e.audio_queue_offset>=i.tokens&&(e.audio_embed_queue.shift(),e.audio_queue_offset=0)}e.audio_consumed+=r-a}var s4=class extends Ol{constructor(e){super(),this._s=e}_call(e){const t=this._s.stream_exhausted&&this._s.audio_embed_queue.length===0;return e.map(()=>t)}},xb=class extends O{forward_params=["input_ids","attention_mask","position_ids","past_key_values"]},Tb=class extends xb{async forward({input_ids:e,past_key_values:t,...r}){const n=e.dims[1],s=If.get(this);s&&await r4(s,s.audio_consumed+n);const{inputs_embeds:a}=await Pe(this.sessions.embed_tokens,{input_ids:e});s&&n4(s,a,n);const i={inputs_embeds:a,...r};dp(this,i,t);const c=this.sessions.decoder_model_merged,u=xt(i,c.inputNames);return await Pe(c,u)}async generate({input_features:e,stopping_criteria:t,...r}){if(!e)throw new Error("input_features (generator/iterable) must be provided");const n=e4(this,e);If.set(this,n);const s=new r0;s.push(new s4(n)),t&&s.extend(t);try{return await super.generate({...r,stopping_criteria:s})}finally{n.enc_kv_cache.dispose(),If.delete(this)}}},Zl=class extends O{},a4=class extends Zl{},o4=class extends Zl{async _call(e){return new as(await super._call(e))}},i4=class extends Zl{async _call(e){return new fe(await super._call(e))}},Eb=class extends _t{constructor({logits:e,embeddings:t}){super(),this.logits=e,this.embeddings=t}},Ws=class extends O{},l4=class extends Ws{},c4=class extends Ws{async _call(e){return new as(await super._call(e))}},u4=class extends Ws{async _call(e){return new fe(await super._call(e))}},d4=class extends Ws{async _call(e){return new Eb(await super._call(e))}},f4=class extends Ws{async _call(e){return new at(await super._call(e))}},kb=class extends O{},h4=class extends kb{},p4=class extends t0{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},hm=class extends O{requires_attention_mask=!1;main_input_name="input_features";forward_params=["input_features","attention_mask","decoder_input_ids","decoder_attention_mask","past_key_values"]},_4=class extends hm{},Cb=class extends hm{_prepare_generation_config(e,t){return super._prepare_generation_config(e,t,p4)}_retrieve_init_tokens(e){const t=[e.decoder_start_token_id];let r=e.language;const n=e.task;if(e.is_multilingual){r||(be.warn("No language specified - defaulting to English (en)."),r="en");const a=`<|${qk(r)}|>`;t.push(e.lang_to_id[a]),t.push(e.task_to_id[n??"transcribe"])}else if(r||n)throw new 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&&(be.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),t.pop()),t.filter(s=>s!=null)}async generate({inputs:e=null,generation_config:t=null,logits_processor:r=null,stopping_criteria:n=null,...s}){t=this._prepare_generation_config(t,s);const a=s.decoder_input_ids instanceof K?tp(s.decoder_input_ids):s.decoder_input_ids??this._retrieve_init_tokens(t);if(t.return_timestamps&&(r??=new yl,r.push(new xS(t,a))),t.begin_suppress_tokens&&(r??=new yl,r.push(new e0(t.begin_suppress_tokens,a.length))),t.return_token_timestamps){if(!t.alignment_heads)throw new 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"&&be.