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Za{constructor(e){super(),this.config=e,this.pattern=new RegExp(`[^${Pf}]+|[${Pf}]+`,"gu")}pre_tokenize_text(e){return e.match(this.pattern)||[]}},bC=wC,MC=class extends Za{constructor(e){super(),this.config=e;const t=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(t,"gu")}pre_tokenize_text(e){return e.match(this.pattern)||[]}},xC=MC,TC=class extends Za{constructor(){super(),this.pattern=new RegExp(`[^\\s${Pf}]+|[${Pf}]`,"gu")}pre_tokenize_text(e,t){return e.trim().match(this.pattern)||[]}},SC=TC,EC=class extends Za{constructor(e){super(),this.config=e,this.pattern=Wf(this.config.pattern??{}),this.content=this.config.content??""}pre_tokenize_text(e){return this.pattern===null?[e]:[e.replaceAll(this.pattern,this.config.content??"")]}},AC=EC,CC=class extends Za{constructor(e){super(),this.tokenizers=(e.pretokenizers??[]).map(t=>OM(t))}pre_tokenize_text(e,t){return this.tokenizers.reduce((r,s)=>s?s.pre_tokenize(r,t):r,[e])}},kC=CC,OC=class extends Za{pre_tokenize_text(e){return RA(e)}},zC=OC,LC=class extends Za{constructor(e){super(),this.config=e,this._length=e.length}pre_tokenize_text(e){const t=[];for(let r=0;rthis.max_input_chars_per_word){t.push(this.unk_token);continue}let o=!1,l=0;const u=[];for(;l0&&(p=this.config.continuing_subword_prefix+p),this.tokens_to_ids.has(p)){f=p;break}--d}if(f===null){o=!0;break}u.push(f),l=d}o?t.push(this.unk_token):t.push(...u)}return t}},kb=RC,Ob=class zM{constructor(t,r){this.is_leaf=t,this.children=r}static default(){return new zM(!1,new Map)}},BC=class{constructor(){this.root=Ob.default()}extend(e){for(const t of e)this.push(t)}push(e){let t=this.root;for(const r of e){let s=t.children.get(r);s===void 0&&(s=Ob.default(),t.children.set(r,s)),t=s}t.is_leaf=!0}*common_prefix_search(e){let t=this.root;if(t===void 0)return;let r="";for(const s of e){if(r+=s,t=t.children.get(s),t===void 0)return;t.is_leaf&&(yield r)}}},PC=BC,Hm=class LM{constructor(t,r,s,o,l){this.token_id=t,this.node_id=r,this.pos=s,this.length=o,this.score=l,this.prev=null,this.backtrace_score=0}clone(){const t=new LM(this.token_id,this.node_id,this.pos,this.length,this.score);return t.prev=this.prev,t.backtrace_score=this.backtrace_score,t}},IC=class{constructor(e,t,r){this.chars=Array.from(e),this.len=this.chars.length,this.bos_token_id=t,this.eos_token_id=r,this.nodes=[],this.begin_nodes=Array.from({length:this.len+1},()=>[]),this.end_nodes=Array.from({length:this.len+1},()=>[]);const s=new Hm(this.bos_token_id??0,0,0,0,0),o=new Hm(this.eos_token_id??0,1,this.len,0,0);this.nodes.push(s.clone()),this.nodes.push(o.clone()),this.begin_nodes[this.len].push(o),this.end_nodes[0].push(s)}insert(e,t,r,s){const o=this.nodes.length,l=new Hm(s,o,e,t,r);this.begin_nodes[e].push(l),this.end_nodes[e+t].push(l),this.nodes.push(l)}viterbi(){const e=this.len;let t=0;for(;t<=e;){if(this.begin_nodes[t].length==0)return[];for(let u of this.begin_nodes[t]){u.prev=null;let d=0,f=null;for(let p of this.end_nodes[t]){const g=p.backtrace_score+u.score;(f===null||g>d)&&(f=p.clone(),d=g)}if(f!==null)u.prev=f,u.backtrace_score=d;else return[]}++t}const r=[],o=this.begin_nodes[e][0].prev;if(o===null)return[];let l=o.clone();for(;l.prev!==null;)r.push(l.clone()),l=l.clone().prev.clone();return r.reverse(),r}piece(e){return this.chars.slice(e.pos,e.pos+e.length).join("")}tokens(){return this.viterbi().map(t=>this.piece(t))}token_ids(){return this.viterbi().map(t=>t.token_id)}},UC=IC;function GC(e){if(e.length===0)throw new Error("Array must not be empty");let t=e[0],r=0;for(let s=1;s[s,o])),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=GC(this.scores)[0],this.unk_score=this.min_score-10,this.scores[this.unk_token_id]=this.unk_score,this.trie=new PC,this.trie.extend(this.vocab),this.fuse_unk=!0}populate_nodes(e){const t=e.chars,r=1;let s=0;for(;sr>s,t=1/0){this._heap=[],this._comparator=e,this._max_size=t}get size(){return this._heap.length}is_empty(){return this.size===0}peek(){return this._heap[0]}push(...e){return this.extend(e)}extend(e){for(const t of e)if(this.size0&&this._swap(0,t),this._heap.pop(),this._sift_down(),e}replace(e){const t=this.peek();return this._heap[0]=e,this._sift_down(),t}_parent(e){return(e+1>>>1)-1}_left(e){return(e<<1)+1}_right(e){return e+1<<1}_greater(e,t){return this._comparator(this._heap[e],this._heap[t])}_swap(e,t){const r=this._heap[e];this._heap[e]=this._heap[t],this._heap[t]=r}_sift_up(){this._sift_up_from(this.size-1)}_sift_up_from(e){for(;e>0&&this._greater(e,this._parent(e));)this._swap(e,this._parent(e)),e=this._parent(e)}_sift_down(){let