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e!=`object`)return`${t} must be a valid object`;for(let r of n)if(!(r in e))return`${t} must contain a "${r}" property`;return null},Ai=e=>e.match(/\S+/g)||[],ji=class{constructor(){let e=function(...t){return e._call(...t)};return Object.setPrototypeOf(e,new.target.prototype)}},Mi=class extends ji{constructor(e){super(),this.config=e}_call(e){return this.normalize(e)}},Ni=class extends Mi{tokenize_chinese_chars(e){let t=[];for(let n=0;ne.normalize(`NFKC`)).join(`～`):e.normalize(`NFKC`),e}},Fi=class extends Mi{constructor(e){super(e),this.normalizers=(e.normalizers??[]).map(e=>qi(e))}normalize(e){return this.normalizers.reduce((e,t)=>t?t.normalize(e):e,e)}},Ii=class extends Mi{normalize(e){let t=vi(this.config.pattern??{});return t===null?e:e.replaceAll(t,this.config.content??``)}},Li=class extends Mi{constructor(){super(...arguments),this.form=`NFC`}normalize(e){return e=e.normalize(this.form),e}},Ri=class extends Li{constructor(){super(...arguments),this.form=`NFC`}},zi=class extends Li{constructor(){super(...arguments),this.form=`NFD`}},Bi=class extends Li{constructor(){super(...arguments),this.form=`NFKC`}},Vi=class extends Li{constructor(){super(...arguments),this.form=`NFKD`}},Hi=class extends Mi{normalize(e){return this.config.strip_left&&this.config.strip_right?e=e.trim():(this.config.strip_left&&(e=e.trimStart()),this.config.strip_right&&(e=e.trimEnd())),e}},Ui=class extends Mi{normalize(e){return Oi(e)}},Wi=class extends Mi{normalize(e){return e.toLowerCase()}},Gi=class extends Mi{normalize(e){return e=this.config.prepend+e,e}};function Ki(e){if(e===null)return null;switch(e.type){case`BertNormalizer`:return new Ni(e);case`Precompiled`:return new Pi(e);case`Sequence`:return new Fi(e);case`Replace`:return new Ii(e);case`NFC`:return new Ri(e);case`NFD`:return new zi(e);case`NFKC`:return new Bi(e);case`NFKD`:return new Vi(e);case`Strip`:return new Hi(e);case`StripAccents`:return new Ui(e);case`Lowercase`:return new Wi(e);case`Prepend`:return new Gi(e);default:throw Error(`Unknown Normalizer type: ${e.type}`)}}var qi=Ki,Ji=class extends ji{pre_tokenize(e,t){return(Array.isArray(e)?e.map(e=>this.pre_tokenize_text(e,t)):this.pre_tokenize_text(e,t)).flat()}_call(e,t){return this.pre_tokenize(e,t)}},Yi=class extends Ji{constructor(e){super(),this.config=e,this.add_prefix_space=this.config.add_prefix_space??!1,this.trim_offsets=this.config.trim_offsets??!1,this.use_regex=this.config.use_regex??!0,this.pattern=/'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+/gu,this.byte_encoder=fi,this.text_encoder=new TextEncoder}pre_tokenize_text(e,t){return this.add_prefix_space&&!e.startsWith(` `)&&(e=` `+e),(this.use_regex?e.match(this.pattern)||[]:[e]).map(e=>Array.from(this.text_encoder.encode(e),e=>this.byte_encoder[e]).join(``))}},Xi=class extends Ji{pre_tokenize_text(e,t){return e.match(/\w+|[^\w\s]+/g)||[]}},Zi=class extends Ji{constructor(e){super(),this.replacement=e.replacement??`▁`,this.str_rep=e.str_rep||this.replacement,this.prepend_scheme=e.prepend_scheme??`always`}pre_tokenize_text(e,t){let{section_index:n=void 0}=t??{},r=e.replaceAll(` `,this.str_rep);return!r.startsWith(this.replacement)&&(this.prepend_scheme===`always`||this.prepend_scheme===`first`&&n===0)&&(r=this.str_rep+r),[r]}},Qi=class extends Ji{constructor(e){super(),this.config=e,this.pattern=vi(this.config.pattern??{},this.config.invert??!0)}pre_tokenize_text(e){return this.pattern===null?[]:this.config.invert?e.match(this.pattern)||[]:this.config.behavior?.toLowerCase()===`removed`?e.split(this.pattern).filter(e=>e):Di(e,this.pattern)}},$i=class extends Ji{constructor(e){super(),this.config=e,this.pattern=RegExp(`[^${gi}]+|[${gi}]+`,`gu`)}pre_tokenize_text(e){return e.match(this.pattern)||[]}},ea=class extends Ji{constructor(e){super(),this.config=e;let t=`[^\\d]+|\\d${this.config.individual_digits?``:`+`}`;this.pattern=new 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r=!1,i=0,a=[];for(;i0&&(r=this.config.continuing_subword_prefix+r),this.tokens_to_ids.has(r)){n=r;break}--t}if(n===null){r=!0;break}a.push(n),i=t}r?t.push(this.unk_token):t.push(...a)}return t}},sa=class e{constructor(e,t){this.is_leaf=e,this.children=t}static default(){return new e(!1,new Map)}},ca=class{constructor(){this.root=sa.default()}extend(e){for(let t of e)this.push(t)}push(e){let t=this.root;for(let n of e){let e=t.children.get(n);e===void 0&&(e=sa.default(),t.children.set(n,e)),t=e}t.is_leaf=!0}*common_prefix_search(e){let t=this.root;if(t===void 0)return;let n=``;for(let r of e){if(n+=r,t=t.children.get(r),t===void 0)return;t.is_leaf&&(yield n)}}},la=class e{constructor(e,t,n,r,i){this.token_id=e,this.node_id=t,this.pos=n,this.length=r,this.score=i,this.prev=null,this.backtrace_score=0}clone(){let t=new e(this.token_id,this.node_id,this.pos,this.length,this.score);return t.prev=this.prev,t.backtrace_score=this.backtrace_score,t}},ua=class{constructor(e,t,n){this.chars=Array.from(e),this.len=this.chars.length,this.bos_token_id=t,this.eos_token_id=n,this.nodes=[],this.begin_nodes=Array.from({length:this.len+1},()=>[]),this.end_nodes=Array.from({length:this.len+1},()=>[]);let r=new la(this.bos_token_id??0,0,0,0,0),i=new la(this.eos_token_id??0,1,this.len,0,0);this.nodes.push(r.clone()),this.nodes.push(i.clone()),this.begin_nodes[this.len].push(i),this.end_nodes[0].push(r)}insert(e,t,n,r){let i=this.nodes.length,a=new la(r,i,e,t,n);this.begin_nodes[e].push(a),this.end_nodes[e+t].push(a),this.nodes.push(a)}viterbi(){let e=this.len,t=0;for(;t<=e;){if(this.begin_nodes[t].length==0)return[];for(let e of this.begin_nodes[t]){e.prev=null;let n=0,r=null;for(let i of this.end_nodes[t]){let t=i.backtrace_score+e.score;(r===null||t>n)&&(r=i.clone(),n=t)}if(r!==null)e.prev=r,e.backtrace_score=n;else return[]}++t}let n=[],r=this.begin_nodes[e][0].prev;if(r===null)return[];let i=r.clone();for(;i.prev!==null;)n.push(i.clone()),i=i.clone().prev.clone();return n.reverse(),n}piece(e){return this.chars.slice(e.pos,e.pos+e.length).join(``)}tokens(){return this.viterbi().map(e=>this.piece(e))}token_ids(){return this.viterbi().map(e=>e.token_id)}};function da(e){if(e.length===0)throw Error(`Array must not be empty`);let t=e[0],n=0;for(let r=1;r[e,t])),this.bos_token=` `,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.unk_token=this.vocab[this.unk_token_id],this.min_score=da(this.scores)[0],this.unk_score=this.min_score-10,this.scores[this.unk_token_id]=this.unk_score,this.trie=new ca,this.trie.extend(this.vocab),this.fuse_unk=!0}populate_nodes(e){let t=e.chars,n=0;for(;ne>t,t=1/0){this._heap=[],this._comparator=e,this._max_size=t}get size(){return this._heap.length}is_empty(){return this.size===0}peek(){return this._heap[0]}push(...e){return this.extend(e)}extend(e){for(let t of e)if(this.size0&&this._swap(0,t),this._heap.pop(),this._sift_down(),e}replace(e){let t=this.peek();return this._heap[0]=e,this._sift_down(),t}_parent(e){return(e+1>>>1)-1}_left(e){return(e<<1)+1}_right(e){return e+1<<1}_greater(e,t){return this._comparator(this._heap[e],this._heap[t])}_swap(e,t){let n=this._heap[e];this._heap[e]=this._heap[t],this._heap[t]=n}_sift_up(){this._sift_up_from(this.size-1)}_sift_up_from(e){for(;e>0&&this._greater(e,this._parent(e));)this._swap(e,this._parent(e)),e=this._parent(e)}_sift_down(){let e=0;for(;this._left(e)this.capacity&&this.cache.delete(this.cache.keys().next().value)}clear(){this.cache.clear()}},ha=class extends L{constructor(e){super(e),this.tokens_to_ids=Ei(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.vocab=Array(this.tokens_to_ids.size);for(let[e,t]of this.tokens_to_ids)this.vocab[t]=e;this.merges=Array.isArray(e.merges[0])?e.merges:e.merges.map(e=>e.split(` `,2)),this.bpe_ranks=new Map(this.merges.map((e,t)=>[JSON.stringify(e),t])),this.end_of_word_suffix=e.end_of_word_suffix,this.continuing_subword_suffix=e.continuing_subword_suffix??null,this.byte_fallback=this.config.byte_fallback??!1,this.byte_fallback&&(this.text_encoder=new TextEncoder),this.ignore_merges=this.config.ignore_merges??!1,this.max_length_to_cache=256,this.cache_capacity=1e4,this.cache=new ma(this.cache_capacity)}clear_cache(){this.cache.clear()}bpe(e){if(e.length===0)return[];let t=this.cache.get(e);if(t!==void 0)return t;let n=Array.from(e);this.end_of_word_suffix&&(n[n.length-1]+=this.end_of_word_suffix);let r=[];if(n.length>1){let e=new pa((e,t)=>e.score`<0x${e.toString(16).toUpperCase().padStart(2,`0`)}>`);e.every(e=>this.tokens_to_ids.has(e))?t.push(...e):this.unk_token!=null&&t.push(this.unk_token)}else this.unk_token!=null&&t.push(this.unk_token)}return t}},ga=class extends L{constructor(e,t){super(e);let n=e.vocab;this.tokens_to_ids=Ei(t.target_lang?n[t.target_lang]:n),this.bos_token=t.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=t.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=t.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=Array(this.tokens_to_ids.size);for(let[e,t]of this.tokens_to_ids)this.vocab[t]=e}encode(e){return e}};function _a(e,t){switch(e.type){case`WordPiece`:return new oa(e);case`Unigram`:return new fa(e,t.eos_token);case`BPE`:return new ha(e);default:if(e.vocab)return Array.isArray(e.vocab)?new fa(e,t.eos_token):Object.hasOwn(e,`continuing_subword_prefix`)&&Object.hasOwn(e,`unk_token`)?Object.hasOwn(e,`merges`)?new ha(e):new oa(e):new ga(e,{target_lang:t.target_lang,bos_token:t.bos_token,eos_token:t.eos_token,pad_token:t.pad_token,unk_token:t.unk_token});throw Error(`Unknown TokenizerModel type: ${e?.type}`)}}var va=_a,ya=class extends ji{constructor(e){super(),this.config=e}_call(e,...t){return this.post_process(e,...t)}},ba=class extends ya{post_process(e,t=null,n=!0){let r=t===null?this.config.single:this.config.pair,i=[],a=[];for(let o of r)`SpecialToken`in o?n&&(i.push(o.SpecialToken.id),a.push(o.SpecialToken.type_id)):`Sequence`in o&&(o.Sequence.id===`A`?(i=Ti(i,e),a=Ti(a,Array(e.length).fill(o.Sequence.type_id))):o.Sequence.id===`B`&&(i=Ti(i,t),a=Ti(a,Array(t.length).fill(o.Sequence.type_id))));return{tokens:i,token_type_ids:a}}},xa=class extends ya{post_process(e,t=null){return{tokens:e,tokens_pair:t}}},Sa=class extends ya{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t=null,n=!0){n&&(e=Ti([this.cls[0]],e,[this.sep[0]]));let r=Array(e.length).fill(0);if(t){let i=[],a=n?[this.sep[0]]:[];e=Ti(e,i,t,a),r=Ti(r,Array(t.length+i.length+a.length).fill(1))}return{tokens:e,token_type_ids:r}}},Ca=class extends ya{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t,n=!0){n&&(e=Ti([this.cls[0]],e,[this.sep[0]]));let r=Array(e.length).fill(0);if(t){let i=n?[this.sep[0]]:[],a=n?[this.sep[0]]:[];e=Ti(e,i,t,a),r=Ti(r,Array(t.length+i.length+a.length).fill(1))}return{tokens:e,token_type_ids:r}}},wa=class extends ya{constructor(e){super(e),this.processors=(e.processors??[]).map(e=>Ea(e))}post_process(e,t=null,n=!0){let r={tokens:e,tokens_pair:t};for(let e of this.processors)r=e.post_process(r.tokens,r.tokens_pair,n);return r}};function Ta(e){if(e===null)return null;switch(e.type){case`TemplateProcessing`:return new ba(e);case`ByteLevel`:return new xa(e);case`BertProcessing`:return new Sa(e);case`RobertaProcessing`:return new Ca(e);case`Sequence`:return new wa(e);default:throw Error(`Unknown PostProcessor type: ${e.type}`)}}var Ea=Ta,Da=class extends ji{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(``)}},Oa=class extends Da{constructor(e){super(e),this.byte_decoder=pi,this.text_decoder=new TextDecoder(`utf-8`,{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){let t=e.join(``),n=new Uint8Array([...t].map(e=>this.byte_decoder[e]));return this.text_decoder.decode(n)}decode_chain(e){let t=[],n=[];for(let r of e)this.added_tokens.find(e=>e.content===r)===void 0?n.push(r):(n.length>0&&(t.push(this.convert_tokens_to_string(n)),n=[]),t.push(r));return n.length>0&&t.push(this.convert_tokens_to_string(n)),t}},ka=class extends Da{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map((e,t)=>{if(t!==0){let t=this.config.prefix;e=t&&e.startsWith(t)?e.replace(t,``):` `+e}return this.cleanup&&(e=_i(e)),e})}},Aa=class extends Da{constructor(e){super(e),this.replacement=e.replacement??`▁`}decode_chain(e){let t=[];for(let n=0;nt.replaceAll(this.suffix,n===e.length-1?``:` `))}},Ma=class extends Da{constructor(e){super(e),this.pad_token=e.pad_token??``,this.word_delimiter_token=e.word_delimiter_token??``,this.cleanup=e.cleanup}convert_tokens_to_string(e){if(e.length===0)return``;let t=[e[0]];for(let n=1;ne!==this.pad_token).join(``);return this.cleanup&&(n=_i(n).replaceAll(this.word_delimiter_token,` `).trim()),n}decode_chain(e){return[this.convert_tokens_to_string(e)]}},Na=class extends Da{constructor(e){super(e),this.decoders=(e.decoders??[]).map(e=>za(e))}decode_chain(e){return this.decoders.reduce((e,t)=>t.decode_chain(e),e)}},Pa=class extends Da{decode_chain(e){let t=vi(this.config.pattern),n=this.config.content??``;return t===null?e:e.map(e=>e.replaceAll(t,n))}},Fa=class extends Da{decode_chain(e){return[e.join(``)]}},Ia=class extends Da{constructor(e){super(e),this.content=e.content??``,this.start=e.start??0,this.stop=e.stop??0}decode_chain(e){return e.map(e=>{let t=0;for(let n=0;n`)){let t=parseInt(r.slice(3,5),16);isNaN(t)||(e=t)}if(e!==null)n.push(e);else{if(n.length>0){let e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}t.push(r)}}if(n.length>0){let e=this.text_decoder.decode(Uint8Array.from(n));t.push(e),n=[]}return t}};function Ra(e){if(e===null)return null;switch(e.type){case`ByteLevel`:return new Oa(e);case`WordPiece`:return new ka(e);case`Metaspace`:return new Aa(e);case`BPEDecoder`:return new ja(e);case`CTC`:return new Ma(e);case`Sequence`:return new Na(e);case`Replace`:return new Pa(e);case`Fuse`:return new Fa(e);case`Strip`:return new Ia(e);case`ByteFallback`:return new La(e);default:throw Error(`Unknown Decoder type: ${e.type}`)}}var za=Ra,Ba=class{constructor(e,t){let n=ki(e,`Tokenizer`,[`model`,`decoder`,`post_processor`,`pre_tokenizer`,`normalizer`]);if(n)throw Error(n);let r=ki(t,`Config`);if(r)throw Error(r);this.tokenizer=e,this.config=t,this.normalizer=qi(this.tokenizer.normalizer),this.pre_tokenizer=aa(this.tokenizer.pre_tokenizer),this.model=va(this.tokenizer.model,this.config),this.post_processor=Ea(this.tokenizer.post_processor),this.decoder=za(this.tokenizer.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];let i=[],a=[];this.added_tokens_map=new Map;for(let e of this.tokenizer.added_tokens){let t=new di(e);if(this.added_tokens.push(t),this.model.tokens_to_ids.set(t.content,t.id),this.model.vocab[t.id]=t.content,t.special&&(this.special_tokens.push(t.content),this.all_special_ids.push(t.id)),this.added_tokens_map.set(t.content,t),t.normalized&&this.normalizer!==null){let e=this.normalizer(t.content);a.push(e),this.added_tokens_map.set(e,t)}else i.push(t.content)}(this.config.additional_special_tokens??[]).forEach(e=>{this.special_tokens.includes(e)||this.special_tokens.push(e)}),this.decoder&&(this.decoder.added_tokens=this.added_tokens,this.decoder.end_of_word_suffix=this.model.end_of_word_suffix),this.splitter_unnormalized=new ui(i),this.splitter_normalized=new ui(a),this.remove_space=this.config.remove_space,this.clean_up_tokenization_spaces=this.config.