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&&!s.max_new_tokens)return this._generate_with_seek({inputs:e,generation_config:t,logits_processor:r,init_tokens:a,kwargs:s});const i=await super.generate({inputs:e,generation_config:t,logits_processor:r,decoder_input_ids:a,...s});return t.return_token_timestamps&&(i.token_timestamps=this._extract_token_timestamps(i,t.alignment_heads,t.num_frames,.02,a.length)),i}async _generate_with_seek({inputs:e,generation_config:t,logits_processor:r,init_tokens:n,kwargs:s}){const a=t.no_timestamps_token_id+1,i=Array.isArray(t.eos_token_id)?t.eos_token_id[0]:t.eos_token_id,c=t.return_token_timestamps,u=e,h=u.dims[2],p=2,_=this.config.max_source_positions,m=p*_;let w=0;const b=[],M=[];for(;w<h;){const T=Math.min(w+m,h),C=u.slice(null,null,[w,T]);let P;const A=C.dims[2];if(A<m){const Y=u.dims[1],se=new Float32Array(Y*m),N=C.data;for(let $=0;$<Y;++$)se.set(N.subarray($*A,($+1)*A),$*m);P=new K("float32",se,[1,Y,m])}else P=C;if(r)for(const Y of r)"begin_index"in Y&&(Y.begin_index=n.length);const F=await super.generate({inputs:P,generation_config:t,logits_processor:r,decoder_input_ids:n,...s}),v=(c?F.sequences:F)[0].tolist().map(Number).slice(n.length);let j;if(c){F.token_timestamps=this._extract_token_timestamps(F,t.alignment_heads,Math.floor((T-w)/p),.02,n.length);const Y=w/p*.02;j=F.token_timestamps[0].tolist().slice(n.length).map(se=>se+Y)}if(v.length>0&&v.at(-1)===i&&v.pop(),v.length===0)break;const U=v.map(Y=>Y>=a),q=v.length>=2&&U[v.length-1]&&!U[v.length-2],ne=[];for(let Y=0;Y<v.length-1;++Y)U[Y]&&U[Y+1]&&ne.push(Y+1);let H,I=v.length;if(ne.length>0)if(q)H=T-w;else{const Y=ne.at(-1);H=(v[Y-1]-a)*p,I=Y}else H=T-w;const S=Math.floor(w/p),D=a+1500;for(let Y=0;Y<I;++Y)v[Y]>=a&&(v[Y]=Math.min(v[Y]+S,D));b.push(...v.slice(0,I)),j&&M.push(...j.slice(0,I)),w+=H}b.push(i);const E=[...n,...b];if(c){const T=new K("int64",E.map(BigInt),[1,E.length]),C=[...new Array(n.length).fill(0),...M,0],P=new K("float32",new Float32Array(C),[1,C.length]);return{sequences:T,token_timestamps:P}}return new K("int64",E.map(BigInt),[1,E.length])}_extract_token_timestamps(e,t,r=null,n=.02,s=0){if(!e.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");r==null&&be.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&&(be.warn("Model config has no `median_filter_width`, using default value of 7."),a=7);const i=e.cross_attentions,c=Array.from({length:this.config.decoder_layers},(E,T)=>je(i.map(C=>C[T]),2)),u=Gr(t.map(([E,T])=>{if(E>=c.length)throw new Error(`Layer index ${E} is out of bounds for cross attentions (length ${c.length}).`);return r?c[E].slice(null,T,null,[0,r]):c[E].slice(null,T)})).transpose(1,0,2,3),[h,p]=XE(u,-2,0,!0),_=u.clone();for(let E=0;E<_.dims[0];++E){const T=_[E];for(let C=0;C<T.dims[0];++C){const P=T[C],A=h[E][C][0].data,F=p[E][C][0].data;for(let G=0;G<P.dims[0];++G){let v=P[G].data;for(let j=0;j<v.length;++j)v[j]=(v[j]-F[j])/A[j];v.set(LE(v,a))}}}const m=s>0?_.slice(null,null,[s,_.dims[2]],null):_,w=[Zh(m,1)],b=e.sequences.dims,M=new K("float32",new Float32Array(b[0]*b[1]),b);for(let E=0;E<b[0];++E){const T=w[E].neg().squeeze_(0),[C,P]=NE(T.tolist()),A=Array.from({length:C.length-1},(j,U)=>C[U+1]-C[U]),F=Tr([1],A).map(j=>!!j),G=[];for(let j=0;j<F.length;++j)F[j]&&G.push(P[j]*n);const v=new Array(s).fill(0);v.push(...G),G.length>0&&v.push(G.at(-1)),M[E].data.set(v)}return M}},m4=class extends Cb{},js=class extends O{},g4=class extends js{},w4=class extends js{async _call(e){return new mt(await super._call(e))}},y4=class extends js{async _call(e){return new fe(await super._call(e))}},v4=class extends js{async _call(e){return new at(await super._call(e))}},b4=class extends js{async _call(e){return new Ft(await super._call(e))}},qs=class extends O{},M4=class extends qs{},x4=class extends qs{async _call(e){return new mt(await super._call(e))}},T4=class extends