e=0;for(;this._left(e)this.capacity&&this.cache.delete(this.cache.keys().next().value)}clear(){this.cache.clear()}},$C=HC,QC=class extends Xf{constructor(e){super(e),this.tokens_to_ids=$_(e.vocab),this.unk_token_id=this.tokens_to_ids.get(e.unk_token),this.unk_token=e.unk_token,this.vocab=new Array(this.tokens_to_ids.size);for(const[r,s]of this.tokens_to_ids)this.vocab[s]=r;const t=Array.isArray(e.merges[0]);this.merges=t?e.merges:e.merges.map(r=>r.split(" ",2)),this.bpe_ranks=new Map(this.merges.map((r,s)=>[JSON.stringify(r),s])),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 $C(this.cache_capacity)}clear_cache(){this.cache.clear()}bpe(e){if(e.length===0)return[];const t=this.cache.get(e);if(t!==void 0)return t;const r=Array.from(e);this.end_of_word_suffix&&(r[r.length-1]+=this.end_of_word_suffix);let s=[];if(r.length>1){const o=new qC((d,f)=>d.score`<0x${u.toString(16).toUpperCase().padStart(2,"0")}>`);l.every(u=>this.tokens_to_ids.has(u))?t.push(...l):t.push(this.unk_token)}else t.push(this.unk_token)}return t}},Lb=QC,WC=class extends Xf{constructor(e,t){super(e);const r=e.vocab;this.tokens_to_ids=$_(t.target_lang?r[t.target_lang]:r),this.bos_token=t.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=t.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=t.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=t.unk_token,this.unk_token_id=this.tokens_to_ids.get(this.unk_token),this.vocab=new Array(this.tokens_to_ids.size);for(const[s,o]of this.tokens_to_ids)this.vocab[o]=s}encode(e){return e}},YC=WC;function XC(e,t){switch(e.type){case"WordPiece":return new kb(e);case"Unigram":return new zb(e,t.eos_token);case"BPE":return new Lb(e);default:if(e.vocab)return Array.isArray(e.vocab)?new zb(e,t.eos_token):Object.hasOwn(e,"continuing_subword_prefix")&&Object.hasOwn(e,"unk_token")?Object.hasOwn(e,"merges")?new Lb(e):new kb(e):new YC(e,{target_lang:t.target_lang,bos_token:t.bos_token,eos_token:t.eos_token,pad_token:t.pad_token,unk_token:t.unk_token});throw new Error(`Unknown TokenizerModel type: ${e?.type}`)}}var ZC=XC,KC=class extends Su{constructor(e){super(),this.config=e}_call(e,...t){return this.post_process(e,...t)}},Eu=KC,JC=class extends Eu{post_process(e,t=null,r=!0){const s=t===null?this.config.single:this.config.pair;let o=[],l=[];for(const u of s)"SpecialToken"in u?r&&(o.push(u.SpecialToken.id),l.push(u.SpecialToken.type_id)):"Sequence"in u&&(u.Sequence.id==="A"?(o=Qa(o,e),l=Qa(l,new Array(e.length).fill(u.Sequence.type_id))):u.Sequence.id==="B"&&(o=Qa(o,t),l=Qa(l,new Array(t.length).fill(u.Sequence.type_id))));return{tokens:o,token_type_ids:l}}},ek=JC,tk=class extends Eu{post_process(e,t=null){return{tokens:e,tokens_pair:t}}},nk=tk,ak=class extends Eu{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t=null,r=!0){r&&(e=Qa([this.cls[0]],e,[this.sep[0]]));let s=new Array(e.length).fill(0);if(t){const o=[],l=r?[this.sep[0]]:[];e=Qa(e,o,t,l),s=Qa(s,new Array(t.length+o.length+l.length).fill(1))}return{tokens:e,token_type_ids:s}}},rk=ak,sk=class extends Eu{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,t,r=!0){r&&(e=Qa([this.cls[0]],e,[this.sep[0]]));let s=new Array(e.length).fill(0);if(t){const o=r?[this.sep[0]]:[],l=r?[this.sep[0]]:[];e=Qa(e,o,t,l),s=Qa(s,new Array(t.length+o.length+l.length).fill(1))}return{tokens:e,token_type_ids:s}}},ik=sk,ok=class extends Eu{constructor(e){super(e),this.processors=(e.processors??[]).map(t=>FM(t))}post_process(e,t=null,r=!0){let s={tokens:e,tokens_pair:t};for(const o of this.processors)s=o.post_process(s.tokens,s.tokens_pair,r);return s}},lk=ok;function ck(e){if(e===null)return null;switch(e.type){case"TemplateProcessing":return new ek(e);case"ByteLevel":return new nk(e);case"BertProcessing":return new rk(e);case"RobertaProcessing":return new ik(e);case"Sequence":return new lk(e);default:throw new Error(`Unknown PostProcessor type: ${e.type}`)}}var FM=ck,uk=class extends Su{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("")}},Ka=uk,dk=class extends Ka{constructor(e){super(e),this.byte_decoder=AA,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){const t=e.join(""),r=new Uint8Array([...t].map(s=>this.byte_decoder[s]));return this.text_decoder.decode(r)}decode_chain(e){const t=[];let r=[];for(const s of e)this.added_tokens.find(o=>o.content===s)!==void 0?(r.length>0&&(t.push(this.convert_tokens_to_string(r)),r=[]),t.push(s)):r.push(s);return r.length>0&&t.push(this.convert_tokens_to_string(r)),t}},fk=dk,hk=class extends Ka{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map((t,r)=>{if(r!