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=this.config.do_lowercase_and_remove_accent??!1}encode(e,{text_pair:t=null,add_special_tokens:n=!0,return_token_type_ids:r=null}={}){let{tokens:i,token_type_ids:a}=this.tokenize_helper(e,{text_pair:t,add_special_tokens:n}),o=i.map(e=>this.added_tokens_map.get(e)?.id??this.model.tokens_to_ids.get(e)??this.model.unk_token_id),s={ids:o,tokens:i,attention_mask:Array(o.length).fill(1)};return r&&a&&(s.token_type_ids=a),s}decode(e,t={}){if(!Array.isArray(e)||e.length===0||!Si(e[0]))throw Error(`token_ids must be 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instanceof ServiceWorkerGlobalScope)&&Lc.versions?.web&&!Lc.wasm.wasmPaths){let e=`https://cdn.jsdelivr.net/npm/onnxruntime-web@${Lc.versions.web}/dist/`;Lc.wasm.wasmPaths=M.IS_SAFARI?{mjs:`${e}ort-wasm-simd-threaded.mjs`,wasm:`${e}ort-wasm-simd-threaded.wasm`}:{mjs:`${e}ort-wasm-simd-threaded.asyncify.mjs`,wasm:`${e}ort-wasm-simd-threaded.asyncify.wasm`}}Lc.wasm.proxy=!1}Lc.webgpu&&(Lc.webgpu.powerPreference=`high-performance`),e(N.logLevel??Xr.WARNING),N.backends.onnx={...Lc,setLogLevel:e}}var zc=async(e,t,n)=>{let r=await Nc(new Uint8Array(e),t);return(async e=>{let t=Rc(),i=await Fc(r,Object.fromEntries(Object.entries(e).map(([e,n])=>[e,(t?n.clone():n).ort_tensor])));return Array.isArray(n)?n.map(e=>new W(i[e])):new W(i[n])})},Bc=class{static session_options={};static get nearest_interpolate_4d(){return this._nearest_interpolate_4d||=zc([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||=zc([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||=zc([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||=zc([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||=zc([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||=zc([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||=zc([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||=zc([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}},Vc=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`}),Hc=M.IS_NODE_ENV?`cpu`:`wasm`;function Uc(e,t,{warn:n}={}){return e?typeof e==`string`?e:e.hasOwnProperty(t)?e[t]:(n&&n(`device not 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Error(`The tensor must have 2 dimensions`);if(e.dims.at(-1)%8!=0)throw Error(`The last dimension of the tensor must be a multiple of 8`);if(![`binary`,`ubinary`].includes(t))throw Error(`The precision must be either 'binary' or 'ubinary'`);let n=t===`binary`,r=n?`int8`:`uint8`,i=n?Int8Array:Uint8Array,a=e.data,o=new i(a.length/8);for(let e=0;e0?1:0,r=Math.floor(e/8),i=e%8;o[r]|=t<<7-i,n&&i===0&&(o[r]-=128)}return new W(r,o,[e.dims[0],e.dims[1]/8])}async function wl(e){if(!e)throw Error(`modelId is required for get_tokenizer_files`);return(await Us(e,`tokenizer_config.json`,{})).exists?[`tokenizer.json`,`tokenizer_config.json`]:[]}async function Tl(e,t){let n=await wl(e);return await Promise.all(n.map(n=>ec(e,n,!0,t)))}function El(e){let t=e.dims;switch(t.length){case 1:return e.tolist();case 2:if(t[0]!==1)throw Error("Unable to decode tensor with `batch size !== 1`. 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Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(n).sort()}.`)}else if(e===null)if(this.chat_template)e=this.chat_template;else throw Error(`Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation at https://huggingface.co/docs/transformers/main/en/chat_templating`);return e}apply_chat_template(e,{tools:t=null,documents:n=null,chat_template:r=null,add_generation_prompt:i=!1,tokenize:a=!0,padding:o=!1,truncation:s=!1,max_length:c=null,return_tensor:l=!0,return_dict:u=!0,tokenizer_kwargs:d={},...f}={}){if(r=this.get_chat_template({chat_template:r,tools:t}),typeof r!=`string`)throw Error(`chat_template must be a string, but got ${typeof r}`);let p=this._compiled_template_cache.get(r);p===void 0&&(p=new ms(r),this._compiled_template_cache.set(r,p));let m=Object.create(null);for(let e of Dl){let t=Al(this.config,e);t&&(m[e]=t)}let h=p.render({messages:e,add_generation_prompt:i,tools:t,documents:n,...m,...f});if(a){let e=this._call(h,{add_special_tokens:!1,padding:o,truncation:s,max_length:c,return_tensor:l,...d});return u?e:e.input_ids}return h}};function Ml(e,t,n,r){if(!(`language_codes`in e)||!Array.isArray(e.language_codes))throw Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!(`languageRegex`in e)||!(e.languageRegex instanceof RegExp))throw Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!(`lang_to_token`in e)||typeof e.lang_to_token!=`function`)throw Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");let i=r.src_lang,a=r.tgt_lang;if(!e.language_codes.includes(a))throw Error(`Target language code "${a}" is not valid. 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Also make sure WhisperTimeStampLogitsProcessor was used during generation.`);let[e,n]=this.findLongestCommonSequence(p,m),r=this.decode(e);l.text=r,o&&(l.words=this.collateWordTimestamps(e,n,a)),c.push(l)}let v=Object.create(null),y=c.map(e=>e.text).join(``);if(t||n){for(let e=0;e0,o=a?[]:null,s=a?t[0]:null;for(let c=1;ce===g[n]&&s[i+n][0]-Ou<=t[c][m+n][0]).length:p.filter((e,t)=>e===g[t]).length;let v=e/1e4,y=_/e+v;_>1&&y>u&&(u=y,d=[i,o,m,h])}let[p,m,h,g]=d,_=Math.floor((m+p)/2),v=Math.floor((g+h)/2);if(a&&u===0&&r>0){let e=s[r-1][0],n=t[c].findIndex(t=>t[0]>=e);v=n===-1?l.length:n}i.push(...n.slice(0,_)),n=l.slice(v),r=n.length,a&&(o.push(...s.slice(0,_)),s=t[c].slice(v))}return i.push(...n),a?(o.push(...s),[i,o]):[i,[]]}collateWordTimestamps(e,t,n){let[r,i,a]=this.combineTokensIntoWords(e,n),o=[];for(let e=0;e=r){let e=((t-r)*n).toFixed(2);i.push(`<|${e}|>`),i.push([])}else i[i.length-1].push(t);return i=i.map(e=>typeof e==`string`?e:super.decode(e,t)),i.join(``)}splitTokensOnUnicode(e){let t=this.decode(e,{decode_with_timestamps:!0}),n=[],r=[],i=[],a=[],o=[],s=0;for(let c=0;c=this._tokenizer.token_to_id(`<|endoftext|>`),d=s.startsWith(` `),f=s.trim(),p=Du.test(f);if(u||d||p||i.length===0)i.push(s),a.push(c),o.push(l);else{let e=i.length-1;i[e]+=s,a[e].push(...c),o[e].push(...l)}}return[i,a,o]}mergePunctuations(e,t,n,r,i){let a=structuredClone(e),o=structuredClone(t),s=structuredClone(n),c=a.length-2,l=a.length-1;for(;c>=0;)a[c].startsWith(` `)&&r.includes(a[c].trim())?(a[l]=a[c]+a[l],o[l]=ai(o[c],o[l]),s[l]=ai(s[c],s[l]),a[c]=``,o[c]=[],s[c]=[]):l=c,--c;for(c=0,l=1;le),o.filter(e=>e.length>0),s.filter(e=>e.length>0)]}},Au=class extends G{},ju=class extends G{return_token_type_ids=!0;constructor(e,t){super(e,t),P.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}},Mu=class{static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:a=`main`}={}){let[o,s]=await Tl(e,{progress_callback:t,config:n,cache_dir:r,local_files_only:i,revision:a}),c=s.tokenizer_class?.replace(/Fast$/,``)??`PreTrainedTokenizer`,l=Nl[c];return l||=(P.warn(`Unknown tokenizer class "${c}", attempting to construct from base class.`),G),new l(o,s)}},Nu=`https://github.com/huggingface/transformers.js/issues/new/choose`,Pu=`preprocessor_config.json`,Fu=Pu,Iu=`processor_config.json`,Lu=`chat_template.jinja`,K=class extends $r{static classes=[`image_processor_class`,`tokenizer_class`,`feature_extractor_class`];static uses_processor_config=!1;static uses_chat_template_file=!1;constructor(e,t,n){super(),this.config=e,this.components=t,this.chat_template=n}get image_processor(){return this.components.image_processor}get tokenizer(){return this.components.tokenizer}get feature_extractor(){return this.components.feature_extractor}apply_chat_template(e,t={}){if(!this.tokenizer)throw Error(`Unable to apply chat template without a tokenizer.`);return this.tokenizer.apply_chat_template(e,{tokenize:!1,chat_template:this.chat_template??void 0,...t})}batch_decode(...e){if(!this.tokenizer)throw Error(`Unable to decode without a tokenizer.`);return this.tokenizer.batch_decode(...e)}decode(...e){if(!this.tokenizer)throw Error(`Unable to decode without a tokenizer.`);return this.tokenizer.decode(...e)}async _call(e,...t){for(let n of[this.image_processor,this.feature_extractor,this.tokenizer])if(n)return n(e,...t);throw Error(`No image processor, feature extractor, or tokenizer found.`)}static async from_pretrained(e,t={}){let[n,r,i]=await Promise.all([this.uses_processor_config?ec(e,Iu,!0,t):{},Promise.all(this.classes.filter(e=>e in this).map(async n=>{let r=await this[n].from_pretrained(e,t);return[n.replace(/_class$/,``),r]})).then(Object.fromEntries),this.uses_chat_template_file?$s(e,Lu,!0,t):null]);return new this(n,r,i)}},Ru={};Sr(Ru,{ChatterboxProcessor:()=>jd,CohereAsrProcessor:()=>Nd,Florence2Processor:()=>Cp,Gemma3Processor:()=>wp,Gemma3nProcessor:()=>Tp,Gemma4Processor:()=>Ep,Glm46VProcessor:()=>Op,GraniteSpeechProcessor:()=>kp,GroundingDinoProcessor:()=>jp,Idefics3Processor:()=>Fp,JinaCLIPProcessor:()=>Lp,Lfm2VlProcessor:()=>Rp,LlavaProcessor:()=>zp,MgpstrProcessor:()=>Vp,MoonshineProcessor:()=>Hp,OwlViTProcessor:()=>Up,PaliGemmaProcessor:()=>Kp,Phi3VProcessor:()=>Yp,PixtralProcessor:()=>Xp,Processor:()=>K,PyAnnoteProcessor:()=>Zp,Qwen2VLProcessor:()=>Dp,Qwen2_5_VLProcessor:()=>Qp,Qwen3VLProcessor:()=>$p,Sam2Processor:()=>tm,Sam2VideoProcessor:()=>nm,SamProcessor:()=>em,SmolVLMProcessor:()=>Fp,SpeechT5Processor:()=>rm,UltravoxProcessor:()=>im,VLChatProcessor:()=>Ip,VoxtralProcessor:()=>lm,VoxtralRealtimeProcessor:()=>hm,Wav2Vec2Processor:()=>gm,Wav2Vec2ProcessorWithLM:()=>_m,WhisperProcessor:()=>vm});var zu=class extends $r{constructor(e){super(),this.config=e}static async from_pretrained(e,t={}){let n=await ec(e,Pu,!0,t);return new this(n)}};function Bu(e,t){if(!(e instanceof Float32Array||e instanceof Float64Array))throw Error(`${t} expects input to be a Float32Array or a Float64Array, but got ${e?.constructor?.name??typeof e} instead. 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For more information and some example code, see https://huggingface.co/docs/transformers.js/guides/node-audio-processing.");let n=await(await Gs(e)).arrayBuffer(),r=new AudioContext({sampleRate:t});t===void 0&&P.warn(`No sampling rate provided, using default of ${r.sampleRate}Hz.`);let i=await r.decodeAudioData(n),a;if(i.numberOfChannels===2){let e=Math.sqrt(2),t=i.getChannelData(0),n=i.getChannelData(1);a=new Float32Array(t.length);for(let r=0;r2595*Math.log10(1+e/700),kaldi:e=>1127*Math.log(1+e/700),slaney:(e,t=1e3,n=15,r=27/Math.log(6.4))=>e>=t?n+Math.log(e/t)*r:3*e/200};function Yu(e,t=`htk`){let n=Ju[t];if(!n)throw Error(`mel_scale should be one of "htk", "slaney" or "kaldi".`);return typeof e==`number`?n(e):e.map(e=>n(e))}var Xu={htk:e=>700*(10**(e/2595)-1),kaldi:e=>700*(Math.exp(e/1127)-1),slaney:(e,t=1e3,n=15,r=Math.log(6.4)/27)=>e>=n?t*Math.exp(r*(e-n)):200*e/3};function Zu(e,t=`htk`){let n=Xu[t];if(!n)throw Error(`mel_scale should be one of "htk", "slaney" or "kaldi".`);return typeof e==`number`?n(e):e.map(e=>n(e))}function Qu(e,t){let n=Float64Array.from({length:t.length-1},(e,n)=>t[n+1]-t[n]),r=Array.from({length:e.length},()=>Array(t.length));for(let n=0;nArray(e.length));for(let t=0;te+r*n)}function ed(e,t,n,r,i,a=null,o=`htk`,s=!1){if(a!==null&&a!==`slaney`)throw Error(`norm must be one of null or "slaney"`);if(e<2)throw Error(`Require num_frequency_bins: ${e} >= 2`);if(n>r)throw Error(`Require min_frequency: ${n} <= max_frequency: ${r}`);let c=$u(Yu(n,o),Yu(r,o),t+2),l=Zu(c,o),u;if(s){let t=i/((e-1)*2);u=Yu(Float64Array.from({length:e},(e,n)=>n*t),o),l=c}else u=$u(0,Math.floor(i/2),e);let d=Qu(u,l);if(a!==null&&a===`slaney`)for(let n=0;ni)throw Error(`frame_length (${n}) may not be larger than fft_length (${i})`);if(C!==n)throw Error(`Length of the window (${C}) must equal frame_length (${n})`);if(r<=0)throw Error(`hop_length must be greater than zero`);if(a===null&&d!==null)throw Error("You have provided `mel_filters` but `power` is `None`. Mel spectrogram computation is not yet supported for complex-valued spectrogram. Specify `power` to fix this issue.");if(!u)throw Error("`preemphasis_htk_flavor=false` is not currently supported.");if(o){let t=Math.floor(n/2);switch(s){case`reflect`:e=td(e,t,t);break;case`constant`:{let n=new e.constructor(e.length+2*t);n.set(e,t),e=n;break}case`semicausal`:{let n=new e.constructor(e.length+t);n.set(e,t),e=n;break}default:throw Error(`pad_mode="${s}" not implemented yet.`)}}let w=Math.floor(1+Math.floor((e.length-n)/r));y!==null&&ww?x&&(T=b):T=re=b);let E=new uc(i),ie=new Float64Array(i),ae=new Float64Array(E.outputBufferSize),oe=new Float32Array(ne*T);for(let i=0;i=1;--e)ie[e]-=l*ie[e-1];ie[0]*=1-l}for(let e=0;ee**.85);break;default:throw Error(`Unknown window type ${t}.`)}if(n&&(o=o.subarray(0,e)),r===null||e===r)return o;if(e>r)throw Error(`Length of the window (${e}) may not be larger than frame_length (${r})`);let s=new Float64Array(r),c=i?Math.floor((r-e)/2):0;return s.set(o,c),s}function sd(e,t){let n=e.reduce((e,t)=>e+t.length,0),r=new ArrayBuffer(44),i=new DataView(r);return cd(i,0,`RIFF`),i.setUint32(4,36+n*4,!0),cd(i,8,`WAVE`),cd(i,12,`fmt `),i.setUint32(16,16,!0),i.setUint16(20,3,!0),i.setUint16(22,1,!0),i.setUint32(24,t,!0),i.setUint32(28,t*4,!0),i.setUint16(32,4,!0),i.setUint16(34,32,!0),cd(i,36,`data`),i.setUint32(40,n*4,!0),new Blob([r,...e.map(e=>e.buffer)],{type:`audio/wav`})}function cd(e,t,n){for(let r=0;re+t.length,0),t=new Float32Array(e),n=0;for(let e of this.audio)t.set(e,n),n+=e.length;return t}else return this.audio}toBlob(){let e=this.audio;return e instanceof Float32Array&&(e=[e]),sd(e,this.sampling_rate)}async save(e){return Uu(e,this.toBlob())}},ud=class extends zu{constructor(e){super(e);let t=this.config.sampling_rate;this.mel_filters=ed(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0),this.window=od(400,`hann`,{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(e,t){return ad(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){Bu(e,`ASTFeatureExtractor`);let t=await this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){let e=this.std*2,n=t.data;for(let t=0;t0)if(n===`rand_trunc`){let n=Math.floor(bs.random()*(a+1));e=e.subarray(n,n+t),i=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}else throw Error(`Truncation strategy "${n}" not implemented`);else{if(a<0){let n=new Float64Array(t);if(n.set(e),r===`repeat`)for(let r=e.length;r=1;--n)e[n]-=t*e[n-1];return await ad(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){Bu(e,`ParakeetFeatureExtractor`);let t=await this._extract_fbank_features(e),n=Math.floor((e.length+Math.floor(this.config.n_fft/2)*2-this.config.n_fft)/this.config.hop_length),r=t.data;r.fill(0,n*t.dims[1]);let[i,a]=t.dims,o=new Float64Array(a),s=new Float64Array(a);for(let e=0;e1?n-1:1;for(let e=0;e=l){s.push(e.slice(c,l));break}let t=Math.max(c,c+a-o),n=Math.min(c+a,l),i;i=n<=t?c+a:this._find_split_point_energy(e,t,n,r),i=Math.max(c+1,Math.min(i,l)),s.push(e.slice(c,i)),c=i}return s}_find_split_point_energy(e,t,n,r){let i=n-t;if(i<=r)return Math.floor((t+n)/2);let a=1/0,o=t,s=i-r;for(let n=0;n<=s;n+=r){let i=0;for(let a=0;at&&(e=e.slice(0,t)),r&&e.length%i!==0){let t=i-e.length%i,n=new Float64Array(e.length+t);n.set(e),this.config.padding_value!