qs{async _call(e){return new fe(await super._call(e))}},E4=class extends qs{async _call(e){return new at(await super._call(e))}},k4=class extends qs{async _call(e){return new Ft(await super._call(e))}},pm=class extends O{},C4=class extends pm{},A4=class extends pm{async _call(e){return new Ab(await super._call(e))}},Ab=class extends _t{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},_m=class extends O{},S4=class extends _m{},P4=class extends _m{},F4=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"]]),I4=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"]]),L4=new Map([["mimi","MimiModel"],["dac","DacModel"],["snac","SnacModel"]]),O4=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"]]),Sb=new Map([["speecht5","SpeechT5ForSpeechToText"],["whisper","WhisperForConditionalGeneration"],["lite-whisper","LiteWhisperForConditionalGeneration"],["moonshine","MoonshineForConditionalGeneration"],["cohere_asr","CohereAsrForConditionalGeneration"]]),Pb=new Map([["speecht5","SpeechT5ForTextToSpeech"]]),Fb=new Map([["vits","VitsModel"],["musicgen","MusicgenForConditionalGeneration"],["supertonic","SupertonicForConditionalGeneration"]]),Ib=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"]]),Lb=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"]]),Ob=new Map([["t5","T5ForConditionalGeneration"],["longt5","LongT5ForConditionalGeneration"],["mt5","MT5ForConditionalGeneration"],["bart","BartForConditionalGeneration"],["mbart","MBartForConditionalGeneration"],["marian","MarianMTModel"],["m2m_100","M2M100ForConditionalGeneration"],["blenderbot","BlenderbotForConditionalGeneration"],["blenderbot-small","BlenderbotSmallForConditionalGeneration"]]),Nb=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"]]),N4=new Map([["multi_modality","MultiModalityCausalLM"]]),Bb=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"]]),$b=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"]]),Db=new Map([["vision-encoder-decoder","VisionEncoderDecoderModel"],["idefics3","Idefics3ForConditionalGeneration"],["smolvlm","SmolVLMForConditionalGeneration"]]),Rb=new 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Map([[1,"float32"],[10,"float16"],[6,"int32"],[12,"uint32"],[7,"int64"],[13,"uint64"],[22,"int4"],[21,"uint4"],[3,"int8"],[2,"uint8"],[9,"uint8"]]),kw=(e,t)=>{if(e===t)return!0;if(e===void 0||t===void 0)return!1;let r=Object.keys(e).sort(),n=Object.keys(t).sort();return r.length===n.length&&r.every((s,a)=>s===n[a]&&e[s]===t[s])},DM=class{constructor(e){this.tensorManager=BM(this),this.mlContextBySessionId=new Map,this.sessionIdsByMLContext=new Map,this.mlContextCache=[],this.sessionGraphInputs=new Map,this.sessionGraphOutputs=new Map,this.temporaryGraphInputs=[],this.temporaryGraphOutputs=[],this.temporarySessionTensorIds=new Map,this.mlOpSupportLimitsBySessionId=new Map,OM(e.logLevel,!!e.debug)}get currentSessionId(){if(this.activeSessionId===void 0)throw new Error("No active session");return this.activeSessionId}onRunStart(e){Ct("verbose",()=>`[WebNN] onRunStart {sessionId: ${e}}`),this.activeSessionId=e}onRunEnd(e){Ct("verbose",()=>`[WebNN] onRunEnd {sessionId: ${e}}`);let t=this.temporarySessionTensorIds.get(e);if(t){for(let r of t)Ct("verbose",()=>`[WebNN] releasing temporary tensor {tensorId: ${r}}`),this.tensorManager.releaseTensorId(r);this.temporarySessionTensorIds.delete(e),this.activeSessionId=void 0}}async createMLContext(e){if(e instanceof GPUDevice){let r=this.mlContextCache.findIndex(n=>n.gpuDevice===e);if(r!