==0){const s=this.config.prefix;s&&t.startsWith(s)?t=t.replace(s,""):t=" "+t}return this.cleanup&&(t=H_(t)),t})}},pk=hk,mk=class extends Ka{constructor(e){super(e),this.replacement=e.replacement??"▁"}decode_chain(e){const t=[];for(let r=0;rt.replaceAll(this.suffix,r===e.length-1?"":" "))}},yk=gk,vk=class extends Ka{constructor(e){super(e),this.pad_token=e.pad_token??"",this.word_delimiter_token=e.word_delimiter_token??"",this.cleanup=e.cleanup}convert_tokens_to_string(e){if(e.length===0)return"";const t=[e[0]];for(let o=1;oo!==this.pad_token).join("");return this.cleanup&&(s=H_(s).replaceAll(this.word_delimiter_token," ").trim()),s}decode_chain(e){return[this.convert_tokens_to_string(e)]}},wk=vk,bk=class extends Ka{constructor(e){super(e),this.decoders=(e.decoders??[]).map(t=>NM(t))}decode_chain(e){return this.decoders.reduce((t,r)=>r.decode_chain(t),e)}},Mk=bk,xk=class extends Ka{decode_chain(e){const t=Wf(this.config.pattern),r=this.config.content??"";return t===null?e:e.map(s=>s.replaceAll(t,r))}},Tk=xk,Sk=class extends Ka{decode_chain(e){return[e.join("")]}},Ek=Sk,Ak=class extends Ka{constructor(e){super(e),this.content=e.content??"",this.start=e.start??0,this.stop=e.stop??0}decode_chain(e){return e.map(t=>{let r=0;for(let o=0;o")){const l=parseInt(s.slice(3,5),16);isNaN(l)||(o=l)}if(o!==null)r.push(o);else{if(r.length>0){const l=this.text_decoder.decode(Uint8Array.from(r));t.push(l),r=[]}t.push(s)}}if(r.length>0){const s=this.text_decoder.decode(Uint8Array.from(r));t.push(s),r=[]}return t}},Ok=kk;function zk(e){if(e===null)return null;switch(e.type){case"ByteLevel":return new fk(e);case"WordPiece":return new pk(e);case"Metaspace":return new _k(e);case"BPEDecoder":return new yk(e);case"CTC":return new wk(e);case"Sequence":return new Mk(e);case"Replace":return new Tk(e);case"Fuse":return new Ek(e);case"Strip":return new Ck(e);case"ByteFallback":return new Ok(e);default:throw new Error(`Unknown Decoder type: ${e.type}`)}}var NM=zk,Lk=class{constructor(e,t){const r=Cb(e,"Tokenizer",["model","decoder","post_processor","pre_tokenizer","normalizer"]);if(r)throw new Error(r);const s=Cb(t,"Config");if(s)throw new Error(s);this.tokenizer=e,this.config=t,this.normalizer=kM(this.tokenizer.normalizer),this.pre_tokenizer=OM(this.tokenizer.pre_tokenizer),this.model=ZC(this.tokenizer.model,this.config),this.post_processor=FM(this.tokenizer.post_processor),this.decoder=NM(this.tokenizer.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];const o=[],l=[];this.added_tokens_map=new Map;for(const u of this.tokenizer.added_tokens){const d=new SA(u);if(this.added_tokens.push(d),this.model.tokens_to_ids.set(d.content,d.id),this.model.vocab[d.id]=d.content,d.special&&(this.special_tokens.push(d.content),this.all_special_ids.push(d.id)),this.added_tokens_map.set(d.content,d),d.normalized&&this.normalizer!==null){const f=this.normalizer(d.content);l.push(f),this.added_tokens_map.set(f,d)}else o.push(d.content)}(this.config.additional_special_tokens??[]).forEach(u=>{this.special_tokens.includes(u)||this.special_tokens.push(u)}),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 Eb(o),this.splitter_normalized=new Eb(l),this.remove_space=this.config.remove_space,this.clean_up_tokenization_spaces=this.config.clean_up_tokenization_spaces??!0,this.do_lowercase_and_remove_accent=this.config.do_lowercase_and_remove_accent??!1}encode(e,{text_pair:t=null,add_special_tokens:r=!0,return_token_type_ids:s=null}={}){const{tokens:o,token_type_ids:l}=this.tokenize_helper(e,{text_pair:t,add_special_tokens:r}),u=o.map(f=>this.added_tokens_map.get(f)?.id??this.model.tokens_to_ids.get(f)??this.model.unk_token_id),d={ids:u,tokens:o,attention_mask:new Array(u.length).fill(1)};return s&&l&&(d.token_type_ids=l),d}decode(e,t={}){if(!Array.isArray(e)||e.length===0||!LA(e[0]))throw Error("token_ids must be a non-empty array of integers.");let r=e.map(o=>this.model.vocab[Number(o)]??this.model.unk_token);t.skip_special_tokens&&(r=r.filter(o=>!this.special_tokens.includes(o)));let s=this.decoder?this.decoder(r):r.join(" ");return this.decoder&&this.decoder.end_of_word_suffix&&(s=s.replaceAll(this.decoder.end_of_word_suffix," "),t.skip_special_tokens&&(s=s.trim())),(t.clean_up_tokenization_spaces??this.clean_up_tokenization_spaces)&&(s=H_(s)),s}tokenize(e,{text_pair:t=null,add_special_tokens:r=!1}={}){return this.tokenize_helper(e,{text_pair:t,add_special_tokens:r}).tokens}encode_text(e){if(e===null)return null;const t=this.splitter_unnormalized.split(e);return t.forEach((r,s)=>{const o=this.added_tokens_map.get(r);o&&(o.lstrip&&s>0&&(t[s-1]=t[s-1].trimEnd()),o.rstrip&&s{if(r.length===0)return[];if(this.added_tokens_map.has(r))return[r];if(this.remove_space===!0&&(r=r.trim().split(/\s+/).join(" ")),this.do_lowercase_and_remove_accent&&(r=NA(r)),this.normalizer!