==0&&n.fill(this.config.padding_value,e.length),e=n}let a=await this._extract_fbank_features(e,this.config.max_length),o=gl([1,a.dims[0]],!0);return{input_features:a.unsqueeze_(0),input_features_mask:o}}},yd=class extends vd{async _extract_fbank_features(e,t){let{frame_length:n,hop_length:r,fft_length:i}=this.config,a=Math.floor(n/2),o=Math.floor((e.length+a-(n+1))/r)+1;return ad(e,this.window,n,r,{fft_length:i,center:!0,pad_mode:`semicausal`,onesided:!0,preemphasis:this.config.preemphasis,preemphasis_htk_flavor:this.config.preemphasis_htk_flavor,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:this.config.mel_floor,mel_floor_mode:`add`,remove_dc_offset:!1,transpose:!0,max_num_frames:o})}async _call(e,t={}){Bu(e,`Gemma4AudioFeatureExtractor`);let n=e.length,r=await super._call(e,t),{input_features:i}=r,[,a,o]=i.dims,{frame_length:s,hop_length:c}=this.config,l=Math.floor(s/2),u=s+1,d=new Uint8Array(n+l+(t.pad_to_multiple_of??128));d.fill(1,l,l+n);let f=new Uint8Array(a);for(let e=0;e({id:e,start:t*n,end:r*n,confidence:i/(r-t)})))}return r}},Cd=class extends zu{constructor(e){super(e);let t=this.config.sampling_rate;this.mel_filters=ed(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0),this.window=od(400,`povey`,{periodic:!1})}async _extract_fbank_features(e,t){return e=e.map(e=>e*32768),ad(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e,{padding:t=!0,pad_to_multiple_of:n=2,do_normalize_per_mel_bins:r=!0,return_attention_mask:i=!0}={}){Bu(e,`SeamlessM4TFeatureExtractor`);let a=await this._extract_fbank_features(e,this.config.max_length);if(r){let[e,t]=a.dims,n=a.data;for(let r=0;r0){let n=new Float32Array(t*(e+s));n.set(r),n.fill(this.config.padding_value,r.length);let c=e+s;a=new W(a.type,n,[c,t]),i&&(o=new W(`int64`,new BigInt64Array(c),[1,c]),o.data.fill(1n,0,e))}}let[s,c]=a.dims,l=this.config.stride;if(s%l!==0)throw Error(`The number of frames (${s}) must be a multiple of the stride (${l}).`);let u=a.view(1,Math.floor(s/l),c*l),d={input_features:u};if(i){let e=u.dims[1],t=new BigInt64Array(e);if(o){let e=o.data;for(let n=1,r=0;ne+t,0)/e.length,n=e.reduce((e,n)=>e+(n-t)**2,0)/e.length;return e.map(e=>(e-t)/Math.sqrt(n+1e-7))}async _call(e){Bu(e,`Wav2Vec2FeatureExtractor`),e instanceof Float64Array&&(e=new Float32Array(e));let t=e;this.config.do_normalize&&(t=this._zero_mean_unit_var_norm(t));let n=[1,t.length];return{input_values:new W(`float32`,t,n),attention_mask:new W(`int64`,new BigInt64Array(t.length).fill(1n),n)}}},Dd=class extends zu{constructor(e){super(e);let t=this.config.sampling_rate;this.mel_filters=ed(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,`kaldi`,!0),this.window=od(400,`hamming`,{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(e){return e=e.map(e=>e*32768),ad(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:`log`,mel_floor:1.192092955078125e-7,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(e){Bu(e,`WeSpeakerFeatureExtractor`);let t=(await this._extract_fbank_features(e)).unsqueeze_(0);if(this.config.fbank_centering_span===null){let e=t.mean(1).data,n=t.data,[r,i,a]=t.dims;for(let t=0;tr?(e.length>this.config.n_samples&&P.warn("Attempting to extract features for audio longer than 30 seconds. If using a pipeline to extract transcript from a long audio clip, remember to specify `chunk_length_s` and/or `stride_length_s`."),n=e.slice(0,r)):(n=new Float32Array(r),n.set(e)),{input_features:(await this._extract_fbank_features(n)).unsqueeze_(0)}}},Ad=class{static async from_pretrained(e,t={}){let n=await ec(e,Pu,!0,t),r=n.feature_extractor_type,i=Vu[r];if(!i)throw Error(`Unknown feature_extractor_type: '${r}'. Please report this at ${Nu}.`);return new i(n)}},jd=class extends K{static tokenizer_class=Mu;static feature_extractor_class=Ad;async _call(e,t=null){let n=this.tokenizer(e),r=t?await this.feature_extractor(t):{};return{...n,...r}}},Md=new Set([`ja`,`zh`]),Nd=class extends K{static tokenizer_class=Mu;static feature_extractor_class=Ad;static uses_processor_config=!0;get_decoder_prompt_ids(e=`en`){let t=[`▁`,`<|startofcontext|>`,`<|startoftranscript|>`,`<|emo:undefined|>`,`<|${e}|>`,`<|${e}|>`,`<|pnc|>`,`<|noitn|>`,`<|notimestamp|>`,`<|nodiarize|>`];return this.tokenizer.convert_tokens_to_ids(t)}static join_chunks(e,t=`en`){let n=e.filter(e=>e&&e.trim());if(n.length===0)return``;let r=Md.has(t)?``:` `;return[n[0].trimEnd(),...n.slice(1).map(e=>e.trim())].join(r)}async _call(e){return await this.feature_extractor(e)}},Pd={},Fd,Id,Ld;if(M.IS_WEB_ENV)Fd=(e,t)=>{if(!self.OffscreenCanvas)throw Error(`OffscreenCanvas not supported by this environment.`);return new self.OffscreenCanvas(e,t)},Ld=self.createImageBitmap,Id=self.ImageData;else if(Pd)Ld=async e=>{let t=(await e.metadata()).channels,{data:n,info:r}=await e.rotate().raw().toBuffer({resolveWithObject:!0}),i=new Bd(new Uint8ClampedArray(n),r.width,r.height,r.channels);return t!==void 0&&t!==r.channels&&i.convert(t),i};else throw Error(`Unable to load image processing library.`);var Rd={0:`nearest`,1:`lanczos`,2:`bilinear`,3:`bicubic`,4:`box`,5:`hamming`},zd=new Map([[`png`,`image/png`],[`jpg`,`image/jpeg`],[`jpeg`,`image/jpeg`],[`gif`,`image/gif`]]),Bd=class e{constructor(e,t,n,r){this.data=e,this.width=t,this.height=n,this.channels=r}get size(){return[this.width,this.height]}static async read(t){if(t instanceof e)return t;if(typeof t==`string`||t instanceof URL)return await this.fromURL(t);if(t instanceof Blob)return await this.fromBlob(t);if(typeof HTMLCanvasElement<`u`&&t instanceof HTMLCanvasElement||typeof OffscreenCanvas<`u`&&t instanceof OffscreenCanvas)return this.fromCanvas(t);throw Error(`Unsupported input type: ${typeof t}`)}static fromCanvas(t){if(!M.IS_WEB_ENV)throw Error(`fromCanvas() is only supported in browser environments.`);let n=t.getContext(`2d`).getImageData(0,0,t.width,t.height).data;return new e(n,t.width,t.height,4)}static async fromURL(e){let t=await Gs(e);if(t.status!==200)throw Error(`Unable to read image from "${e}" (${t.status} ${t.statusText})`);let n=await t.blob();return this.fromBlob(n)}static async fromBlob(e){if(M.IS_WEB_ENV){let t=await Ld(e),n=Fd(t.width,t.height).getContext(`2d`);return n.drawImage(t,0,0),new this(n.getImageData(0,0,t.width,t.height).data,t.width,t.height,4)}else{let t=Pd(await e.arrayBuffer());return await Ld(t)}}static fromTensor(t,n=`CHW`){if(t.dims.length!==3)throw Error(`Tensor should have 3 dimensions, but has ${t.dims.length} dimensions.`);if(n===`CHW`)t=t.transpose(1,2,0);else if(n!==`HWC`)throw Error(`Unsupported channel format: ${n}`);if(!(t.data instanceof Uint8ClampedArray||t.data instanceof Uint8Array))throw Error(`Unsupported tensor type: ${t.type}`);switch(t.dims[2]){case 1:case 2:case 3:case 4:return new e(t.data,t.dims[1],t.dims[0],t.dims[2]);default:throw Error(`Unsupported number of channels: ${t.dims[2]}`)}}grayscale(){if(this.channels===1)return this;let e=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let t=0,n=0;t=0?c=r:u=-r,i>=0?l=i:d=-i,s.drawImage(o,c,l,t,n,u,d,t,n),new e(s.getImageData(0,0,t,n).data,t,n,4).convert(a)}else{let e=this.toSharp();if(r>=0&&i>=0)e=e.extract({left:Math.floor(r),top:Math.floor(i),width:t,height:n});else if(r<=0&&i<=0){let a=Math.floor(-i),o=Math.floor(-r);e=e.extend({top:a,left:o,right:t-this.width-o,bottom:n-this.height-a})}else{let a=[0,0],o=0;i<0?(a[0]=Math.floor(-i),a[1]=n-this.height-a[0]):o=Math.floor(i);let s=[0,0],c=0;r<0?(s[0]=Math.floor(-r),s[1]=t-this.width-s[0]):c=Math.floor(r),e=e.extend({top:a[0],bottom:a[1],left:s[0],right:s[1]}).extract({left:c,top:o,width:t,height:n})}return await Ld(e)}}async toBlob(e=`image/png`,t=1){if(!M.IS_WEB_ENV)throw Error(`toBlob() is only supported in browser environments.`);return await this.toCanvas().convertToBlob({type:e,quality:t})}toTensor(e=`CHW`){let t=new W(`uint8`,new Uint8Array(this.data),[this.height,this.width,this.channels]);if(e!==`HWC`)if(e===`CHW`)t=t.permute(2,0,1);else throw Error(`Unsupported channel format: ${e}`);return t}toCanvas(){if(!M.IS_WEB_ENV)throw Error(`toCanvas() is only supported in browser environments.`);let e=this.clone().rgba(),t=Fd(e.width,e.height),n=new Id(e.data,e.width,e.height);return t.getContext(`2d`).putImageData(n,0,0),t}split(){let{data:t,width:n,height:r,channels:i}=this,a=t.constructor,o=t.length/i,s=Array.from({length:i},()=>new a(o));for(let e=0;enew e(t,n,r,1))}_update(e,t,n,r=null){return this.data=e,this.width=t,this.height=n,r!==null&&(this.channels=r),this}clone(){return new e(this.data.slice(),this.width,this.height,this.channels)}convert(e){if(this.channels===e)return this;switch(e){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(e){if(M.IS_WEB_ENV){if(M.IS_WEBWORKER_ENV)throw Error(`Unable to save an image from a Web Worker.`);let t=e.split(`.`).pop().toLowerCase(),n=zd.get(t)??`image/png`;return Uu(e,await this.toBlob(n))}else if(M.IS_FS_AVAILABLE)await this.toSharp().toFile(e);else throw Error(`Unable to save the image because filesystem is disabled in this environment.`)}toSharp(){if(M.IS_WEB_ENV)throw Error(`toSharp() is only supported in server-side environments.`);return Pd(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}},Vd=Bd.read.bind(Bd);function Hd(e,t,n=0,r=null){let i=e/t,a=pc(i)*t;return r!==null&&a>r&&(a=Math.floor(i)*t),at&&i.push(e)}else{let e=oc(n.data)[1];if(e===c-1||(a=rc(n.data),a[e]e*o[(t+1)%2])),u.boxes.push(n),u.classes.push(t),u.scores.push(a[t])}}l.push(u)}return l}function Kd(e,t=null){let n=e.logits,r=n.dims[0];if(t!==null&&t.length!==r)throw Error(`Make sure that you pass in as many target sizes as the batch dimension of the logits`);let i=[];for(let e=0;el[n]&&(l[n]=t[n],u[n]=e)}let d=Array(a.dims[0]);for(let e=0;ee!==void 0);i.push({segmentation:c,labels:f})}return i}function qd(e,t,n,r){let i=[],a=[],o=[];for(let s=0;sn&&(i.push(l),a.push(d),o.push(u))}return[i,a,o]}function Jd(e,t,n,r=.5,i=.8){let a=[],o=0,s=0,c=t[n].data;for(let t=0;t=r&&++s;let l=o>0&&s>0;return l&&=o/s>i,[l,a]}function Yd(e,t,n,r,i,a=null,o=null){let[s,c]=o??e[0].dims,l=new W(`int32`,new Int32Array(s*c),[s,c]),u=[];if(o!==null)for(let t=0;tf[e]&&(d[e]=n,f[e]=i[e])}let p=0,m=l.data;for(let a=0;a200)throw Error(`absolute aspect ratio must be smaller than 200, got ${Math.max(e,t)/Math.min(e,t)}`);let o=Math.round(e/n)*n,s=Math.round(t/n)*n;if(a*o*s>i){let r=Math.sqrt(a*e*t/i);o=Math.max(n,Math.floor(e/r/n)*n),s=Math.max(n,Math.floor(t/r/n)*n)}else if(a*o*si?c=Math.floor(i*s/r):i>r&&(s=Math.floor(r*c/i)),await e.resize(c,s,{resample:n}))}async crop_margin(e,t=200){let n=e.clone().grayscale(),r=ac(n.data)[0],i=oc(n.data)[0]-r;if(i===0)return e;let a=t/255,o=n.width,s=n.height,c=0,l=0,u=n.data;for(let e=0;ethis.preprocess(e)));return{pixel_values:ul(n.map(e=>e.pixel_values),0),original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}static async from_pretrained(e,t={}){let n=await ec(e,Fu,!0,t);return new this(n)}},$d={};Sr($d,{BeitFeatureExtractor:()=>ef,BitImageProcessor:()=>tf,CHMv2ImageProcessor:()=>rf,CLIPFeatureExtractor:()=>of,CLIPImageProcessor:()=>af,ChineseCLIPFeatureExtractor:()=>nf,ConvNextFeatureExtractor:()=>cf,ConvNextImageProcessor:()=>sf,DINOv3ViTImageProcessor:()=>pf,DPTFeatureExtractor:()=>_f,DPTImageProcessor:()=>gf,DeiTFeatureExtractor:()=>uf,DeiTImageProcessor:()=>lf,DetrFeatureExtractor:()=>ff,DetrImageProcessor:()=>df,DonutFeatureExtractor:()=>hf,DonutImageProcessor:()=>mf,EfficientNetImageProcessor:()=>vf,GLPNFeatureExtractor:()=>Tf,Gemma3ImageProcessor:()=>yf,Gemma4ImageProcessor:()=>Sf,Glm46VImageProcessor:()=>wf,GroundingDinoImageProcessor:()=>Ef,Idefics3ImageProcessor:()=>Df,ImageFeatureExtractor:()=>q,ImageProcessor:()=>q,JinaCLIPImageProcessor:()=>kf,Lfm2VlImageProcessor:()=>Ff,LlavaOnevisionImageProcessor:()=>If,Mask2FormerImageProcessor:()=>zf,MaskFormerFeatureExtractor:()=>Rf,MaskFormerImageProcessor:()=>Lf,MobileNetV1FeatureExtractor:()=>Vf,MobileNetV1ImageProcessor:()=>Bf,MobileNetV2FeatureExtractor:()=>Uf,MobileNetV2ImageProcessor:()=>Hf,MobileNetV3FeatureExtractor:()=>Gf,MobileNetV3ImageProcessor:()=>Wf,MobileNetV4FeatureExtractor:()=>qf,MobileNetV4ImageProcessor:()=>Kf,MobileViTFeatureExtractor:()=>Yf,MobileViTImageProcessor:()=>Jf,NougatImageProcessor:()=>Xf,OwlViTFeatureExtractor:()=>Qf,OwlViTImageProcessor:()=>Zf,Owlv2ImageProcessor:()=>$f,Phi3VImageProcessor:()=>ap,PixtralImageProcessor:()=>op,PvtImageProcessor:()=>sp,Qwen2VLImageProcessor:()=>Cf,RTDetrImageProcessor:()=>cp,Sam2ImageProcessor:()=>lp,Sam3ImageProcessor:()=>lp,SamImageProcessor:()=>lp,SapiensFeatureExtractor:()=>dp,SapiensImageProcessor:()=>up,SegformerFeatureExtractor:()=>pp,SegformerImageProcessor:()=>fp,SiglipImageProcessor:()=>mp,SmolVLMImageProcessor:()=>Df,Swin2SRImageProcessor:()=>hp,VLMImageProcessor:()=>Of,ViTFeatureExtractor:()=>_p,ViTImageProcessor:()=>gp,VitMatteImageProcessor:()=>vp,VitPoseImageProcessor:()=>yp,YolosFeatureExtractor:()=>xp,YolosImageProcessor:()=>bp});var ef=class extends q{},tf=class extends q{},nf=class extends q{},rf=class extends q{},af=class extends q{},of=class extends af{},sf=class extends q{constructor(e){super(e),this.crop_pct=this.config.crop_pct??224/256}async resize(e){let t=this.size?.shortest_edge;if(t===void 0)throw Error(`Size dictionary must contain 'shortest_edge' key.`);if(t<384){let n=Math.floor(t/this.crop_pct),[r,i]=this.get_resize_output_image_size(e,{shortest_edge:n});e=await e.resize(r,i,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}},cf=class extends sf{},lf=class extends q{},uf=class extends lf{},df=class extends q{async _call(e){let t=await super._call(e),n=gl([t.pixel_values.dims[0],64,64],1n);return{...t,pixel_mask:n}}post_process_object_detection(...e){return Gd(...e)}post_process_panoptic_segmentation(...e){return Zd(...e)}post_process_instance_segmentation(...e){return Qd(...e)}},ff=class extends df{},pf=class extends q{},mf=class extends q{pad_image(e,t,n,r={}){let[i,a,o]=t,s=this.image_mean;Array.isArray(this.image_mean)||(s=Array(o).fill(s));let c=this.image_std;Array.isArray(c)||(c=Array(o).fill(s));let l=s.map((e,t)=>-e/c[t]);return super.pad_image(e,t,n,{center:!0,constant_values:l,...r})}},hf=class extends mf{},gf=class extends q{},_f=class extends gf{},vf=class extends q{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(e=>e*e))}},yf=class extends q{};function bf(e,t,n,r,i){let a=r*n**2,o=Math.sqrt(a/(e*t)),s=i*n,c=Math.floor(o*e/s)*s,l=Math.floor(o*t/s)*s;if(c===0&&l===0)throw Error(`Attempting to resize to a 0 x 0 image. Resized height should be divisible by \`pooling_kernel_size * patch_size\`=${s}.`);let u=Math.floor(r/i**2)*s;return c===0?(c=s,l=Math.min(Math.floor(t/e)*s,u)):l===0&&(l=s,c=Math.min(Math.floor(e/t)*s,u)),[c,l]}function xf(e,t,n,r,i,a,o){let s=Math.floor(t/i),c=Math.floor(n/i),l=s*c,u=i*i*r,d=new Float32Array(a*u),f=0;for(let t=0;ta),0));let l=a.dims[0]/o,u=a.dims[1],d=Math.floor(a.dims[2]/c),f=Math.floor(a.dims[3]/c);return{pixel_values:a.view(l,o,u,Math.floor(d/s),s,c,Math.floor(f/s),s,c).permute(0,3,6,4,7,2,1,5,8).view(l*d*f,u*o*c*c),image_grid_thw:new W(`int64`,[l,d,f],[1,3]),original_sizes:r,reshaped_input_sizes:i}}},wf=class extends Cf{get_resize_output_image_size(e,t){let n=this.patch_size*this.merge_size,r=this.config.temporal_patch_size??2;return Xd(e.height,e.width,n,this.min_pixels,this.max_pixels,r)}},Tf=class extends q{},Ef=class extends q{async _call(e){let t=await super._call(e),n=t.pixel_values.dims,r=vl([n[0],n[2],n[3]]);return{...t,pixel_mask:r}}},Df=class extends q{constructor(e){super(e),this.do_image_splitting=e.do_image_splitting??!0,this.max_image_size=e.max_image_size}get_resize_for_vision_encoder(e,t){let[n,r]=e.dims.slice(-2),i=r/n;return r>=n?