==-1)return this.mlContextCache[r].mlContext;{let n=await navigator.ml.createContext(e);return this.mlContextCache.push({gpuDevice:e,mlContext:n}),n}}else if(e===void 0){let r=this.mlContextCache.findIndex(n=>n.options===void 0&&n.gpuDevice===void 0);if(r!==-1)return this.mlContextCache[r].mlContext;{let n=await navigator.ml.createContext();return this.mlContextCache.push({mlContext:n}),n}}let t=this.mlContextCache.findIndex(r=>kw(r.options,e));if(t!==-1)return this.mlContextCache[t].mlContext;{let r=await navigator.ml.createContext(e);return this.mlContextCache.push({options:e,mlContext:r}),r}}registerMLContext(e,t){this.mlContextBySessionId.set(e,t);let r=this.sessionIdsByMLContext.get(t);r||(r=new Set,this.sessionIdsByMLContext.set(t,r)),r.add(e),this.mlOpSupportLimitsBySessionId.has(e)||this.mlOpSupportLimitsBySessionId.set(e,t.opSupportLimits()),this.temporaryGraphInputs.length>0&&(this.sessionGraphInputs.set(e,this.temporaryGraphInputs),this.temporaryGraphInputs=[]),this.temporaryGraphOutputs.length>0&&(this.sessionGraphOutputs.set(e,this.temporaryGraphOutputs),this.temporaryGraphOutputs=[])}onReleaseSession(e){this.sessionGraphInputs.delete(e),this.sessionGraphOutputs.delete(e);let t=this.mlContextBySessionId.get(e);if(!t)return;this.tensorManager.releaseTensorsForSession(e),this.mlContextBySessionId.delete(e),this.mlOpSupportLimitsBySessionId.delete(e);let r=this.sessionIdsByMLContext.get(t);if(r.delete(e),r.size===0){this.sessionIdsByMLContext.delete(t);let n=this.mlContextCache.findIndex(s=>s.mlContext===t);n!==-1&&this.mlContextCache.splice(n,1)}}getMLContext(e){return this.mlContextBySessionId.get(e)}getMLOpSupportLimits(e){return this.mlOpSupportLimitsBySessionId.get(e)}reserveTensorId(){return this.tensorManager.reserveTensorId()}releaseTensorId(e){Ct("verbose",()=>`[WebNN] releaseTensorId {tensorId: ${e}}`),this.tensorManager.releaseTensorId(e)}async ensureTensor(e,t,r,n,s){let a=ci.get(r);if(!a)throw new Error(`Unsupported ONNX data type: ${r}`);return this.tensorManager.ensureTensor(e??this.currentSessionId,t,a,n,s)}async createTemporaryTensor(e,t,r){Ct("verbose",()=>`[WebNN] createTemporaryTensor {onnxDataType: ${t}, shape: ${r}}`);let n=ci.get(t);if(!n)throw new Error(`Unsupported ONNX data type: ${t}`);let s=this.tensorManager.reserveTensorId();await this.tensorManager.ensureTensor(e,s,n,r,!1);let a=this.temporarySessionTensorIds.get(e);return a?a.push(s):this.temporarySessionTensorIds.set(e,[s]),s}uploadTensor(e,t){if(!Ge().shouldTransferToMLTensor)throw new Error("Trying to upload to a MLTensor while shouldTransferToMLTensor is false");Ct("verbose",()=>`[WebNN] uploadTensor {tensorId: ${e}, data: ${t.byteLength}}`),this.tensorManager.upload(e,t)}async downloadTensor(e,t){return this.tensorManager.download(e,t)}createMLTensorDownloader(e,t){return async()=>{let r=await this.tensorManager.download(e);return LM(r,t)}}registerMLTensor(e,t,r,n){let s=ci.get(r);if(!s)throw new Error(`Unsupported ONNX data type: ${r}`);let a=this.tensorManager.registerTensor(e,t,s,n);return Ct("verbose",()=>`[WebNN] registerMLTensor {tensor: ${t}, dataType: ${s}, dimensions: ${n}} -> {tensorId: ${a}}`),a}registerMLConstant(e,t,r,n,s,a,i=!1){if(!a)throw new Error("External mounted files are not available.");let c=e;e.startsWith("./")&&(c=e.substring(2));let u=a.get(c);if(!u)throw new Error(`File with name ${c} not found in preloaded 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