==null&&(r=this.normalizer(r)),r.length===0)return[];const o=this.splitter_normalized.split(r);return o.forEach((l,u)=>{const 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r.__bool__().value?this.evaluate(e.right,t):r;case"or":return r.__bool__().value?r:this.evaluate(e.right,t)}const s=this.evaluate(e.right,t);switch(e.operator.value){case"==":return new Fe(r.value==s.value);case"!=":return new Fe(r.value!=s.value)}if(r instanceof St||s instanceof St){if(s instanceof St&&["in","not in"].includes(e.operator.value))return new Fe(e.operator.value==="not in");throw new Error(`Cannot perform operation ${e.operator.value} on undefined values`)}else{if(r instanceof Ot||s instanceof Ot)throw new Error("Cannot perform operation on null values");if(e.operator.value==="~")return new be(r.value.toString()+s.value.toString());if((r instanceof je||r instanceof Gt)&&(s instanceof je||s instanceof Gt)){const o=r.value,l=s.value;switch(e.operator.value){case"+":case"-":case"*":{const u=e.operator.value==="+"?o+l:e.operator.value==="-"?o-l:o*l;return r instanceof Gt||s instanceof Gt?new Gt(u):new je(u)}case"/":return new Gt(o/l);case"%":{const u=o%l;return r instanceof 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St||f.value&&!e.__bool__().value?d:e}if(e instanceof Ke){switch(o){case"sort":{const[l,u]=this.evaluateArguments(s.args,r),d=l.at(0)??u.get("reverse")??new Fe(!1);if(!(d instanceof Fe))throw new Error("reverse must be a boolean");const f=l.at(1)??u.get("case_sensitive")??new Fe(!1);if(!(f instanceof Fe))throw new Error("case_sensitive must be a boolean");const p=l.at(2)??u.get("attribute")??new Ot;if(!(p instanceof be||p instanceof je||p instanceof Ot))throw new Error("attribute must be a string, integer, or null");const g=y=>{if(p instanceof Ot)return y;const w=p instanceof je?String(p.value):p.value;return Vb(y,w)};return new Ke(e.value.slice().sort((y,w)=>{const b=g(y),S=g(w),E=d_(b,S,f.value);return d.value?-E:E}))}case"selectattr":case"rejectattr":{const l=o==="selectattr";if(e.value.some(y=>!(y instanceof un)))throw new Error(`\`${o}\` can only be applied to array of objects`);if(s.args.some(y=>y.type!=="StringLiteral"))throw new Error(`arguments of \`${o}\` must be 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this._nearest_interpolate_4d||(this._nearest_interpolate_4d=Ys([8,10,18,0,58,129,1,10,41,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,18,10,4,109,111,100,101,34,7,110,101,97,114,101,115,116,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,21],this.session_options,"y")),this._nearest_interpolate_4d}static get bilinear_interpolate_4d(){return this._bilinear_interpolate_4d||(this._bilinear_interpolate_4d=Ys([8,9,18,0,58,128,1,10,40,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,17,10,4,109,111,100,101,34,6,108,105,110,101,97,114,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bilinear_interpolate_4d}static get bicubic_interpolate_4d(){return this._bicubic_interpolate_4d||(this._bicubic_interpolate_4d=Ys([8,9,18,0,58,127,10,39,10,1,120,10,0,10,0,10,1,115,18,1,121,34,6,82,101,115,105,122,101,42,16,10,4,109,111,100,101,34,5,99,117,98,105,99,160,1,3,18,1,114,90,31,10,1,120,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,90,15,10,1,115,18,10,10,8,8,7,18,4,10,2,8,4,98,31,10,1,121,18,26,10,24,8,1,18,20,10,3,18,1,98,10,3,18,1,99,10,3,18,1,104,10,3,18,1,119,66,2,16,20],this.session_options,"y")),this._bicubic_interpolate_4d}static get matmul(){return this._matmul||(this._matmul=Ys([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 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b=o.reduce((k,L)=>k+L,0)/o.length,S=Math.sqrt(o.reduce((k,L)=>k+(L-b)**2,0)/(o.length-r)),E=new me(e.type,[b],[]);return[new me(e.type,[S],[]),E]}t=xr(t,l.length);const u=Z_(e,t,s),d=u.data,[f,p,g]=gu((w,b,S,E)=>w+(b-d[E])**2,e,t,s);for(let w=0;wp+g,0);return new me(e.type,[f/o.length],[])}t=xr(t,s.length);const[l,u,d]=gu((f,p)=>f+p,e,t,r);if(s[t]!