(r=Math.ceil(r/t)*t,n=Math.floor(r/i),n=Math.ceil(n/t)*t):(n=Math.ceil(n/t)*t,r=Math.floor(n*i),r=Math.ceil(r/t)*t),{height:n,width:r}}async _call(e,{do_image_splitting:t=null,return_row_col_info:n=!1}={}){let r;if(!Array.isArray(e))r=[[e]];else{if(e.length===0||!e[0])throw Error(`No images provided.`);r=Array.isArray(e[0])?e:[e]}let i=[],a=[],o=[],s=[],c=[];for(let e of r){let n=await Promise.all(e.map(e=>this.preprocess(e)));s.push(...n.map(e=>e.original_size)),c.push(...n.map(e=>e.reshaped_input_size)),n.forEach(e=>e.pixel_values.unsqueeze_(0));let{longest_edge:r}=this.max_image_size,l;if(t??this.do_image_splitting){let e=Array(n.length),t=Array(n.length);l=await Promise.all(n.map(async(n,i)=>{let a=this.get_resize_for_vision_encoder(n.pixel_values,r),o=await el(n.pixel_values,{size:[a.height,a.width]}),{frames:s,num_splits_h:c,num_splits_w:l}=await this.split_image(o,this.max_image_size);return e[i]=c,t[i]=l,ll(s,0)})),a.push(e),o.push(t)}else{let e=[r,r];l=await Promise.all(n.map(t=>el(t.pixel_values,{size:e}))),a.push(Array(n.length).fill(0)),o.push(Array(n.length).fill(0))}i.push(ll(l,0))}let l=i.length,[u,d,f,p]=i[0].dims,m,h;if(l===1)m=i[0].unsqueeze_(0),h=gl([l,u,f,p],!0);else{let e=Math.max(...i.map(e=>e.dims.at(0)));h=gl([l,e,f,p],!0);let t=h.data,n=e*f*p;for(let r=0;rn||o>r){s=Math.ceil(a/n),c=Math.ceil(o/r);let t=Math.ceil(a/s),l=Math.ceil(o/c);for(let n=0;ne*this.rescale_factor)}pad_image(e,t,n,r){return super.pad_image(e,t,n,{constant_values:this.constant_values,center:!0,...r})}},kf=class extends q{constructor(e){let{resize_mode:t,fill_color:n,interpolation:r,size:i,...a}=e,o=t===`squash`?{width:i,height:i}:t===`shortest`?{shortest_edge:i}:{longest_edge:i},s=r===`bicubic`?3:2;super({...a,size:o,resample:s,do_center_crop:!0,crop_size:i,do_normalize:!0})}};function Af(e,t){return Math.round(e/t)*t}function jf(e,t,n,r,i){let a=1/0,o=[1,1],s=n*r;for(let n of t){let t=Math.abs(e-n[0]/n[1]);t.5*i*i*n[0]*n[1]&&(o=n)}return o}function Mf(e,t){let n=[],r=new Set;for(let i=e;i<=t;++i)for(let a=1;a<=i;++a)for(let o=1;o<=i;++o){let i=a*o;if(i>=e&&i<=t){let e=a<<16|o;r.has(e)||(r.add(e),n.push([a,o]))}}return n.sort((e,t)=>e[0]*e[1]-t[0]*t[1])}function Nf(e,t){let[n,r,i,a]=e.dims,o=Math.floor(i/t),s=Math.floor(a/t),c=t*t*r,l=e.data,u=new Float32Array(n*o*s*c),d=i*a;for(let e=0;ethis.max_image_tokens*(this.encoder_patch_size*this.downsample_factor)**2*this.max_pixels_tolerance}_get_grid_layout(e,t){let n=Mf(this.min_tiles,this.max_tiles),[r,i]=jf(t/e,n,t,e,this.tile_size);return{grid_width:r,grid_height:i,target_width:this.tile_size*r,target_height:this.tile_size*i}}async _call(e,{return_row_col_info:t=null}={}){let n;n=Array.isArray(e)?Array.isArray(e[0])?e:[e]:[[e]];let r=[],i=[],a=[],o=[],s=[],c=[];for(let e of n){let t=await Promise.all(e.map(e=>this.preprocess(e,{do_pad:!1})));for(let{pixel_values:e}of t){let[,t,n]=e.dims,l=e.unsqueeze_(0),u=this.encoder_patch_size*this.downsample_factor,d=u**2,[f,p]=Xd(Math.max(u,t),Math.max(u,n),u,this.min_image_tokens*d,this.max_image_tokens*d).map(e=>Math.max(u,e)),m,h=1,g=1,_=this._is_image_too_large(t,n),v=this.do_image_splitting&&!(this.min_tiles===1&&this.max_tiles===1);if(_&&v){let{grid_width:e,grid_height:r,target_width:i,target_height:a}=this._get_grid_layout(t,n);h=r,g=e;let o=await el(l,{size:[a,i]});m=[];for(let t=0;t(e-this.image_mean[t])/this.image_std[t]);return super.pad_image(e,t,{width:s,height:o},{center:!0,constant_values:c,...r})}async _call(e,{num_crops:t=null}={}){if(this._num_crops=t??=this.config.num_crops,t<4||ip(t)%1!=0)throw Error(`num_crops must be a square number >= 4`);Array.isArray(e)||(e=[e]);let n=e.length,r=await Promise.all(e.map(e=>this.preprocess(e))),i=r.map(e=>e.original_size),a=r.map(e=>e.reshaped_input_size),o=[];for(let{pixel_values:e}of r){e.unsqueeze_(0);let[n,r]=e.dims.slice(-2),i=await el(e,{size:[ep,ep],mode:`bicubic`});if(t>0){let a=[],s=ip(t),c=rp(r/s),l=rp(n/s);for(let t=0;te.map(e=>ep*np(e/ep)));return{pixel_values:s,original_sizes:i,reshaped_input_sizes:a,image_sizes:new W(`int64`,c.flat(),[n,2]),num_img_tokens:c.map(([e,t])=>this.calc_num_image_tokens_from_image_size(t,e))}}},op=class extends q{get_resize_output_image_size(e,t){let{longest_edge:n}=t;if(n===void 0)throw Error(`size must contain 'longest_edge'`);let[r,i]=e.size,a=Math.max(r,i)/n,o=r,s=i;a>1&&(o=Math.floor(r/a),s=Math.floor(i/a));let{patch_size:c,spatial_merge_size:l}=this.config;if(!l)throw Error(`config must contain 'spatial_merge_size'`);let u=c*l,d=Math.floor((o-1)/u)+1,f=Math.floor((s-1)/u)+1;return[d*u,f*u]}},sp=class extends q{},cp=class extends q{post_process_object_detection(...e){return Gd(...e)}},lp=class extends q{reshape_input_points(e,t,n,r=!1){e=structuredClone(e);let i=ii(e);if(i.length===3)r||(i=[1,...i]),e=[e];else if(i.length!==4)throw Error("The input_points must be a 4D tensor of shape `batch_size`, `point_batch_size`, `nb_points_per_image`, `2`.");for(let r=0;re!==t.dims[n]))throw Error(`The first ${n.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new W(`int64`,e.flat(1/0).map(BigInt),n)}async _call(e,{input_points:t=null,input_labels:n=null,input_boxes:r=null}={}){let i=await super._call(e);if(t&&(i.input_points=this.reshape_input_points(t,i.original_sizes,i.reshaped_input_sizes)),n){if(!i.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");i.input_labels=this.add_input_labels(n,i.input_points)}return r&&(i.input_boxes=this.reshape_input_points(r,i.original_sizes,i.reshaped_input_sizes,!0)),i}async post_process_masks(e,t,n,{mask_threshold:r=0,binarize:i=!0,pad_size:a=null}={}){let o=[];a=a??this.pad_size??this.size;let s=[a.height,a.width];for(let a=0;ar&&(t[n]=1);u=new W(`bool`,t,u.dims)}o.push(u)}return o}generate_crop_boxes(e,t,{crop_n_layers:n=0,overlap_ratio:r=512/1500,points_per_crop:i=32,crop_n_points_downscale_factor:a=1}={}){}},up=class extends q{post_process_semantic_segmentation(...e){return Kd(...e)}},dp=class extends up{},fp=class extends q{post_process_semantic_segmentation(...e){return Kd(...e)}},pp=class extends fp{},mp=class extends q{},hp=class extends q{pad_image(e,t,n,r={}){let[i,a,o]=t;return super.pad_image(e,t,{width:a+(n-a%n)%n,height:i+(n-i%n)%n},{mode:`symmetric`,center:!1,constant_values:-1,...r})}},gp=class extends q{},_p=class extends gp{},vp=class extends q{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);let n=await Promise.all(e.map(e=>this.preprocess(e))),r=await Promise.all(t.map(e=>this.preprocess(e,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:ul(n.map((e,t)=>ll([e.pixel_values,r[t].pixel_values],0)),0),original_sizes:n.map(e=>e.original_size),reshaped_input_sizes:n.map(e=>e.reshaped_input_size)}}},yp=class extends q{post_process_pose_estimation(e,t,{threshold:n=null}={}){let r=e.tolist(),[i,a,o,s]=e.dims,c=[];for(let e=0;e/gm,bboxes:/([^<]+)?/gm},this.size_per_bin=1e3}construct_prompts(e){typeof e==`string`&&(e=[e]);let t=[];for(let n of e)if(this.task_prompts_without_inputs.has(n))t.push(this.task_prompts_without_inputs.get(n));else{for(let[e,r]of this.task_prompts_with_input)if(n.includes(e)){t.push(r.replaceAll(`{input}`,n).replaceAll(e,``));break}t.length!==e.length&&t.push(n)}return t}post_process_generation(e,t,n){let r=this.tasks_answer_post_processing_type.get(t)??`pure_text`;e=e.replaceAll(``,``).replaceAll(``,``);let i;switch(r){case`pure_text`:i=e;break;case`description_with_bboxes`:case`bboxes`:case`phrase_grounding`:case`ocr`:let a=r===`ocr`?`quad_boxes`:`bboxes`,o=e.matchAll(this.regexes[a]),s=[],c=[];for(let[e,t,...r]of o)s.push(t?t.trim():s.at(-1)??``),c.push(r.map((e,t)=>(Number(e)+.5)/this.size_per_bin*n[t%2]));i={labels:s,[a]:c};break;default:throw Error(`Task "${t}" (of type "${r}") not yet implemented.`)}return{[t]:i}}async _call(e,t=null,n={}){if(!e&&!t)throw Error(`Either text or images must be provided`);let r=await this.image_processor(e,n),i=t?this.tokenizer(this.construct_prompts(t),n):{};return{...r,...i}}},wp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.image_seq_length=this.config.image_seq_length;let{boi_token:r,image_token:i,eoi_token:a}=this.tokenizer.config;this.boi_token=r,this.image_token=i,this.eoi_token=a,this.full_image_sequence=` + +${r}${i.repeat(this.image_seq_length)}${a} + +`}async _call(e,t=null,n={}){typeof e==`string`&&(e=[e]);let r;return t&&(r=await this.image_processor(t,n),e=e.map(e=>e.replaceAll(this.boi_token,this.full_image_sequence))),{...this.tokenizer(e,n),...r}}},Tp=class extends K{static image_processor_class=Sp;static feature_extractor_class=Ad;static tokenizer_class=Mu;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.audio_seq_length=this.config.audio_seq_length,this.image_seq_length=this.config.image_seq_length;let{audio_token_id:r,boa_token:i,audio_token:a,eoa_token:o,image_token_id:s,boi_token:c,image_token:l,eoi_token:u}=this.tokenizer.config;this.audio_token_id=r,this.boa_token=i,this.audio_token=a,this.full_audio_sequence=` + +${i}${a.repeat(this.audio_seq_length)}${o} + +`,this.image_token_id=s,this.boi_token=c,this.image_token=l,this.full_image_sequence=` + +${c}${l.repeat(this.image_seq_length)}${u} + +`}async _call(e,t=null,n=null,r={}){typeof e==`string`&&(e=[e]);let i;n&&(i=await this.feature_extractor(n,r),e=e.map(e=>e.replaceAll(this.audio_token,this.full_audio_sequence)));let a;return t&&(a=await this.image_processor(t,r),e=e.map(e=>e.replaceAll(this.image_token,this.full_image_sequence))),{...this.tokenizer(e,r),...a,...i}}},Ep=class extends K{static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,n){super(e,t,n),this.audio_ms_per_token=this.config.audio_ms_per_token??40,this.audio_seq_length=this.config.audio_seq_length??750,this.image_seq_length=this.config.image_seq_length??280;let{audio_token:r,boa_token:i,eoa_token:a,image_token:o,boi_token:s,eoi_token:c}=this.tokenizer.config;this.audio_token=r,this.boa_token=i,this.eoa_token=a,this.image_token=o,this.boi_token=s,this.eoi_token=c}static async from_pretrained(e,t={}){let[n,r,i]=await Promise.all([ec(e,Iu,!0,t),Mu.from_pretrained(e,t),$s(e,Lu,!1,t)]),a={tokenizer:r};return n.image_processor&&(a.image_processor=new Sf(n.image_processor)),n.feature_extractor&&(a.feature_extractor=new yd(n.feature_extractor)),new this(n,a,i)}_compute_audio_num_tokens(e,t){let n=Math.round(t*20/1e3),r=Math.round(t*10/1e3),i=Math.floor(n/2),a=Math.floor((e+i-n-1)/r)+1;if(a<=0)return 0;for(let e=0;e<2;++e)a=Math.floor((a-1)/2)+1;return Math.min(a,this.audio_seq_length)}async _call(e,t=null,n=null,r={}){typeof e==`string`&&(e=[e]);let i;if(t){i=await this.image_processor(t,r);let n=i.num_soft_tokens_per_image,a=0;e=e.map(e=>e.replaceAll(this.image_token,()=>` + +${this.boi_token}${this.image_token.repeat(n[a++])}${this.eoi_token} + +`))}let a;if(n){let t=Array.isArray(n)?n:[n];a=await this.feature_extractor(t[0],r);let i=this.feature_extractor.config.sampling_rate??16e3,o=0;e=e.map(e=>e.replaceAll(this.audio_token,()=>` + +${this.boa_token}${this.audio_token.repeat(this._compute_audio_num_tokens(t[o++].length,i))}${this.eoa_token} + +`))}return{...this.tokenizer(e,r),...i,...a}}},Dp=class extends K{static image_processor_class=Sp;static tokenizer_class=Mu;static image_token=`<|image_pad|>`;async _call(e,t=null,...n){Array.isArray(e)||(e=[e]);let r,i;if(t&&(r=await this.image_processor(t),i=r.image_grid_thw),i){let t=this.image_processor.config.merge_size**2,n=0,r=this.constructor.image_token,a=i.tolist();e=e.map(e=>{for(;e.includes(r);){let i=Number(a[n++].reduce((e,t)=>e*t,1n));e=e.replace(r,`<|placeholder|>`.repeat(Math.floor(i/t)))}return e.replaceAll(`<|placeholder|>`,r)})}return{...this.tokenizer(e),...r}}},Op=class extends Dp{static image_token=`<|image|>`},kp=class extends K{static tokenizer_class=Mu;static feature_extractor_class=Ad;static uses_processor_config=!0;_get_num_audio_features(e){let{hop_length:t}=this.feature_extractor.config.melspec_kwargs,{projector_window_size:n,projector_downsample_rate:r}=this.feature_extractor.config,i=Math.floor(n/r),a=Math.floor(e/t)+1,o=Math.floor(a/2);return Math.ceil(o/n)*i}async _call(e,t=null,n={}){if(Array.isArray(e))throw Error(`Batched inputs are not supported yet.`);let r={};if(t){let{input_features:n}=await this.feature_extractor(t);r.input_features=n;let i=this._get_num_audio_features(t.length);r.input_features_mask=new W(`bool`,new Uint8Array(i).fill(1),[1,i]);let a=this.config.audio_token??`<|audio|>`;if(!e.includes(a))throw Error(`The input text does not contain the audio token ${a}.`);e=e.replaceAll(a,a.repeat(i))}return{...this.tokenizer(e,{add_special_tokens:!1,...n}),...r}}};function Ap(e,t){let n=e.dims.at(-1)-1,r=e.tolist();r.fill(!1,0,1),r.fill(!1,n);let i=t.tolist();return r.map((e,t)=>e?t:null).filter(e=>e!==null).map(e=>i[e])}var jp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;async _call(e,t,n={}){let r=e?await this.image_processor(e,n):{};return{...t?this.tokenizer(t,n):{},...r}}post_process_grounded_object_detection(e,t,{box_threshold:n=.25,text_threshold:r=.25,target_sizes:i=null}={}){let{logits:a,pred_boxes:o}=e,s=a.dims[0];if(i!==null&&i.length!==s)throw Error(`Make sure that you pass in as many target sizes as the batch dimension of the logits`);let c=a.dims.at(1),l=a.sigmoid(),u=l.max(-1).tolist(),d=o.tolist().map(e=>e.map(e=>Wd(e))),f=[];for(let e=0;ee.map((e,t)=>e*a[(t+1)%2])));let o=u[e],s=[],p=[],m=[];for(let i=0;i`+i.repeat(e);o+=` +`}return o+=` +${r}${a}`+i.repeat(e)+`${r}`,o}function Np(e,t,n,r){return`${t}${r}`+n.repeat(e)+`${t}`}function Pp(e,t,n,r,i,a){return e===0&&t===0?Np(n,r,i,a):Mp(n,e,t,r,i,a)}var Fp=class extends K{static image_processor_class=Sp;static tokenizer_class=Mu;static uses_processor_config=!0;fake_image_token=``;image_token=``;global_img_token=``;async _call(e,t=null,n={}){n.return_row_col_info??=!0;let r;t&&(r=await this.image_processor(t,n)),Array.isArray(e)||(e=[e]);let i=r.rows??[Array(e.length).fill(0)],a=r.cols??[Array(e.length).fill(0)],o=this.config.image_seq_len,s=[],c=[];for(let t=0;tPp(e,l[t],o,this.fake_image_token,this.image_token,this.global_img_token)),d=n.split(this.image_token);if(d.length===0)throw Error(`The image token should be present in the text.`);let f=d[0];for(let e=0;ee.images).flatMap(e=>e.images).map(e=>Bd.read(e)));let r=this.tokenizer,i=r.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0,chat_template:n}),a=e=>r.encode(e,{add_special_tokens:!1}),o=i.split(this.image_tag),s=o.length-1;if(t.length!