==1)for(let f=0;f=0;--r)t[r]=s,s*=e[r];return t}function K_(e,t,r,s){const o=e.reduce((l,u)=>l*u,1);return new me(r,new s(o).fill(t),e)}function On(e,t){let r,s;if(typeof t=="number")r="float32",s=Float32Array;else if(typeof t=="bigint")r="int64",s=BigInt64Array;else if(typeof t=="boolean")r="bool",s=Uint8Array;else throw new Error(`Unsupported data type: ${typeof t}`);return K_(e,t,r,s)}function m_(e,t){return On(e.dims,t)}function ha(e){return K_(e,1n,"int64",BigInt64Array)}function nx(e){return ha(e.dims)}function ax(e){return K_(e,0n,"int64",BigInt64Array)}function rx(e){return ax(e.dims)}function mO(e){const t=e.reduce((r,s)=>r*s,1);return new me("float32",Float32Array.from({length:t},()=>W_.gauss()),e)}function _O(e,t){if(e.dims.length!==2)throw new Error("The tensor must have 2 dimensions");if(e.dims.at(-1)%8!==0)throw new Error("The last dimension of the tensor must be a multiple of 8");if(!["binary","ubinary"].includes(t))throw new Error("The precision must be either 'binary' or 'ubinary'");const r=t==="binary",s=r?"int8":"uint8",o=r?Int8Array:Uint8Array,l=e.data,u=new o(l.length/8);for(let d=0;d0?1:0,p=Math.floor(d/8),g=d%8;u[p]|=f<<7-g,r&&g===0&&(u[p]-=128)}return new me(s,u,[e.dims[0],e.dims[1]/8])}async function sx(e){if(!e)throw new Error("modelId is required for get_tokenizer_files");return(await Zf(e,"tokenizer_config.json",{})).exists?["tokenizer.json","tokenizer_config.json"]:[]}async function ix(e,t){const r=await sx(e);return await Promise.all(r.map(s=>ss(e,s,!0,t)))}function ox(e){const t=e.dims;switch(t.length){case 1:return e.tolist();case 2:if(t[0]!==1)throw new Error("Unable to decode tensor with `batch size !== 1`. Use `tokenizer.batch_decode(...)` for batched inputs.");return e.tolist()[0];default:throw new Error(`Expected tensor to have 1-2 dimensions, got ${t.length}.`)}}var gO=["bos_token","eos_token","unk_token","sep_token","pad_token","cls_token","mask_token"];function yO(e,t,r,s){for(const o of Object.keys(e)){const l=t-e[o].length,u=r(o),d=new Array(l).fill(u);e[o]=s==="right"?Sr(e[o],d):Sr(d,e[o])}}function vO(e,t){for(const r of Object.keys(e))e[r].length=t}function Ui(e,...t){for(const r of t){if(!Object.hasOwn(e,r))continue;const s=e[r];if(s)if(typeof s=="object"){if(s.__type==="AddedToken")return s.content;throw Error(`Unknown token: ${s}`)}else return s}return null}function wO(e){const t=[];for(const r of e.get_added_tokens_decoder().values())r.special&&t.push(r);return t}var De=class extends Oa{return_token_type_ids=!1;padding_side="right";constructor(e,t){if(super(),this._tokenizerJSON=e,this._tokenizerConfig=t,this._tokenizer=new Fk(e,t),this.config=t,this.padding_side=t.padding_side??this.padding_side,this.mask_token=Ui(t,"mask_token"),this.mask_token_id=this._tokenizer.token_to_id(this.mask_token),this.pad_token=Ui(t,"pad_token","eos_token"),this.pad_token_id=this._tokenizer.token_to_id(this.pad_token),this.sep_token=Ui(t,"sep_token"),this.sep_token_id=this._tokenizer.token_to_id(this.sep_token),this.unk_token=Ui(t,"unk_token"),this.unk_token_id=this._tokenizer.token_to_id(this.unk_token),this.bos_token=Ui(t,"bos_token"),this.bos_token_id=this._tokenizer.token_to_id(this.bos_token),this.eos_token=Ui(t,"eos_token"),this.eos_token_id=this._tokenizer.token_to_id(this.eos_token),this.chat_template=t.chat_template??null,Array.isArray(this.chat_template)){const s=Object.create(null);for(const{name:o,template:l}of this.chat_template){if(typeof o!="string"||typeof l!="string")throw new Error('Chat template must be a list of objects with "name" and "template" properties');s[o]=l}this.chat_template=s}this._compiled_template_cache=new Map;const r=wO(this._tokenizer);this.all_special_ids=r.map(s=>s.id),this.all_special_tokens=r.map(s=>s.content)}static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:s=null,local_files_only:o=!1,revision:l="main"}={}){const u=await ix(e,{progress_callback:t,config:r,cache_dir:s,local_files_only:o,revision:l});return new this(...u)}get_vocab(){return this._tokenizer.get_vocab()}get model_max_length(){return this._tokenizerConfig.model_max_length??1/0}get add_eos_token(){return this._tokenizerConfig.add_eos_token}get add_bos_token(){return this._tokenizerConfig.add_bos_token}convert_tokens_to_ids(e){return typeof e=="string"?this._tokenizer.token_to_id(e):e.map(t=>this._tokenizer.token_to_id(t))}_call(e,{text_pair:t=null,add_special_tokens:r=!0,padding:s=!1,truncation:o=null,max_length:l=null,return_tensor:u=!0,return_token_type_ids:d=null}={}){const f=Array.isArray(e);let p;if(f){if(e.length===0)throw Error("text array must be non-empty");if(t!==null){if(Array.isArray(t)){if(e.length!==t.length)throw Error("text and text_pair must have the same length")}else throw Error("text_pair must also be an array");p=e.map((y,w)=>this._encode_plus(y,{text_pair:t[w],add_special_tokens:r,return_token_type_ids:d}))}else p=e.map(y=>this._encode_plus(y,{add_special_tokens:r,return_token_type_ids:d}))}else{if(e==null)throw Error("text may not be null or undefined");if(Array.isArray(t))throw Error("When specifying `text_pair`, since `text` is a string, `text_pair` must also be a string (i.e., not an array).");p=[this._encode_plus(e,{text_pair:t,add_special_tokens:r,return_token_type_ids:d})]}if(l===null?l=this.model_max_length:o===null&&(s===!0?(Re.warn("`max_length` is ignored when `padding: true` and there is no truncation strategy. To pad to max length, use `padding: 'max_length'`."),l=this.model_max_length):s===!1&&(Re.warn("Truncation was not explicitly activated but `max_length` is provided a specific value, please use `truncation: true` to explicitly truncate examples to max length."),o=!0)),s===!0&&(l=Math.min(Ht(p.map(y=>y.input_ids.length))[0],l??1/0)),l=Math.min(l,this.model_max_length??1/0),s||o)for(let y=0;yl?o&&vO(p[y],l):s&&yO(p[y],l,w=>w==="input_ids"?this.pad_token_id:0,this.padding_side));const g={};if(u){if(!(s&&o)&&p.some(w=>{for(const b of Object.keys(w))if(w[b].length!==p[0][b]?.length)return!0;return!1}))throw Error("Unable to create tensor, you should probably activate truncation and/or padding with 'padding=true' and 'truncation=true' to have batched tensors with the same length.");const y=[p.length,p[0].input_ids.length];for(const w of Object.keys(p[0]))g[w]=new me("int64",BigInt64Array.from(p.flatMap(b=>b[w]).map(BigInt)),y)}else{for(const y of Object.keys(p[0]))g[y]=p.map(w=>w[y]);if(!f)for(const y of Object.keys(g))g[y]=g[y][0]}return g}_encode_text(e){return e===null?null:this._tokenizer.encode(e).tokens}_encode_plus(e,{text_pair:t=null,add_special_tokens:r=!0,return_token_type_ids:s=null}={}){const{ids:o,attention_mask:l,token_type_ids:u}=this._tokenizer.encode(e,{text_pair:t,add_special_tokens:r,return_token_type_ids:s??this.return_token_type_ids});return{input_ids:o,attention_mask:l,...u?{token_type_ids:u}:{}}}tokenize(e,{pair:t=null,add_special_tokens:r=!1}={}){return this._tokenizer.tokenize(e,{text_pair:t,add_special_tokens:r})}encode(e,{text_pair:t=null,add_special_tokens:r=!0,return_token_type_ids:s=null}={}){return this._tokenizer.encode(e,{text_pair:t,add_special_tokens:r,return_token_type_ids:s}).ids}batch_decode(e,t={}){return e instanceof me&&(e=e.tolist()),e.map(r=>this.decode(r,t))}decode(e,t={}){if(e instanceof me&&(e=ox(e)),!Array.isArray(e)||e.length===0||!wA(e[0]))throw Error("token_ids must be a non-empty array of integers.");return this.decode_single(e,t)}decode_single(e,{skip_special_tokens:t=!1,clean_up_tokenization_spaces:r=null}){return this._tokenizer.decode(e,{skip_special_tokens:t,clean_up_tokenization_spaces:r})}get_chat_template({chat_template:e=null,tools:t=null}={}){if(this.chat_template&&typeof this.chat_template=="object"){const r=this.chat_template;if(e!==null&&Object.hasOwn(r,e))e=r[e];else if(e===null)if(t!==null&&"tool_use"in r)e=r.tool_use;else if("default"in r)e=r.default;else throw Error(`This model has multiple chat templates with no default specified! Please either pass a chat template or the name of the template you wish to use to the 'chat_template' argument. Available template names are ${Object.keys(r).sort()}.`)}else if(e===null)if(this.chat_template)e=this.chat_template;else throw Error("Cannot use apply_chat_template() because tokenizer.chat_template is not set and no template argument was passed! For information about writing templates and setting the tokenizer.chat_template attribute, please see the documentation at https://huggingface.co/docs/transformers/main/en/chat_templating");return e}apply_chat_template(e,{tools:t=null,documents:r=null,chat_template:s=null,add_generation_prompt:o=!1,tokenize:l=!0,padding:u=!1,truncation:d=!1,max_length:f=null,return_tensor:p=!0,return_dict:g=!0,tokenizer_kwargs:y={},...w}={}){if(s=this.get_chat_template({chat_template:s,tools:t}),typeof s!="string")throw Error(`chat_template must be a string, but got ${typeof s}`);let b=this._compiled_template_cache.get(s);b===void 0&&(b=new C3(s),this._compiled_template_cache.set(s,b));const S=Object.create(null);for(const z of gO){const k=Ui(this.config,z);k&&(S[z]=k)}const E=b.render({messages:e,add_generation_prompt:o,tools:t,documents:r,...S,...w});if(l){const z=this._call(E,{add_special_tokens:!1,padding:u,truncation:d,max_length:f,return_tensor:p,...y});return g?z:z.input_ids}return E}};function J_(e,t,r,s){if(!