==s)throw Error(`Number of images provided (${t.length}) does not match number of "${this.image_tag}" image tags (${s})`);let[c,l,u]=r.convert_tokens_to_ids([this.image_tag,this.image_start_tag,this.image_end_tag]),d=a(o[0]),f=Array(d.length).fill(!1);for(let e=1;e0){let e=await this.image_processor(t);return e.pixel_values.unsqueeze_(0),{...m,...e}}return m}},Lp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;async _call(e=null,t=null,n={}){if(!e&&!t)throw Error(`Either text or images must be provided`);let r=e?this.tokenizer(e,n):{},i=t?await this.image_processor(t,n):{};return{...r,...i}}},Rp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;async _call(e,t=null,n={}){let{image_rows:r,image_cols:i,image_sizes:a,...o}=await this.image_processor(e,{...n,return_row_col_info:!0});if(t){let e=this.config.image_token??``,{tile_size:n=512,downsample_factor:o=2,encoder_patch_size:s=16,use_thumbnail:c=!0}=this.image_processor.config,l=e=>Math.ceil(Math.floor(e/s)/o),u=l(n)**2,d=this.config.image_start_token??`<|image_start|>`,f=this.config.image_end_token??`<|image_end|>`,p=this.config.image_thumbnail??`<|img_thumbnail|>`;Array.isArray(t)||(t=[t]);let m=0;t=t.map(t=>{let n=t.split(e);return n[0]+n.slice(1).map(t=>{let n=m++,[o,s]=a[n],h=r[n],g=i[n],_=l(o)*l(s),v=d;if(h>1||g>1){let t=e.repeat(u);for(let e=0;e`+t;c&&(v+=p+e.repeat(_))}else v+=e.repeat(_);return v+f+t}).join(``)})}return{...o,...t?this.tokenizer(t,n):{}}}},zp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;static uses_processor_config=!0;async _call(e,t=null,n={}){let r=await this.image_processor(e,n);if(t){let[e,n]=r.pixel_values.dims.slice(-2),{image_token:i,patch_size:a,num_additional_image_tokens:o}=this.config,s=Math.floor(e/a)*Math.floor(n/a)+o;t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let e=0;e0?i.reduce((e,t)=>e*t,1):0;c.push(n),s.push(a)}return[i(c),s]}char_decode(e){return this.char_tokenizer.batch_decode(e).map(e=>e.replaceAll(` `,``))}bpe_decode(e){return this.bpe_tokenizer.batch_decode(e)}wp_decode(e){return this.wp_tokenizer.batch_decode(e).map(e=>e.replaceAll(` `,``))}batch_decode([e,t,n]){let[r,i]=this._decode_helper(e,`char`),[a,o]=this._decode_helper(t,`bpe`),[s,c]=this._decode_helper(n,`wp`),l=[],u=[];for(let e=0;e`;function Gp(e,t,n,r,i){return`${r.repeat(n*i)}${t}${e} +`}var Kp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;static uses_processor_config=!1;async _call(e,t=null,n={}){t||=(P.warn(`You are using PaliGemma without a text prefix. It will perform as a picture-captioning model.`),``),Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);let r=this.tokenizer.bos_token,i=this.image_processor.config.image_seq_length,a;t.some(e=>e.includes(Wp))?a=t.map(e=>{let t=e.replaceAll(Wp,Wp.repeat(i)),n=t.lastIndexOf(Wp),a=n===-1?0:n+Wp.length;return t.slice(0,a)+r+t.slice(a)+` +`}):(P.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 `` tokens in the very beginning of your text. For this call, we will infer how many images each text has and add special tokens."),a=t.map(t=>Gp(t,r,i,Wp,e.length)));let o=this.tokenizer(a,n);return{...await this.image_processor(e,n),...o}}},qp=`<|image|>`,Jp=/<\|image_\d+\|>/g,Yp=class extends K{static image_processor_class=Sp;static tokenizer_class=Mu;async _call(e,t=null,{padding:n=!0,truncation:r=!0,num_crops:i=null}={}){Array.isArray(e)||(e=[e]);let a,o;if(t){o=await this.image_processor(t,{num_crops:i});let{num_img_tokens:s}=o,c=e.map((e,t)=>e.split(Jp).join(qp.repeat(s[t])));a=this.tokenizer(c,{padding:n,truncation:r});let l=this.tokenizer._tokenizer.token_to_id(qp);a.input_ids.map_(e=>e==l?-e:e)}else a=this.tokenizer(e);return{...a,...o}}},Xp=class extends K{static tokenizer_class=Mu;static image_processor_class=Sp;static uses_processor_config=!0;async _call(e,t=null,n={}){let r=await this.image_processor(e,n);if(t){let[e,n]=r.pixel_values.dims.slice(-2),{image_token:i,image_break_token:a,image_end_token:o,patch_size:s,spatial_merge_size:c}=this.config,l=s*c,u=Math.floor(e/l),d=Math.floor(n/l);t=structuredClone(t),Array.isArray(t)||(t=[t]);for(let e=0;ecm(e,o)),c=s.map(e=>e.length),l=s.flat(),u=(await Promise.all(l.map(e=>this.feature_extractor(e,n)))).map(e=>e.input_features);r.audio_values=u.length>1?ll(u,0):u[0];let d=i[0];for(let e=0;e0){if(l>Ts)throw Error(`The number of external data chunks (${l}) exceeds the maximum allowed value (${Ts}).`);let t=Dm(o,l);for(let n of t){let t=`${r.subfolder??``}/${n}`;c.push(new Promise(async(i,a)=>{let o=await Qs(e,t,!0,r,s);i(o instanceof Uint8Array?{path:n,data:o}:n)}))}}else a.externalData!==void 0&&(c=a.externalData.map(async t=>{if(typeof t.data==`string`){let n=await Qs(e,t.data,!0,r);return{...t,data:n}}return t}));return Promise.all(c)}async function Am(e,t,n,r=!1,i=void 0){let a=n.config?.[`transformers.js_config`]??{},o=Uc(n.device??a.device,t,{warn:e=>P.info(e)}),s=kc(o),c=a.device_config??{};c.hasOwnProperty(o)&&(a={...a,...c[o]});let l=Yc(n.dtype??a.dtype,t,o,{configDtype:a.dtype,warn:e=>P.info(e)});if(!Jc.hasOwnProperty(l))throw Error(`Invalid dtype: ${l}. 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When 'free_dimension_overrides' is not set, you may experience significant performance degradation.`);let h=Om(e,t,n,f),g=await km(e,t,f,n,n.use_external_data_format??a.use_external_data_format,p);if(g.length>0&&(!M.IS_NODE_ENV||g.some(e=>typeof e!=`string`))&&(p.externalData=g),r&&o===`webgpu`&&u!==!1){let e=Sm(n.config,{prefix:`present`,session_name:i});if(Object.keys(e).length>0&&!Rc()){let t={};for(let n in e)t[n]=`gpu-buffer`;p.preferredOutputLocation=t}}return{buffer_or_path:await h,session_options:p,session_config:{dtype:l,kv_cache_dtype:d,device:o}}}async function jm(e,t,n,r=void 0){return Object.fromEntries(await Promise.all(Object.keys(t).map(async i=>{let a=r?.[i]??!1,{buffer_or_path:o,session_options:s,session_config:c}=await Am(e,t[i],n,a,i);return[i,await Nc(o,s,c)]})))}function Mm(e){for(let t in e)Ic(e[t])?e[t]=new W(e[t]):typeof e[t]==`object`&&Mm(e[t]);return e}async function J(e,t){let n=Nm(e,t);try{return Mm(await Fc(e,Object.fromEntries(Object.entries(n).map(([e,t])=>{let n=t.ort_tensor;return M.IS_NODE_ENV&&typeof Float16Array<`u`&&n.cpuData instanceof Float16Array&&(n.cpuData=new Uint16Array(n.cpuData.buffer)),[e,n]}))))}catch(e){let t=Object.fromEntries(Object.entries(n).map(([e,t])=>{let n={type:t.type,dims:t.dims,location:t.location};return n.location!==`gpu-buffer`&&(n.data=t.data),[e,n]}));throw P.error(`An error occurred during model execution: "${e}".`),P.error(`Inputs given to model:`,t),e}}function Nm(e,t){let n=Object.create(null),r=[];for(let i of e.inputNames){let e=t[i];if(!(e instanceof W)){r.push(i);continue}n[i]=Rc()?e.clone():e}if(r.length>0)throw Error(`An error occurred during model execution: "Missing the following inputs: ${r.join(`, `)}.`);let i=Object.keys(t).length,a=e.inputNames.length;if(i>a){let n=Object.keys(t).filter(t=>!e.inputNames.includes(t));P.warn(`WARNING: Too many inputs were provided (${i} > ${a}). 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Please report this at ${Nu}.`)}if(t&&!(t instanceof ti)){let r={};try{let t=await gh(e,{config:n,dtype:l,device:c,model_file_name:o});(await Promise.all(t.map(t=>Us(e,t,f)))).forEach((e,n)=>{if(e.exists){let i=t[n]===`config.json`;r[t[n]]={loaded:i?e.size??0:0,total:e.size??0}}})}catch(e){P.warn(`Unable to fetch model file metadata for total progress tracking: ${e}`)}Object.keys(r).length>0&&(f.progress_callback=new ti(t,r))}let _=[jm(e,m.sessions(n,f,h),f,m.cache_sessions)];m.optional_configs&&_.push(Vh(e,m.optional_configs,f));let v=await Promise.all(_);return new this(n,...v)}async _call(e){return await this.forward(e)}async forward(e){return await this._forward(this,e)}get generation_config(){return this.configs?.generation_config??null}_get_logits_processor(e,t,n=null){let r=new Hm;if(e.repetition_penalty!==null&&e.repetition_penalty!==1&&r.push(new Ym(e.repetition_penalty)),e.no_repeat_ngram_size!==null&&e.no_repeat_ngram_size>0&&r.push(new Jm(e.no_repeat_ngram_size)),e.bad_words_ids!==null&&r.push(new Qm(e.bad_words_ids,e.eos_token_id)),e.min_length!==null&&e.eos_token_id!==null&&e.min_length>0&&r.push(new Xm(e.min_length,e.eos_token_id)),e.min_new_tokens!==null&&e.eos_token_id!==null&&e.min_new_tokens>0&&r.push(new Zm(t,e.min_new_tokens,e.eos_token_id)),e.forced_bos_token_id!==null&&r.push(new Um(e.forced_bos_token_id)),e.forced_eos_token_id!==null&&r.push(new Wm(e.max_length,e.forced_eos_token_id)),e.suppress_tokens!==null&&r.push(new Gm(e.suppress_tokens)),e.begin_suppress_tokens!==null){let n=t>1||e.forced_bos_token_id===null?t:t+1;r.push(new Km(e.begin_suppress_tokens,n))}return e.guidance_scale!==null&&e.guidance_scale>1&&r.push(new $m(e.guidance_scale)),e.temperature===0&&e.do_sample&&(P.warn("`do_sample` changed to false because `temperature: 0` implies greedy sampling (always selecting the most likely token), which is incompatible with `do_sample: true`."),e.do_sample=!1),e.do_sample&&e.temperature!==null&&e.temperature!==1&&r.push(new eh(e.temperature)),n!==null&&r.extend(n),r}_prepare_generation_config(e,t,n=th){let r={...this.config};for(let e of[`decoder`,`generator`,`text_config`])e in r&&Object.assign(r,r[e]);let i=new n(r);return Object.assign(i,this.generation_config??{}),e&&Object.assign(i,e),t&&Object.assign(i,ci(t,Object.getOwnPropertyNames(i))),i}_get_stopping_criteria(e,t=null){let n=new rh;return e.max_length!==null&&n.push(new ih(e.max_length,this.config.max_position_embeddings??null)),e.eos_token_id!==null&&n.push(new ah(e.eos_token_id)),t&&n.extend(t),n}_validate_model_class(){if(!this.can_generate){let e=[_h.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,_h.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,_h.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,_h.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES].filter(Boolean),t=Th.get(this.constructor),n=new Set,r=this.config.model_type;for(let t of e){let e=t?.get(r);e&&n.add(e)}let i=`The current model class (${t}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw n.size>0&&(i+=` Please use the following class instead: ${[...n].join(`, `)}`),Error(i)}}prepare_inputs_for_generation(...e){if(!this._prepare_inputs_for_generation)throw Error(`prepare_inputs_for_generation is not implemented for this model.`);return this._prepare_inputs_for_generation(this,...e)}_update_model_kwargs_for_generation({generated_input_ids:e,outputs:t,model_inputs:n,is_encoder_decoder:r}){return n.past_key_values=this.getPastKeyValues(t,n.past_key_values),n.input_ids=new W(`int64`,e.flat(),[e.length,1]),r?`decoder_attention_mask`in n&&(n.decoder_attention_mask=ll([n.decoder_attention_mask,vl([n.decoder_attention_mask.dims[0],1])],1)):n.attention_mask=ll([n.attention_mask,vl([n.attention_mask.dims[0],1])],1),n.position_ids=null,n}_prepare_model_inputs({inputs:e,bos_token_id:t,model_kwargs:n}){let r=ci(n,this.forward_params),i=this.main_input_name;if(i in r){if(e)throw Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else r[i]=e;return{inputs_tensor:r[i],model_inputs:r,model_input_name:i}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:e,model_inputs:t,model_input_name:n,generation_config:r}){if(this.sessions.model.inputNames.includes(`inputs_embeds`)&&!t.inputs_embeds&&`_prepare_inputs_embeds`in this){let{input_ids:e,pixel_values:n,attention_mask:r,...i}=t,a=await this._prepare_inputs_embeds(t);t={...i,...ci(a,[`inputs_embeds`,`attention_mask`])}}let{last_hidden_state:i}=await Dh(this,t);if(r.guidance_scale!==null&&r.guidance_scale>1)i=ll([i,_l(i,0)],0),`attention_mask`in t&&(t.attention_mask=ll([t.attention_mask,xl(t.attention_mask)],0));else if(t.decoder_input_ids){let e=yh(t.decoder_input_ids).dims[0];if(e!==i.dims[0]){if(i.dims[0]!==1)throw Error(`The encoder outputs have a different batch size (${i.dims[0]}) than the decoder inputs (${e}).`);i=ll(Array.from({length:e},()=>i),0)}}return t.encoder_outputs=i,t}_prepare_decoder_input_ids_for_generation({batch_size:e,model_input_name:t,model_kwargs:n,decoder_start_token_id:r,bos_token_id:i,generation_config:a}){let{decoder_input_ids:o,...s}=n;if(!(o instanceof W)){if(o)Array.isArray(o[0])||(o=Array.from({length:e},()=>o));else if(r??=i,this.config.model_type===`musicgen`)o=Array.from({length:e*this.config.decoder.num_codebooks},()=>[r]);else if(Array.isArray(r)){if(r.length!==e)throw Error(`\`decoder_start_token_id\` expcted to have length ${e} but got ${r.length}`);o=r}else o=Array.from({length:e},()=>[r]);o=yh(o)}return s.decoder_attention_mask=yl(o),{input_ids:o,model_inputs:s}}async generate({inputs:e=null,generation_config:t=null,logits_processor:n=null,stopping_criteria:r=null,streamer:i=null,...a}){this._validate_model_class(),t=this._prepare_generation_config(t,a);let{inputs_tensor:o,model_inputs:s,model_input_name:c}=this._prepare_model_inputs({inputs:e,model_kwargs:a}),l=this.config.is_encoder_decoder;l&&(`encoder_outputs`in s||(s=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:o,model_inputs:s,model_input_name:c,generation_config:t})));let u;l?{input_ids:u,model_inputs:s}=this._prepare_decoder_input_ids_for_generation({batch_size:s[c].dims.at(0),model_input_name:c,model_kwargs:s,decoder_start_token_id:t.decoder_start_token_id,bos_token_id:t.bos_token_id,generation_config:t}):u=s[c];let d=u.dims.at(-1);t.max_new_tokens!==null&&(t.max_length=d+t.max_new_tokens);let f=this._get_logits_processor(t,d,n),p=this._get_stopping_criteria(t,r),m=s[c].dims.at(0),h=sh.getSampler(t),g=Array(m).fill(0),_=u.tolist();i&&i.put(_);let v,y={},b={};for(;;){if(s=this.prepare_inputs_for_generation(_,s,t),v=await this.forward(s),t.return_dict_in_generate)if(t.output_attentions){let e=this.getAttentions(v);for(let t in e)t in y||(y[t]=[]),y[t].push(e[t])}else this._return_dict_in_generate_keys&&Object.assign(b,ci(v,this._return_dict_in_generate_keys));let e=f(_,v.logits.slice(null,-1,null).to(`float32`)),n=[];for(let t=0;te))break;s=this._update_model_kwargs_for_generation({generated_input_ids:n,outputs:v,model_inputs:s,is_encoder_decoder:l})}i&&i.end();let x=this.getPastKeyValues(v,s.past_key_values,!0),ee=new W(`int64`,_.flat(),[_.length,_[0].length]);if(t.return_dict_in_generate)return{sequences:ee,past_key_values:x,...y,...b};for(let e of Object.values(v))e.location===`gpu-buffer`&&e.dispose();return ee}getPastKeyValues(e,t,n=!1){let r=Object.create(null);for(let i in e)if(i.startsWith(`present`)){let a=i.replace(`present_ssm`,`past_ssm`).replace(`present_conv`,`past_conv`).replace(`present_recurrent`,`past_recurrent`).replace(`present`,`past_key_values`),o=i.includes(`encoder`);if(o&&t?r[a]=t[a]:r[a]=e[i],t&&(!o||n)){let e=t[a];e.location===`gpu-buffer`&&e.dispose()}}return new dh(r)}getAttentions(e){let t={};for(let n of[`cross_attentions`,`encoder_attentions`,`decoder_attentions`])for(let r in e)r.startsWith(n)&&(n in t||(t[n]=[]),t[n].push(e[r]));return t}addPastKeyValues(e,t){if(t)Object.assign(e,t);else{let t=this.sessions.decoder_model_merged??this.sessions.model,n=(e[this.main_input_name]??e.attention_mask)?.dims?.[0]??1,r=t?.config?.kv_cache_dtype??`float32`,i=r===`float16`?Xc.float16:Xc.float32,a=Sm(this.config,{batch_size:n});for(let t in a)e[t]=new W(r,new i(a[t].reduce((e,t)=>e*t,1)),a[t])}}async _encode_input(e,t,n){if(!Object.hasOwn(this.sessions,e))throw Error(`Model does not have a ${e} session.