("language_codes"in e)||!Array.isArray(e.language_codes))throw new Error("Tokenizer must have `language_codes` attribute set and it should be an array of language ids.");if(!("languageRegex"in e)||!(e.languageRegex instanceof RegExp))throw new Error("Tokenizer must have `languageRegex` attribute set and it should be a regular expression.");if(!("lang_to_token"in e)||typeof e.lang_to_token!="function")throw new Error("Tokenizer must have `lang_to_token` attribute set and it should be a function.");const o=s.src_lang,l=s.tgt_lang;if(!e.language_codes.includes(l))throw new Error(`Target language code "${l}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);if(o!==void 0){if(!e.language_codes.includes(o))throw new Error(`Source language code "${o}" is not valid. Must be one of: {${e.language_codes.join(", ")}}`);for(const u of e._tokenizer.post_processor.config.single)if("SpecialToken"in u&&e.languageRegex.test(u.SpecialToken.id)){u.SpecialToken.id=e.lang_to_token(o);break}}return s.forced_bos_token_id=e._tokenizer.token_to_id(e.lang_to_token(l)),e._call(t,r)}var lx={};Al(lx,{AlbertTokenizer:()=>bO,AutoTokenizer:()=>yt,BartTokenizer:()=>MO,BertTokenizer:()=>xO,BlenderbotSmallTokenizer:()=>TO,BlenderbotTokenizer:()=>SO,BloomTokenizer:()=>EO,CLIPTokenizer:()=>CO,CamembertTokenizer:()=>AO,CodeGenTokenizer:()=>OO,CodeLlamaTokenizer:()=>kO,CohereTokenizer:()=>zO,ConvBertTokenizer:()=>LO,DebertaTokenizer:()=>NO,DebertaV2Tokenizer:()=>FO,DistilBertTokenizer:()=>DO,ElectraTokenizer:()=>RO,EsmTokenizer:()=>BO,FalconTokenizer:()=>PO,GPT2Tokenizer:()=>GO,GPTNeoXTokenizer:()=>UO,GemmaTokenizer:()=>IO,HerbertTokenizer:()=>jO,LlamaTokenizer:()=>VO,M2M100Tokenizer:()=>qO,MBart50Tokenizer:()=>$O,MBartTokenizer:()=>cx,MPNetTokenizer:()=>YO,MarianTokenizer:()=>HO,MgpstrTokenizer:()=>QO,MobileBertTokenizer:()=>WO,NllbTokenizer:()=>XO,NougatTokenizer:()=>ZO,PreTrainedTokenizer:()=>De,Qwen2Tokenizer:()=>KO,RoFormerTokenizer:()=>ez,RobertaTokenizer:()=>JO,SiglipTokenizer:()=>tz,SpeechT5Tokenizer:()=>nz,SqueezeBertTokenizer:()=>az,T5Tokenizer:()=>rz,TokenizersBackend:()=>De,VitsTokenizer:()=>iz,Wav2Vec2CTCTokenizer:()=>oz,WhisperTokenizer:()=>dz,XLMRobertaTokenizer:()=>fz,XLMTokenizer:()=>hz});var bO=class extends De{return_token_type_ids=!0},MO=class extends De{},xO=class extends De{return_token_type_ids=!0},TO=class extends De{},SO=class extends De{},EO=class extends De{},AO=class extends De{},CO=class extends De{},kO=class extends De{},OO=class extends De{},zO=class extends De{},LO=class extends De{return_token_type_ids=!0},FO=class extends De{return_token_type_ids=!0},NO=class extends De{return_token_type_ids=!0},DO=class extends De{},RO=class extends De{return_token_type_ids=!0},BO=class extends De{},PO=class extends De{},IO=class extends De{},UO=class extends De{},GO=class extends De{},jO=class extends De{return_token_type_ids=!0},VO=class extends De{padding_side="left"},qO=class extends De{constructor(e,t){super(e,t),this.languageRegex=/^__[a-z]{2,3}__$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)).map(r=>r.slice(2,-2)),this.lang_to_token=r=>`__${r}__`}_build_translation_inputs(e,t,r){return J_(this,e,t,r)}},HO=class extends De{constructor(e,t){super(e,t),this.languageRegex=/^(>>\w+<<)\s*/g,this.supported_language_codes=Array.from(this.get_vocab().keys()).filter(r=>this.languageRegex.test(r)),Re.warn('WARNING: `MarianTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. Therefore, you may experience slightly inaccurate results.')}_encode_text(e){if(e===null)return null;const[t,...r]=e.trim().split(this.languageRegex);if(r.length===0)return super._encode_text(t);if(r.length===2){const[s,o]=r;return this.supported_language_codes.includes(s)||Re.warn(`Unsupported language code "${s}" detected, which may lead to unexpected behavior. Should be one of: ${JSON.stringify(this.supported_language_codes)}`),Sr([s],super._encode_text(o))}}},cx=class extends De{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{2}_[A-Z]{2}$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)).map(r=>r),this.lang_to_token=r=>r}_build_translation_inputs(e,t,r){return J_(this,e,t,r)}},$O=class extends cx{},QO=class extends De{},WO=class extends De{return_token_type_ids=!0},YO=class extends De{},XO=class extends De{constructor(e,t){super(e,t),this.languageRegex=/^[a-z]{3}_[A-Z][a-z]{3}$/,this.language_codes=this.all_special_tokens.filter(r=>this.languageRegex.test(r)),this.lang_to_token=r=>r}_build_translation_inputs(e,t,r){return J_(this,e,t,r)}},ZO=class