`);let r=this.sessions[e];return(await J(r,ci(t,r.inputNames)))[n]}async encode_image(e){return this._encode_input(`vision_encoder`,e,`image_features`)}async encode_text(e){return this._encode_input(`embed_tokens`,e,`inputs_embeds`)}async encode_audio(e){return this._encode_input(`audio_encoder`,e,`audio_features`)}};async function Eh(e,t){let{encoder_outputs:n,input_ids:r,decoder_input_ids:i,decoder_attention_mask:a,...o}=t;return n||=(await Dh(e,ci(t,e.sessions.model.inputNames))).last_hidden_state,o.input_ids=i,o.encoder_hidden_states=n,e.sessions.decoder_model_merged.inputNames.includes(`encoder_attention_mask`)&&(o.encoder_attention_mask=t.attention_mask),a&&!o.attention_mask&&(o.attention_mask=a),await kh(e,o,!0)}async function Dh(e,t){let n=e.sessions.model,r=ci(t,n.inputNames);if(n.inputNames.includes(`inputs_embeds`)&&!r.inputs_embeds){if(!t.input_ids)throw Error("Both `input_ids` and `inputs_embeds` are missing in the model inputs.");r.inputs_embeds=await e.encode_text({input_ids:t.input_ids})}if(n.inputNames.includes(`token_type_ids`)&&!r.token_type_ids){if(!r.input_ids)throw Error("Both `input_ids` and `token_type_ids` are missing in the model inputs.");r.token_type_ids=xl(r.input_ids)}if(n.inputNames.includes(`pixel_mask`)&&!r.pixel_mask){if(!r.pixel_values)throw Error("Both `pixel_values` and `pixel_mask` are missing in the model inputs.");let e=r.pixel_values.dims;r.pixel_mask=vl([e[0],e[2],e[3]])}return await J(n,r)}async function Oh(e,t){let n=await e.encode(t);return await e.decode(n)}async function kh(e,t,n=!1){let r=e.sessions[n?`decoder_model_merged`:`model`],{past_key_values:i,...a}=t;return r.inputNames.includes(`use_cache_branch`)&&(a.use_cache_branch=bh(!!i)),r.inputNames.includes(`position_ids`)&&a.attention_mask&&!a.position_ids&&(a.position_ids=Ph(a,i,[`paligemma`,`gemma3_text`,`gemma3`].includes(e.config.model_type)?1:0)),r.inputNames.includes(`num_logits_to_keep`)&&!a.num_logits_to_keep&&(a.num_logits_to_keep=new W(`int64`,[0n],[])),e.addPastKeyValues(a,i),await J(r,ci(a,r.inputNames))}async function Ah(e,{encode_function:t,merge_function:n,modality_input_names:r,modality_output_name:i,input_ids:a=null,attention_mask:o=null,position_ids:s=null,inputs_embeds:c=null,past_key_values:l=null,generation_config:u=null,logits_processor:d=null,...f}){if(!c){c=await e.encode_text({input_ids:a,...f});let s=ci(f,r);if(Object.keys(s).length>0){if(a.dims[1]!==1){let e=await t({...s,...f});({inputs_embeds:c,attention_mask:o}=n({[i]:e,inputs_embeds:c,input_ids:a,attention_mask:o}))}else if(l&&a.dims[1]===1){let e=a.dims[1],t=l.get_seq_length();o=ll([vl([a.dims[0],t]),o.slice(null,[o.dims[1]-e,o.dims[1]])],1)}}}if(!s&&[`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)){let{image_grid_thw:t,video_grid_thw:n}=f;[s]=e.get_rope_index(a,t,n,o)}return await kh(e,{inputs_embeds:c,past_key_values:l,attention_mask:o,position_ids:s,generation_config:u,logits_processor:d},!0)}async function jh(e,t){return await Ah(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 Mh(e,t){return await 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await Dh(this,{pixel_values:e})}async forward(e){let{num_feature_levels:t}=this.config.vision_config;if(e=Array.from({length:t},(e,t)=>`image_embeddings.${t}`).some(t=>!e[t])?{...e,...await this.get_image_embeddings(e)}:{...e},e.input_points){if(e.input_boxes&&e.input_boxes.dims[1]!==1)throw Error("When both `input_points` and `input_boxes` are provided, the number of boxes per image must be 1.");let t=e.input_points.dims;e.input_labels??=vl(t.slice(0,-1)),e.input_boxes??=gl([t[0],0,4],0)}else if(e.input_boxes){let t=e.input_boxes.dims;e.input_labels=gl([t[0],t[1],0],-1n),e.input_points=gl([t[0],1,0,2],0)}else throw Error("At least one of `input_points` or `input_boxes` must be provided.");let n=this.sessions.prompt_encoder_mask_decoder;return await J(n,ci(e,n.inputNames))}async _call(e){return new aT(await super._call(e))}},cT=class extends sT{},lT=class extends sT{},uT=class extends Z{},dT=class extends uT{},fT=class extends uT{},pT=class extends uT{},mT=class extends Z{},hT=class extends mT{},gT=class extends mT{},_T=class extends mT{},vT=class extends Z{},yT=class extends vT{},bT=class extends vT{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`text_model`})}},xT=class extends Kg{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`vision_model`})}},ST=class extends Z{},CT=class extends ST{},wT=class extends ST{},TT=class extends Z{main_input_name=`input_values`;forward_params=[`input_values`]},ET=class extends TT{async encode(e){return await J(this.sessions.encoder_model,e)}async decode(e){return await J(this.sessions.decoder_model,e)}},DT=class extends TT{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`encoder_model`})}},OT=class extends TT{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??`decoder_model`})}},kT=class extends Z{},AT=class extends kT{},jT=class extends kT{},MT=class extends Z{},NT=class extends MT{},PT=class extends MT{},FT=class extends MT{async generate_speech(e,t,{threshold:n=.5,minlenratio:r=0,maxlenratio:i=20,vocoder:a=null}={}){let{encoder_outputs:o,encoder_attention_mask:s}=await Dh(this,{input_ids:e}),c=o.dims[1]/this.config.reduction_factor,l=Math.floor(c*i),u=Math.floor(c*r),d=this.config.num_mel_bins,f=[],p=null,m=null,h=0;for(;;){++h;let e=bh(!!m),r;r=m?m.output_sequence_out:new W(`float32`,new Float32Array(d),[1,1,d]);let i={use_cache_branch:e,output_sequence:r,encoder_attention_mask:s,speaker_embeddings:t,encoder_hidden_states:o};this.addPastKeyValues(i,p),m=await J(this.sessions.decoder_model_merged,i),p=this.getPastKeyValues(m,p);let{prob:a,spectrum:c}=m;if(f.push(c),h>=u&&(Array.from(a.data).filter(e=>e>=n).length>0||h>=l))break}let g=ll(f),{waveform:_}=await J(a.sessions.model,{spectrogram:g});return{spectrogram:g,waveform:_}}},IT=class extends Z{main_input_name=`spectrogram`},LT=class extends Z{},RT=class extends LT{},zT=class extends LT{async _call(e){return new Im(await super._call(e))}},BT=class extends LT{async _call(e){return new Y(await super._call(e))}},VT=class extends LT{async _call(e){return new Lm(await super._call(e))}},HT=class extends Z{},UT=class extends HT{},WT=class extends HT{},GT=class extends Z{},KT=class extends GT{},qT=class extends GT{},JT=class extends Z{},YT=class extends JT{},XT=class extends Z{},ZT=class extends XT{async generate_speech({input_ids:e,attention_mask:t,style:n,num_inference_steps:r=5,speed:i=1.05}){let{sampling_rate:a,chunk_compress_factor:o,base_chunk_size:s,latent_dim:c}=this.config,{last_hidden_state:l,durations:u}=await J(this.sessions.text_encoder,{input_ids:e,attention_mask:t,style:n}),d=u.div(i).mul_(a),f=s*o,p=d.data,m=Int32Array.from(p,e=>Math.ceil(e/f)),h=Math.max(...m),g=e.dims[0],_=new BigInt64Array(g*h);for(let e=0;ee*t,1)),d[e]);let f=new W(l,new u(s*UE),[1,s,UE]),p=t[Symbol.asyncIterator]?.()??t[Symbol.iterator]?.();if(!p)throw Error(`input_features must be iterable or async iterable`);return{encoder_session:i,enc_kv_cache:c,enc_padding_cache:f,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:p,text_hidden_size:n.hidden_size}}async function qE(e,t){let n=t.dims[2],r=Math.floor((WE+n-3)/2)+1,i=new W(`int64`,BigInt64Array.from({length:r},(t,n)=>BigInt(e.enc_past_seq_len+n)),[1,r]),a=e.enc_past_seq_len+r,o=vl([1,a]),{audio_embeds:s,present_padding_cache:c,...l}=await J(e.encoder_session,{input_features:t,attention_mask:o,position_ids:i,past_padding_cache:e.enc_padding_cache,...e.enc_kv_cache});e.enc_padding_cache.location===`gpu-buffer`&&e.enc_padding_cache.dispose(),e.enc_padding_cache=c;for(let t in l)if(t.startsWith(`present.`)){let n=t.replace(`present`,`past_key_values`),r=e.enc_kv_cache[n];r?.location===`gpu-buffer`&&r.dispose(),e.enc_kv_cache[n]=l[t]}return e.enc_past_seq_len=a,s}async function JE(e,t){for(;e.audio_embed_total_tokens0&&e.audio_embed_queue.length>0;){let t=e.audio_embed_queue[0],n=t.tokens-e.audio_queue_offset,o=Math.min(a,n),s=e.audio_queue_offset*e.text_hidden_size;for(let n=0;n=t.tokens&&(e.audio_embed_queue.shift(),e.audio_queue_offset=0)}e.audio_consumed+=n-a}var XE=class extends nh{constructor(e){super(),this._s=e}_call(e){let t=this._s.stream_exhausted&&this._s.audio_embed_queue.length===0;return e.map(()=>t)}},ZE=class extends Z{forward_params=[`input_ids`,`attention_mask`,`position_ids`,`past_key_values`]},QE=class extends ZE{async forward({input_ids:e,past_key_values:t,...n}){let r=e.dims[1],i=GE.get(this);i&&await JE(i,i.audio_consumed+r);let{inputs_embeds:a}=await J(this.sessions.embed_tokens,{input_ids:e});i&&YE(i,a,r);let o={inputs_embeds:a,...n};this.addPastKeyValues(o,t);let s=this.sessions.decoder_model_merged;return await J(s,ci(o,s.inputNames))}async generate({input_features:e,stopping_criteria:t,...n}){if(!e)throw Error(`input_features (generator/iterable) must be provided`);let r=KE(this,e);GE.set(this,r);let i=new rh;i.push(new XE(r)),t&&i.extend(t);try{return await super.generate({...n,stopping_criteria:i})}finally{r.enc_kv_cache.dispose(),GE.delete(this)}}},$E=class extends Z{},eD=class extends $E{},tD=class extends $E{async _call(e){return new Rm(await super._call(e))}},nD=class extends $E{async _call(e){return new Y(await super._call(e))}},rD=class extends Pm{constructor({logits:e,embeddings:t}){super(),this.logits=e,this.embeddings=t}},iD=class extends Z{},aD=class extends iD{},oD=class extends iD{async _call(e){return new Rm(await super._call(e))}},sD=class extends iD{async _call(e){return new Y(await super._call(e))}},cD=class extends iD{async _call(e){return new rD(await super._call(e))}},lD=class extends iD{async _call(e){return new Fm(await super._call(e))}},uD=class extends Z{},dD=class extends uD{},fD=class extends th{return_timestamps=null;return_token_timestamps=null;num_frames=null;alignment_heads=null;task=null;language=null;no_timestamps_token_id=null;prompt_ids=null;is_multilingual=null;lang_to_id=null;task_to_id=null;max_initial_timestamp_index=1},pD=class extends Z{requires_attention_mask=!1;main_input_name=`input_features`;forward_params=[`input_features`,`attention_mask`,`decoder_input_ids`,`decoder_attention_mask`,`past_key_values`]},mD=class extends pD{},hD=class extends pD{_prepare_generation_config(e,t){return super._prepare_generation_config(e,t,fD)}_retrieve_init_tokens(e){let t=[e.decoder_start_token_id],n=e.language,r=e.task;if(e.is_multilingual){n||=(P.warn(`No language specified - defaulting to English (en).`),`en`);let i=`<|${Eu(n)}|>`;t.push(e.lang_to_id[i]),t.push(e.task_to_id[r??`transcribe`])}else if(n||r)throw Error("Cannot specify `task` or `language` for an English-only model. If the model is intended to be multilingual, pass `is_multilingual=true` to generate, or update the generation config.");return!e.return_timestamps&&e.no_timestamps_token_id&&t.at(-1)!==e.no_timestamps_token_id?t.push(e.no_timestamps_token_id):e.return_timestamps&&t.at(-1)===e.no_timestamps_token_id&&(P.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),t.pop()),t.filter(e=>e!=null)}async generate({inputs:e=null,generation_config:t=null,logits_processor:n=null,stopping_criteria:r=null,...i}){t=this._prepare_generation_config(t,i);let a=i.decoder_input_ids??this._retrieve_init_tokens(t);if(t.return_timestamps&&(n??=new Hm,n.push(new qm(t,a))),t.begin_suppress_tokens&&(n??=new Hm,n.push(new Km(t.begin_suppress_tokens,a.length))),t.return_token_timestamps){if(!t.alignment_heads)throw Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");t.task===`translate`&&P.warn(`Token-level timestamps may not be reliable for task 'translate'.`),t.output_attentions=!0,t.return_dict_in_generate=!0}if(t.return_timestamps&&!i.max_new_tokens)return this._generate_with_seek({inputs:e,generation_config:t,logits_processor:n,init_tokens:a,kwargs:i});let o=await super.generate({inputs:e,generation_config:t,logits_processor:n,decoder_input_ids:a,...i});return t.return_token_timestamps&&(o.token_timestamps=this._extract_token_timestamps(o,t.alignment_heads,t.num_frames,.02,a.length)),o}async _generate_with_seek({inputs:e,generation_config:t,logits_processor:n,init_tokens:r,kwargs:i}){let a=t.no_timestamps_token_id+1,o=Array.isArray(t.eos_token_id)?t.eos_token_id[0]:t.eos_token_id,s=t.return_token_timestamps,c=e,l=c.dims[2],u=2*this.config.max_source_positions,d=0,f=[],p=[];for(;de+n)}if(v.length>0&&v.at(-1)===o&&v.pop(),v.length===0)break;let b=v.map(e=>e>=a),x=v.length>=2&&b[v.length-1]&&!b[v.length-2],ee=[];for(let e=0;e0)if(x)S=e-d;else{let e=ee.at(-1);S=(v[e-1]-a)*2,te=e}else S=e-d;let C=Math.floor(d/2),w=a+1500;for(let e=0;e=a&&(v[e]=Math.min(v[e]+C,w));f.push(...v.slice(0,te)),y&&p.push(...y.slice(0,te)),d+=S}f.push(o);let m=[...r,...f];if(s){let e=new W(`int64`,m.map(BigInt),[1,m.length]),t=[...Array(r.length).fill(0),...p,0];return{sequences:e,token_timestamps:new W(`float32`,new Float32Array(t),[1,t.length])}}return new W(`int64`,m.map(BigInt),[1,m.length])}_extract_token_timestamps(e,t,n=null,r=.02,i=0){if(!e.cross_attentions)throw Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");n??P.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&&(P.warn("Model config has no `median_filter_width`, using default value of 7."),a=7);let o=e.cross_attentions,s=Array.from({length:this.config.decoder_layers},(e,t)=>ll(o.map(e=>e[t]),2)),c=ul(t.map(([e,t])=>{if(e>=s.length)throw Error(`Layer index ${e} is out of bounds for cross attentions (length ${s.length}).`);return n?s[e].slice(null,t,null,[0,n]):s[e].slice(null,t)})).transpose(1,0,2,3),[l,u]=fl(c,-2,0,!0),d=c.clone();for(let e=0;e0?d.slice(null,null,[i,d.dims[2]],null):d,1)],p=e.sequences.dims,m=new W(`float32`,new Float32Array(p[0]*p[1]),p);for(let e=0;et[n+1]-t[n])).map(e=>!!e),o=[];for(let e=0;e0&&s.push(o.at(-1)),m[e].data.set(s)}return m}},gD=class extends hD{},_D=class extends Z{},vD=class extends _D{},yD=class extends _D{async _call(e){return new Im(await super._call(e))}},bD=class extends _D{async _call(e){return new Y(await super._call(e))}},xD=class extends _D{async _call(e){return new Fm(await super._call(e))}},SD=class extends _D{async _call(e){return new Lm(await super._call(e))}},CD=class extends Z{},wD=class extends CD{},TD=class extends CD{async _call(e){return new Im(await super._call(e))}},ED=class extends CD{async _call(e){return new Y(await super._call(e))}},DD=class extends CD{async _call(e){return new Fm(await super._call(e))}},OD=class extends CD{async _call(e){return new Lm(await super._call(e))}},kD=class extends Z{},AD=class extends kD{},jD=class extends kD{async _call(e){return new MD(await super._call(e))}},MD=class extends Pm{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},ND=class extends Z{},PD=class extends ND{},FD=class extends ND{},ID=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`]]),LD=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`]]),RD=new Map([[`mimi`,`MimiModel`],[`dac`,`DacModel`],[`snac`,`SnacModel`]]),zD=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`]]),BD=new Map([[`speecht5`,`SpeechT5ForSpeechToText`],[`whisper`,`WhisperForConditionalGeneration`],[`lite-whisper`,`LiteWhisperForConditionalGeneration`],[`moonshine`,`MoonshineForConditionalGeneration`],[`cohere_asr`,`CohereAsrForConditionalGeneration`]]),VD=new Map([[`speecht5`,`SpeechT5ForTextToSpeech`]]),HD=new Map([[`vits`,`VitsModel`],[`musicgen`,`MusicgenForConditionalGeneration`],[`supertonic`,`SupertonicForConditionalGeneration`]]),UD=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`]]),WD=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`]]),GD=new Map([[`t5`,`T5ForConditionalGeneration`],[`longt5`,`LongT5ForConditionalGeneration`],[`mt5`,`MT5ForConditionalGeneration`],[`bart`,`BartForConditionalGeneration`],[`mbart`,`MBartForConditionalGeneration`],[`marian`,`MarianMTModel`],[`m2m_100`,`M2M100ForConditionalGeneration`],[`blenderbot`,`BlenderbotForConditionalGeneration`],[`blenderbot-small`,`BlenderbotSmallForConditionalGeneration`]]),KD=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`]]),qD=new Map([[`multi_modality`,`MultiModalityCausalLM`]]),JD=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`]]),YD=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`]]),XD=new Map([[`vision-encoder-decoder`,`VisionEncoderDecoderModel`],[`idefics3`,`Idefics3ForConditionalGeneration`],[`smolvlm`,`SmolVLMForConditionalGeneration`]]),ZD=new Map([[`llava`,`LlavaForConditionalGeneration`],[`llava_onevision`,`LlavaOnevisionForConditionalGeneration`],[`moondream1`,`Moondream1ForConditionalGeneration`],[`florence2`,`Florence2ForConditionalGeneration`],[`qwen2_vl`,`Qwen2VLForConditionalGeneration`],[`qwen2_5_vl`,`Qwen2_5_VLForConditionalGeneration`],[`qwen3_vl`,`Qwen3VLForConditionalGeneration`],[`qwen3_vl_moe`,`Qwen3VLMoeForConditionalGeneration`],[`qwen3_5`,`Qwen3_5ForConditionalGeneration`],[`qwen3_5_moe`,`Qwen3_5MoeForConditionalGeneration`],[`lfm2_vl`,`Lfm2VlForConditionalGeneration`],[`idefics3`,`Idefics3ForConditionalGeneration`],[`smolvlm`,`SmolVLMForConditionalGeneration`],[`paligemma`,`PaliGemmaForConditionalGeneration`],[`llava_qwen2`,`LlavaQwen2ForCausalLM`],[`gemma3`,`Gemma3ForConditionalGeneration`],[`gemma3n`,`Gemma3nForConditionalGeneration`],[`gemma4`,`Gemma4ForConditionalGeneration`],[`mistral3`,`Mistral3ForConditionalGeneration`],[`lighton_ocr`,`LightOnOcrForConditionalGeneration`],[`glm_ocr`,`GlmOcrForConditionalGeneration`]]),QD=new Map([[`granite_speech`,`GraniteSpeechForConditionalGeneration`],[`ultravox`,`UltravoxModel`],[`voxtral`,`VoxtralForConditionalGeneration`],[`voxtral_realtime`,`VoxtralRealtimeForConditionalGeneration`]]),$D=new Map([[`vision-encoder-decoder`,`VisionEncoderDecoderModel`]]),eO=new Map([[`vit`,`ViTForImageClassification`],[`ijepa`,`IJepaForImageClassification`],[`pvt`,`PvtForImageClassification`],[`vit_msn`,`ViTMSNForImageClassification`],[`fastvit`,`FastViTForImageClassification`],[`mobilevit`,`MobileViTForImageClassification`],[`mobilevitv2`,`MobileViTV2ForImageClassification`],[`beit`,`BeitForImageClassification`],[`deit`,`DeiTForImageClassification`],[`hiera`,`HieraForImageClassification`],[`convnext`,`ConvNextForImageClassification`],[`convnextv2`,`ConvNextV2ForImageClassification`],[`dinov2`,`Dinov2ForImageClassification`],[`dinov2_with_registers`,`Dinov2WithRegistersForImageClassification`],[`resnet`,`ResNetForImageClassification`],[`swin`,`SwinForImageClassification`],[`segformer`,`SegformerForImageClassification`],[`efficientnet`,`EfficientNetForImageClassification`],[`mobilenet_v1`,`MobileNetV1ForImageClassification`],[`mobilenet_v2`,`MobileNetV2ForImageClassification`],[`mobilenet_v3`,`MobileNetV3ForImageClassification`],[`mobilenet_v4`,`MobileNetV4ForImageClassification`]]),tO=new Map([[`detr`,`DetrForObjectDetection`],[`rt_detr`,`RTDetrForObjectDetection`],[`rt_detr_v2`,`RTDetrV2ForObjectDetection`],[`rf_detr`,`RFDetrForObjectDetection`],[`d_fine`,`DFineForObjectDetection`],[`table-transformer`,`TableTransformerForObjectDetection`],[`yolos`,`YolosForObjectDetection`]]),nO=new Map([[`owlvit`,`OwlViTForObjectDetection`],[`owlv2`,`Owlv2ForObjectDetection`],[`grounding-dino`,`GroundingDinoForObjectDetection`]]),rO=new Map([[`detr`,`DetrForSegmentation`],[`clipseg`,`CLIPSegForImageSegmentation`]]),iO=new Map([[`segformer`,`SegformerForSemanticSegmentation`],[`sapiens`,`SapiensForSemanticSegmentation`],[`swin`,`SwinForSemanticSegmentation`],[`mobilenet_v1`,`MobileNetV1ForSemanticSegmentation`],[`mobilenet_v2`,`MobileNetV2ForSemanticSegmentation`],[`mobilenet_v3`,`MobileNetV3ForSemanticSegmentation`],[`mobilenet_v4`,`MobileNetV4ForSemanticSegmentation`]]),aO=new Map([[`detr`,`DetrForSegmentation`],[`maskformer`,`MaskFormerForInstanceSegmentation`]]),oO=new Map([[`sam`,`SamModel`],[`sam2`,`Sam2Model`],[`edgetam`,`EdgeTamModel`],[`sam3_tracker`,`Sam3TrackerModel`]]),sO=new Map([[`wav2vec2`,`Wav2Vec2ForCTC`],[`wav2vec2-bert`,`Wav2Vec2BertForCTC`],[`unispeech`,`UniSpeechForCTC`],[`unispeech-sat`,`UniSpeechSatForCTC`],[`wavlm`,`WavLMForCTC`],[`hubert`,`HubertForCTC`],[`parakeet_ctc`,`ParakeetForCTC`]]),cO=new Map([[`wav2vec2`,`Wav2Vec2ForSequenceClassification`],[`wav2vec2-bert`,`Wav2Vec2BertForSequenceClassification`],[`unispeech`,`UniSpeechForSequenceClassification`],[`unispeech-sat`,`UniSpeechSatForSequenceClassification`],[`wavlm`,`WavLMForSequenceClassification`],[`hubert`,`HubertForSequenceClassification`],[`audio-spectrogram-transformer`,`ASTForAudioClassification`]]),lO=new Map([[`wavlm`,`WavLMForXVector`]]),uO=new Map([[`unispeech-sat`,`UniSpeechSatForAudioFrameClassification`],[`wavlm`,`WavLMForAudioFrameClassification`],[`wav2vec2`,`Wav2Vec2ForAudioFrameClassification`],[`pyannote`,`PyAnnoteForAudioFrameClassification`]]),dO=new Map([[`vitmatte`,`VitMatteForImageMatting`]]),fO=new Map([[`patchtst`,`PatchTSTForPrediction`],[`patchtsmixer`,`PatchTSMixerForPrediction`]]),pO=new Map([[`swin2sr`,`Swin2SRForImageSuperResolution`]]),mO=new Map([[`chmv2`,`CHMv2ForDepthEstimation`],[`dpt`,`DPTForDepthEstimation`],[`depth_anything`,`DepthAnythingForDepthEstimation`],[`glpn`,`GLPNForDepthEstimation`],[`sapiens`,`SapiensForDepthEstimation`],[`depth_pro`,`DepthProForDepthEstimation`],[`metric3d`,`Metric3DForDepthEstimation`],[`metric3dv2`,`Metric3Dv2ForDepthEstimation`]]),hO=new Map([[`sapiens`,`SapiensForNormalEstimation`]]),gO=new Map([[`vitpose`,`VitPoseForPoseEstimation`]]),_O=new Map([[`clip`,`CLIPVisionModelWithProjection`],[`siglip`,`SiglipVisionModel`],[`jina_clip`,`JinaCLIPVisionModel`]]),vO=[[ID,X.EncoderOnly],[LD,X.EncoderDecoder],[zD,X.DecoderOnlyWithoutHead],[RD,X.AutoEncoder],[UD,X.EncoderOnly],[WD,X.EncoderOnly],[GD,X.Seq2Seq],[BD,X.Seq2Seq],[KD,X.DecoderOnly],[qD,X.MultiModality],[JD,X.EncoderOnly],[YD,X.EncoderOnly],[XD,X.Vision2Seq],[ZD,X.ImageTextToText],[QD,X.AudioTextToText],[eO,X.EncoderOnly],[rO,X.EncoderOnly],[aO,X.EncoderOnly],[iO,X.EncoderOnly],[dO,X.EncoderOnly],[fO,X.EncoderOnly],[pO,X.EncoderOnly],[mO,X.EncoderOnly],[hO,X.EncoderOnly],[gO,X.EncoderOnly],[tO,X.EncoderOnly],[nO,X.EncoderOnly],[oO,X.MaskGeneration],[sO,X.EncoderOnly],[cO,X.EncoderOnly],[VD,X.Seq2Seq],[HD,X.EncoderOnly],[lO,X.EncoderOnly],[uO,X.EncoderOnly],[_O,X.EncoderOnly]];for(let[e,t]of vO)for(let n of e.values()){Ch.set(n,t);let e=Hh[n];Th.set(e,n),wh.set(n,e)}var yO=[[`MusicgenForConditionalGeneration`,nC,X.Musicgen],[`Phi3VForCausalLM`,rw,X.Phi3V],[`CLIPTextModelWithProjection`,Yg,X.EncoderOnly],[`SiglipTextModel`,bT,X.EncoderOnly],[`JinaCLIPTextModel`,tx,X.EncoderOnly],[`ClapTextModelWithProjection`,Wg,X.EncoderOnly],[`ClapAudioModelWithProjection`,Gg,X.EncoderOnly],[`DacEncoderModel`,I_,X.EncoderOnly],[`DacDecoderModel`,L_,X.EncoderOnly],[`MimiEncoderModel`,Wx,X.EncoderOnly],[`MimiDecoderModel`,Gx,X.EncoderOnly],[`SnacEncoderModel`,DT,X.EncoderOnly],[`SnacDecoderModel`,OT,X.EncoderOnly],[`Gemma3nForConditionalGeneration`,My,X.ImageAudioTextToText],[`Gemma4ForConditionalGeneration`,Py,X.ImageAudioTextToText],[`SupertonicForConditionalGeneration`,ZT,X.Supertonic],[`ChatterboxModel`,Lg,X.Chatterbox],[`VoxtralRealtimeForConditionalGeneration`,QE,X.VoxtralRealtime]];for(let[e,t,n]of yO)Ch.set(e,n),Th.set(t,e),wh.set(e,t);var bO=new Map([[`modnet`,rO],[`birefnet`,rO],[`isnet`,rO],[`ben`,rO]]);for(let[e,t]of bO.entries())t.set(e,`PreTrainedModel`),Ch.set(e,X.EncoderOnly),wh.set(e,Z);var xO=new Set(bO.keys());Ch.set(`PreTrainedModel`,X.EncoderOnly),Th.set(Z,`PreTrainedModel`);var Q={MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES:UD,MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES:WD,MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES:VD,MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES:HD,MODEL_FOR_MASKED_LM_MAPPING_NAMES:JD,MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES:YD,MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES:eO,MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES:rO,MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES:iO,MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES:aO,MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES:tO,MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES:nO,MODEL_FOR_MASK_GENERATION_MAPPING_NAMES:oO,MODEL_FOR_CTC_MAPPING_NAMES:sO,MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES:cO,MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES:lO,MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES:uO,MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES:$D,MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES:dO,MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES:pO,MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES:mO,MODEL_FOR_NORMAL_ESTIMATION_MAPPING_NAMES:hO,MODEL_FOR_POSE_ESTIMATION_MAPPING_NAMES:gO,MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES:_O,MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES:ZD,MODEL_FOR_AUDIO_TEXT_TO_TEXT_MAPPING_NAMES:QD,MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES:GD,MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES:BD,MODEL_FOR_CAUSAL_LM_MAPPING_NAMES:KD,MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES:XD};vh(Q);var $=class{static MODEL_CLASS_MAPPINGS=null;static BASE_IF_FAIL=!1;static supports(e){if(!this.MODEL_CLASS_MAPPINGS)return!1;for(let t of this.MODEL_CLASS_MAPPINGS)if(t.has(e))return!0;return this.BASE_IF_FAIL}static async from_pretrained(e,{progress_callback:t=null,config:n=null,cache_dir:r=null,local_files_only:i=!1,revision:a=`main`,model_file_name:o=null,subfolder:s=`onnx`,device:c=null,dtype:l=null,use_external_data_format:u=null,session_options:d={}}={}){let f={progress_callback:t,config:n,cache_dir:r,local_files_only:i,revision:a,model_file_name:o,subfolder:s,device:c,dtype:l,use_external_data_format:u,session_options:d};if(f.config=await Tm.from_pretrained(e,f),!this.MODEL_CLASS_MAPPINGS)throw Error("`MODEL_CLASS_MAPPINGS` not implemented for this type of `AutoClass`: "+this.name);let{model_type:p}=f.config;for(let t of this.MODEL_CLASS_MAPPINGS){let n=t.get(p);if(!n){for(let e of t.values())if(e[0]===p){n=e;break}if(!n)continue}return await Hh[n].from_pretrained(e,f)}if(this.BASE_IF_FAIL)return xO.has(p)||P.warn(`Unknown model class "${p}", attempting to construct from base class.`),await Z.from_pretrained(e,f);throw Error(`Unsupported model type: ${p}`)}},SO=class extends ${static MODEL_CLASS_MAPPINGS=vO.map(e=>e[0]);static BASE_IF_FAIL=!0},CO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]},wO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]},TO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]},EO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]},DO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]},OO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES]},kO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES]},AO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_MASKED_LM_MAPPING_NAMES]},jO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]},MO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]},NO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]},PO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]},FO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES]},IO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES]},LO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]},RO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_MASK_GENERATION_MAPPING_NAMES]});var zO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_CTC_MAPPING_NAMES]},BO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES]};var VO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES]});var HO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES]},UO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_NORMAL_ESTIMATION_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_POSE_ESTIMATION_MAPPING_NAMES]};var WO=class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES]};(class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES]}),class extends ${static MODEL_CLASS_MAPPINGS=[Q.MODEL_FOR_AUDIO_TEXT_TO_TEXT_MAPPING_NAMES]};async function GO(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>Bd.read(e)))}async function KO(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(e=>typeof e==`string`||e instanceof URL?Wu(e,t):e instanceof Float64Array?new Float32Array(e):e))}function qO(e,t){t&&(e=e.map(e=>e|0));let[n,r,i,a]=e;return{xmin:n,ymin:r,xmax:i,ymax:a}}var JO=class extends $r{constructor({task:e,model:t,tokenizer:n=null,processor:r=null}){super(),this.task=e,this.model=t,this.tokenizer=n,this.processor=r}async dispose(){await this.model.dispose()}},YO=class extends JO{async _call(e,{top_k:t=1}={}){let n=this.tokenizer(e,{padding:!0,truncation:!0}),r=await this.model(n),{problem_type:i,id2label:a}=this.model.config,o=i===`multi_label_classification`?e=>e.sigmoid():e=>new W(`float32`,rc(e.data),e.dims),s=[];for(let e of r.logits){let n=await nl(o(e),t),r=n[0].tolist(),i=n[1].tolist().map((e,t)=>({label:a?a[e]:`LABEL_${e}`,score:r[t]}));t===1?s.push(...i):s.push(i)}return Array.isArray(e)||t===1?s:s[0]}},XO=class extends JO{async _call(e,{ignore_labels:t=[`O`]}={}){let n=Array.isArray(e),r=this.tokenizer(n?e:[e],{padding:!0,truncation:!0}),i=(await this.model(r)).logits,a=this.model.config.id2label,o=[];for(let e=0;ee==u),i=a[e].tolist(),f=o[e].tolist();for(let n=1;ne==t[n])!==-1)&&(i[n]=-1/0,f[n]=-1/0);let p=rc(i).map((e,t)=>[e,t]),m=rc(f).map((e,t)=>[e,t]);p[0][0]=0,m[0][0]=0;let h=oi(p,m).filter(e=>e[0][1]<=e[1][1]).map(e=>[e[0][1],e[1][1],e[0][0]*e[1][0]]).sort((e,t)=>t[2]-e[2]),g=[];for(let e=0;ee==n);if(c===-1)throw Error(`Mask token (${r}) not found in text.`);let l=a[e][c],u=await nl(new W(`float32`,rc(l.data),l.dims),t),d=u[0].tolist(),f=u[1].tolist();o.push(f.map((e,t)=>{let n=i.slice();return n[c]=e,{score:d[t],token:Number(e),token_str:this.tokenizer.decode([e]),sequence:this.tokenizer.decode(n,{skip_special_tokens:!0})}}))}return Array.isArray(e)?o:o[0]}},$O=class extends JO{_key=`generated_text`;async _call(e,t={}){Array.isArray(e)||(e=[e]),this.model.config.prefix&&(e=e.map(e=>this.model.config.prefix+e));let n=this.model.config.task_specific_params;n&&n[this.task]&&n[this.task].prefix&&(e=e.map(e=>n[this.task].prefix+e));let r=this.tokenizer,i={padding:!0,truncation:!0},a;a=this.task===`translation`&&`_build_translation_inputs`in r?r._build_translation_inputs(e,i,t):r(e,i);let o=await this.model.generate({...a,...t});return r.batch_decode(o,{skip_special_tokens:!0}).map(e=>({[this._key]:e}))}},ek=class extends $O{_key=`summary_text`},tk=class extends $O{_key=`translation_text`};function nk(e){return Array.isArray(e)&&e.every(e=>`role`in e&&`content`in e)}var rk=class extends JO{async _call(e,t={}){let n=!1,r=!1,i=t.add_special_tokens??(this.tokenizer.add_bos_token||this.tokenizer.add_eos_token)??!1,a=t.tokenizer_encode_kwargs,o;if(typeof e==`string`)o=e=[e];else if(Array.isArray(e)&&e.every(e=>typeof e==`string`))n=!0,o=e;else{if(nk(e))e=[e];else if(Array.isArray(e)&&e.every(nk))n=!0;else throw Error(`Input must be a string, an array of strings, a Chat, or an array of Chats`);r=!0,o=e.map(e=>this.tokenizer.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0,...a})),i=!1,a=void 0}let s=r?!1:t.return_full_text??!0;this.tokenizer.padding_side=`left`;let c=this.tokenizer(o,{add_special_tokens:i,padding:!0,truncation:!0,...a}),l=await this.model.generate({...c,...t}),u=this.tokenizer.batch_decode(l,{skip_special_tokens:!0}),d;!s&&c.input_ids.dims.at(-1)>0&&(d=this.tokenizer.batch_decode(c.input_ids,{skip_special_tokens:!0}).map(e=>e.length));let f=Array.from({length:e.length},e=>[]);for(let t=0;t[e.toLowerCase(),t])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(P.warn(`Could not find 'entailment' in label2id mapping. Using 2 as entailment_id.`),this.entailment_id=2),this.contradiction_id=this.label2id.contradiction??this.label2id.not_entailment,this.contradiction_id===void 0&&(P.warn(`Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id.`),this.contradiction_id=0)}async _call(e,t,{hypothesis_template:n=`This example is {}.`,multi_label:r=!1}={}){let i=Array.isArray(e);i||(e=[e]),Array.isArray(t)||(t=[t]);let a=t.map(e=>n.replace(`{}`,e)),o=r||t.length===1,s=[];for(let n of e){let e=[];for(let t of a){let r=this.tokenizer(n,{text_pair:t,padding:!0,truncation:!0}),i=await this.model(r);o?e.push([i.logits.data[this.contradiction_id],i.logits.data[this.entailment_id]]):e.push(i.logits.data[this.entailment_id])}let r=(o?e.map(e=>rc(e)[1]):rc(e)).map((e,t)=>[e,t]).sort((e,t)=>t[0]-e[0]);s.push({sequence:n,labels:r.map(e=>t[e[1]]),scores:r.map(e=>e[0])})}return i?s:s[0]}},ak=class extends JO{async _call(e,{top_k:t=5}={}){let n=this.processor.feature_extractor.config.sampling_rate,r=await KO(e,n),i=this.model.config.id2label,a=[];for(let e of r){let n=await this.processor(e),r=(await this.model(n)).logits[0],o=await nl(new W(`float32`,rc(r.data),r.dims),t),s=o[0].tolist(),c=o[1].tolist().map((e,t)=>({label:i?i[e]:`LABEL_${e}`,score:s[t]}));a.push(c)}return Array.isArray(e)?a:a[0]}},ok=class extends JO{async _call(e,t,{hypothesis_template:n=`This is a sound of {}.`}={}){let r=!Array.isArray(e);r&&(e=[e]);let i=t.map(e=>n.replace(`{}`,e)),a=this.tokenizer(i,{padding:!0,truncation:!0}),o=this.processor.feature_extractor.config.sampling_rate,s=await KO(e,o),c=[];for(let e of s){let n=await this.processor(e),r=rc((await this.model({...a,...n})).logits_per_audio.data);c.push([...r].map((e,n)=>({score:e,label:t[n]})))}return r?c[0]:c}},sk=class extends JO{async _call(e,t={}){switch(this.model.config.model_type){case`whisper`:case`lite-whisper`:return this._call_whisper(e,t);case`wav2vec2`:case`wav2vec2-bert`:case`unispeech`:case`unispeech-sat`:case`hubert`:case`parakeet_ctc`:return this._call_wav2vec2(e,t);case`moonshine`:return this._call_moonshine(e,t);case`cohere_asr`:return this._call_cohere_asr(e,t);default:throw Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(e,t){t.language&&P.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),t.task&&P.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor.config.sampling_rate,a=await KO(r,i),o=[];for(let e of a){let t=await this.processor(e),n=(await this.model(t)).logits[0],r=[];for(let e of n)r.push(oc(e.data)[1]);let i=this.tokenizer.decode(r,{skip_special_tokens:!0}).trim();o.push({text:i})}return n?o[0]:o}async _call_whisper(e,t){let n=t.return_timestamps??!1,r=t.chunk_length_s??0,i=t.force_full_sequences??!1,a=t.stride_length_s??null,o={...t};n===`word`&&(o.return_token_timestamps=!0,o.return_timestamps=!0);let s=!Array.isArray(e),c=s?[e]:e,l=this.processor.feature_extractor.config,u=l.chunk_length/this.model.config.max_source_positions,d=l.hop_length,f=l.sampling_rate,p=await KO(c,f),m=[];for(let e of p){let t=[];if(r>0){if(a===null)a=r/6;else if(r<=a)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");let n=f*r,i=f*a,o=n-2*i,s=0;for(;;){let r=s+n,a=e.subarray(s,r),c=await this.processor(a),l=s===0,u=r>=e.length;if(t.push({stride:[a.length,l?0:i,u?0:i],input_features:c.input_features,is_last:u}),u)break;s+=o}}else t=[{stride:[e.length,0,0],input_features:(await this.processor(e)).input_features,is_last:!0}];for(let e of t){o.num_frames=Math.floor(e.stride[0]/d);let t=await this.model.generate({inputs:e.input_features,...o});if(n===`word`){let n=t.sequences.tolist()[0],r=t.token_timestamps.tolist()[0],i=this.tokenizer.timestamp_begin,a=Math.max(n.findIndex(e=>Number(e)>=i),0);e.tokens=n.slice(a),e.token_timestamps=r.slice(a).map(e=>fc(e,2))}else e.tokens=t[0].tolist();e.stride=e.stride.map(e=>e/f)}let[s,c]=this.tokenizer._decode_asr(t,{time_precision:u,return_timestamps:n,force_full_sequences:i});m.push({text:s,...c})}return s?m[0]:m}async _call_moonshine(e,t){let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor.config.sampling_rate,a=await KO(r,i),o=[];for(let e of a){let n=await this.processor(e),r=Math.floor(e.length/i)*6,a=await this.model.generate({max_new_tokens:r,...t,...n}),s=this.processor.batch_decode(a,{skip_special_tokens:!0})[0];o.push({text:s})}return n?o[0]:o}async _call_cohere_asr(e,t){let n=!Array.isArray(e),r=n?[e]:e,i=this.processor.feature_extractor,a=i.config.sampling_rate,o=await KO(r,a),s=t.language??`en`,c=this.processor.get_decoder_prompt_ids(s),l=[];for(let e of o){let n=i.split_audio(e),r=[];for(let e of n){let n=await this.processor(e),i=await this.model.generate({...n,decoder_input_ids:c,...t}),a=this.tokenizer.decode(i[0].tolist(),{skip_special_tokens:!0}).trim();r.push(a)}let a=this.processor.constructor.join_chunks(r,s);l.push({text:a})}return n?l[0]:l}},ck=class extends JO{DEFAULT_VOCODER_ID=`Xenova/speecht5_hifigan`;constructor(e){super(e),this.vocoder=e.vocoder??null}async _prepare_speaker_embeddings(e,t){if((typeof e==`string`||e instanceof URL)&&(e=new Float32Array(await(await N.fetch(e)).arrayBuffer())),e instanceof Float32Array)e=new W(`float32`,e,[e.length]);else if(!(e instanceof W))throw Error("Speaker embeddings must be a `Tensor`, `Float32Array`, `string`, or `URL`.");if(t>1){if(e.dims[0]===1)e=e.repeat(t,1);else if(e.dims[0]!==t)throw Error(`Expected speaker embeddings batch size to be 1 or ${t}, but got ${e.dims[0]}.`)}return e}_postprocess_waveform(e,t,n,r=null){let i=t.data,[a,o]=t.dims,s=r?r.data:null,c=[];for(let e=0;e({generated_text:e.trim()}));a.push(r)}return n?a:a[0]}},uk=class extends JO{async _call(e,{top_k:t=5}={}){let n=await GO(e),{pixel_values:r}=await this.processor(n),i=await this.model({pixel_values:r}),{id2label:a}=this.model.config,o=[];for(let e of i.logits){let n=await nl(new W(`float32`,rc(e.data),e.dims),t),r=n[0].tolist(),i=n[1].tolist().map((e,t)=>({label:a?a[e]:`LABEL_${e}`,score:r[t]}));o.push(i)}return Array.isArray(e)?o:o[0]}},dk={panoptic:`post_process_panoptic_segmentation`,instance:`post_process_instance_segmentation`,semantic:`post_process_semantic_segmentation`},fk=class extends JO{async _call(e,{threshold:t=.5,mask_threshold:n=.5,overlap_mask_area_threshold:r=.8,label_ids_to_fuse:i=null,target_sizes:a=null,subtask:o=null}={}){if(Array.isArray(e)&&e.length!==1)throw Error(`Image segmentation pipeline currently only supports a batch size of 1.`);let s=await GO(e),c=s.map(e=>[e.height,e.width]),l=await this.processor(s),{inputNames:u,outputNames:d}=this.model.sessions.model;if(!u.includes(`pixel_values`)){if(u.length!==1)throw Error(`Expected a single input name, but got ${u.length} inputs: ${u}.`);let e=u[0];if(e in l)throw Error(`Input name ${e} already exists in the inputs.`);l[e]=l.pixel_values}let f=await this.model(l),p=null;if(o!==null)p=dk[o];else if(this.processor.image_processor){for(let[e,t]of Object.entries(dk))if(t in this.processor.image_processor){p=this.processor.image_processor[t].bind(this.processor.image_processor),o=e;break}}let m=this.model.config.id2label,h=[];if(!o){let e=1e-5,t=f[d[0]];for(let n=0;nt<-e||t>1+e)&&i.sigmoid_();let a=await Bd.fromTensor(i.mul_(255).to(`uint8`)).resize(r[1],r[0]);h.push({label:null,score:null,mask:a})}}else if(o===`panoptic`||o===`instance`){let e=p(f,t,n,r,i,a??c)[0],o=e.segmentation;for(let t of e.segments_info){let e=new Uint8ClampedArray(o.data.length);for(let n=0;n{let n=e.clone();return n.putAlpha(r[t].mask),n});return Array.isArray(e)?i:i[0]}},mk=class extends JO{async _call(e,t,{hypothesis_template:n=`This is a photo of {}`}={}){let r=Array.isArray(e),i=await GO(e),a=t.map(e=>n.replace(`{}`,e)),o=this.tokenizer(a,{padding:this.model.config.model_type===`siglip`?`max_length`:!0,truncation:!0}),{pixel_values:s}=await this.processor(i),c=await this.model({...o,pixel_values:s}),l=this.model.config.model_type===`siglip`?e=>e.sigmoid().data:e=>rc(e.data),u=[];for(let e of c.logits_per_image){let n=[...l(e)].map((e,n)=>({score:e,label:t[n]}));n.sort((e,t)=>t.score-e.score),u.push(n)}return r?u:u[0]}},hk=class extends JO{async _call(e,{threshold:t=.9,percentage:n=!1}={}){let r=Array.isArray(e);if(r&&e.length!==1)throw Error(`Object detection pipeline currently only supports a batch size of 1.`);let i=await GO(e),a=n?null:i.map(e=>[e.height,e.width]),{pixel_values:o,pixel_mask:s}=await this.processor(i),c=await this.model({pixel_values:o,pixel_mask:s}),l=this.processor.image_processor.post_process_object_detection(c,t,a),{id2label:u}=this.model.config,d=l.map(e=>e.boxes.map((t,r)=>({score:e.scores[r],label:u[e.classes[r]],box:qO(t,!n)})));return r?d:d[0]}},gk=class extends JO{async _call(e,t,{threshold:n=.1,top_k:r=null,percentage:i=!1}={}){let a=Array.isArray(e),o=await GO(e),s=this.tokenizer(t,{padding:!0,truncation:!0}),c=await this.processor(o),l=[];for(let e=0;e({score:e.scores[n],label:e.labels[n],box:qO(t,!i)}))}else{let e=this.processor.image_processor.post_process_object_detection(f,n,u,!0)[0];p=e.boxes.map((n,r)=>({score:e.scores[r],label:t[e.classes[r]],box:qO(n,!i)}))}p.sort((e,t)=>t.score-e.score),r!==null&&(p=p.slice(0,r)),l.push(p)}return a?l:l[0]}},_k=class extends JO{async _call(e,t,n={}){if(Array.isArray(e)){if(e.length!==1)throw Error(`Document Question Answering pipeline currently only supports a batch size of 1.`);e=e[0]}let r=(await GO(e))[0],{pixel_values:i}=await this.processor(r),a=`${t}`,o=this.tokenizer(a,{add_special_tokens:!1,padding:!0,truncation:!0}).input_ids,s=await this.model.generate({inputs:i,max_length:this.model.config.decoder.max_position_embeddings,decoder_input_ids:o,...n}),c=this.tokenizer.batch_decode(s)[0].match(/(.*?)<\/s_answer>/),l=null;return c&&c.length>=2&&(l=c[1].trim()),[{answer:l}]}},vk=class extends JO{async _call(e){let t=await GO(e),n=await this.processor(t),r=await this.model(n),i=[];for(let e of r.reconstruction){let t=e.squeeze().clamp_(0,1).mul_(255).round_().to(`uint8`);i.push(Bd.fromTensor(t))}return Array.isArray(e)?i:i[0]}},yk=class extends JO{async _call(e){let t=await GO(e),n=await this.processor(t),{predicted_depth:r}=await this.model(n),i=[];for(let e=0;ee>=19968&&e<=40959||e>=13312&&e<=19903||e>=131072&&e<=173791||e>=173824&&e<=177983||e>=177984&&e<=178207||e>=178208&&e<=183983||e>=63744&&e<=64255||e>=194560&&e<=195103,Ck=class{put(e){throw Error(`Not implemented`)}end(){throw Error(`Not implemented`)}},wk=M.IS_PROCESS_AVAILABLE?e=>process.stdout.write(e):e=>console.log(e),Tk=class extends Ck{constructor(e,{skip_prompt:t=!1,callback_function:n=null,token_callback_function:r=null,skip_special_tokens:i=!0,decode_kwargs:a={},...o}={}){super(),this.tokenizer=e,this.skip_prompt=t,this.callback_function=n??wk,this.token_callback_function=r,this.decode_kwargs={skip_special_tokens:i,...a,...o},this.token_cache=[],this.print_len=0,this.next_tokens_are_prompt=!0,this.special_ids=new Set(this.tokenizer.all_special_ids.map(BigInt))}put(e){if(e.length>1)throw Error(`TextStreamer only supports batch size of 1`);let t=this.next_tokens_are_prompt;if(t&&(this.next_tokens_are_prompt=!1,this.skip_prompt))return;let n=e[0];if(this.token_callback_function?.(n),n.length===1&&this.special_ids.has(n[0])){if(this.decode_kwargs.skip_special_tokens)return;if(this.token_cache.length>0){let e=this.tokenizer.decode(this.token_cache,this.decode_kwargs).slice(this.print_len);this.on_finalized_text(e,!1),this.token_cache=[],this.print_len=0}let e=this.tokenizer.decode(n,this.decode_kwargs);this.on_finalized_text(e,!1);return}this.token_cache=ai(this.token_cache,n);let r=this.tokenizer.decode(this.token_cache,this.decode_kwargs),i;t||r.endsWith(` +`)?(i=r.slice(this.print_len),this.token_cache=[],this.print_len=0):r.length>0&&Sk(r.charCodeAt(r.length-1))?(i=r.slice(this.print_len),this.print_len+=i.length):(i=r.slice(this.print_len,r.lastIndexOf(` `)+1),this.print_len+=i.length),this.on_finalized_text(i,!1)}end(){let e;this.token_cache.length>0?(e=this.tokenizer.decode(this.token_cache,this.decode_kwargs).slice(this.print_len),this.token_cache=[],this.print_len=0):e=``,this.next_tokens_are_prompt=!0,this.on_finalized_text(e,!0)}on_finalized_text(e,t){e.length>0&&this.callback_function?.(e),t&&this.callback_function===wk&&M.IS_PROCESS_AVAILABLE&&this.callback_function?.(` +`)}};let Ek=`onnx-community/gemma-4-E2B-it-ONNX`;function Dk(e){return e.replace(/<\|?channel\|?>?\s*thought\s*/gi,`‹‹THINK››`).replace(/<\|?channell?\|?>/gi,`‹‹/THINK››`).replace(/<\|?[a-z_]+\|?>/gi,``).trim()}let Ok=null,kk=null,Ak=new oh;async function jk(){try{let e=await navigator.gpu?.requestAdapter();self.postMessage({type:`status`,status:e?`webgpu-available`:`webgpu-unavailable`})}catch{self.postMessage({type:`status`,status:`webgpu-unavailable`})}}async function Mk(){try{self.postMessage({type:`status`,status:`loading`});let e=e=>self.postMessage({type:`progress`,...e});Ok=await ym.from_pretrained(Ek,{progress_callback:e}),kk=await Py.from_pretrained(Ek,{dtype:`q4f16`,device:`webgpu`,progress_callback:e}),self.postMessage({type:`status`,status:`ready`})}catch(e){self.postMessage({type:`error`,message:e.message})}}async function Nk({messages:e,imageUrl:t,audioData:n,enableThinking:r}){if(!kk||!Ok){self.postMessage({type:`error`,message:`Model not loaded`});return}try{self.postMessage({type:`status`,status:`generating`}),Ak.reset();let i=Ok.apply_chat_template(e,{enable_thinking:r,add_generation_prompt:!0}),a=t?await Vd(t):null,o=await Ok(i,a,n??null,{add_special_tokens:!1}),s=``,c=new Tk(Ok.tokenizer,{skip_prompt:!0,skip_special_tokens:!1,callback_function:e=>{s+=e;let t=Dk(s);self.postMessage({type:`update`,text:t})}});await kk.generate({...o,max_new_tokens:512,do_sample:!1,streamer:c,stopping_criteria:[Ak]}),self.postMessage({type:`complete`,text:Dk(s)})}catch(e){self.postMessage({type:`error`,message:e.message})}}self.onmessage=e=>{switch(e.data.type){case`check`:jk();break;case`load`:Mk();break;case`generate`:Nk(e.data);break;case`interrupt`:Ak.interrupt();break}}})(); \ No newline at end of file