extends De{},KO=class extends De{},JO=class extends De{},ez=class extends De{return_token_type_ids=!0},tz=class extends De{},nz=class extends De{},az=class extends De{return_token_type_ids=!0},rz=class extends De{},sz=class extends Ka{decode_chain(e){let t="";for(let r=1;r[t,e]),["burmese","my"],["valencian","ca"],["flemish","nl"],["haitian","ht"],["letzeburgesch","lb"],["pushto","ps"],["panjabi","pa"],["moldavian","ro"],["moldovan","ro"],["sinhalese","si"],["castilian","es"]]);function cz(e){e=e.toLowerCase();let t=lz.get(e);if(t===void 0){const r=e.match(/^<\|([a-z]{2})\|>$/);if(r&&(e=r[1]),Cf.has(e))t=e;else{const o=e.length===2?Cf.keys():Cf.values();throw new Error(`Language "${e}" is not supported. Must be one of: ${JSON.stringify(Array.from(o))}`)}}return t}var uz="\\p{P}\\u0021-\\u002F\\u003A-\\u0040\\u005B-\\u0060\\u007B-\\u007E",n1=new RegExp(`^[${uz}]+$`,"gu"),dz=class extends De{get timestamp_begin(){return this._tokenizer.token_to_id("<|notimestamps|>")+1}_decode_asr(e,{return_timestamps:t=!1,return_language:r=!1,time_precision:s=null,force_full_sequences:o=!0}={}){if(s===null)throw Error("Must specify time_precision");let l=null;const u=t==="word";function d(){return{language:l,timestamp:[null,null],text:""}}const f=[];let p=d(),g=0;const y=this.timestamp_begin,b=y+1500;let S=[],E=[],z=!1,k=null;const L=new Set(this.all_special_ids);for(const B of e){const j=B.tokens,C=u?B.token_timestamps:null;let ue=null,oe=y;if("stride"in B){const[de,re,W]=B.stride;if(g-=re,k=de-W,re&&(oe=re/s+y),W)for(let pe=j.length-1;pe>=0;--pe){const V=Number(j[pe]);if(V>=y){if(ue!==null&&(V-y)*s=y&&re<=b){const W=(re-y)*s+g,pe=mu(W,2);if(ue!==null&&re>=ue)z=!0;else if(z||S.length>0&&re0?(S.push(he),u&&E.push(_e)):S.every(de=>de.length===0)&&(p=d(),S=[],he=[],E=[],_e=[])}if(S.length>0){if(o&&t)throw new Error("Whisper did not predict an ending timestamp, which can happen if audio is cut off in the middle of a word. Also make sure WhisperTimeStampLogitsProcessor was used during generation.");const[B,j]=this.findLongestCommonSequence(S,E),C=this.decode(B);p.text=C,u&&(p.words=this.collateWordTimestamps(B,j,l)),f.push(p)}let R=Object.create(null);const N=f.map(B=>B.text).join("");if(t||r){for(let B=0;B0;let u=l?[]:null,d=l?t[0]:null;for(let f=1;fre===oe[W]&&d[N+W]<=t[f][C+W]).length:he=j.filter((re,W)=>re===oe[W]).length;const _e=R/1e4,de=he/R+_e;he>1&&de>g&&(g=de,y=[N,B,C,ue])}const[b,S,E,z]=y,k=Math.floor((S+b)/2),L=Math.floor((z+E)/2);o.push(...r.slice(0,k)),r=p.slice(L),s=r.length,l&&(u.push(...d.slice(0,k)),d=t[f].slice(L))}return o.push(...r),l?(u.push(...d),[o,u]):[o,[]]}collateWordTimestamps(e,t,r){const[s,o,l]=this.combineTokensIntoWords(e,r),u=[];for(let d=0;d=s){const u=((l-s)*r).toFixed(2);o.push(`<|${u}|>`),o.push([])}else o[o.length-1].push(l);return o=o.map(l=>typeof l=="string"?l:super.decode(l,t)),o.join("")}splitTokensOnUnicode(e){const t=this.decode(e,{decode_with_timestamps:!0}),r="�",s=[],o=[],l=[];let u=[],d=[],f=0;for(let p=0;p=this._tokenizer.token_to_id("<|endoftext|>"),w=f.startsWith(" "),b=f.trim(),S=n1.test(b);if(y||w||S||o.length===0)o.push(f),l.push(p),u.push(g);else{const E=o.length-1;o[E]+=f,l[E].push(...p),u[E].push(...g)}}return[o,l,u]}mergePunctuations(e,t,r,s,o){const l=structuredClone(e),u=structuredClone(t),d=structuredClone(r);let f=l.length-2,p=l.length-1;for(;f>=0;)l[f].startsWith(" ")&&s.includes(l[f].trim())?(l[p]=l[f]+l[p],u[p]=Sr(u[f],u[p]),d[p]=Sr(d[f],d[p]),l[f]="",u[f]=[],d[f]=[]):p=f,--f;for(f=0,p=1;pg),u.filter(g=>g.length>0),d.filter(g=>g.length>0)]}},fz=class extends De{},hz=class extends De{return_token_type_ids=!0;constructor(e,t){super(e,t),Re.warn('WARNING: `XLMTokenizer` is not yet supported by Hugging Face\'s "fast" tokenizers library. 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Specify `power` to fix this issue.");if(!g)throw new Error("`preemphasis_htk_flavor=false` is not currently supported.");if(u)switch(d){case"reflect":{const J=Math.floor((o-1)/2)+1;e=Tz(e,J,J);break}case"constant":{const J=Math.floor(o/2),D=new e.constructor(e.length+2*J);D.set(e,J),e=D;break}default:throw new Error(`pad_mode="${d}" not implemented yet.`)}let oe=Math.floor(1+Math.floor((e.length-r)/s));R!==null&&oeoe?B&&(de=N):de=_e=N);const re=new Y3(o),W=new Float64Array(o),pe=new Float64Array(re.outputBufferSize),V=new Float32Array(he*de);for(let J=0;J<_e;++J){const D=J*s,te=Math.min(e.length-D,r);te!==r&&W.fill(0,0,r);for(let ae=0;ae=1;--ae)W[ae]-=p*W[ae-1];W[0]*=1-p}for(let ae=0;aeMath.pow(d,.85));break;default:throw new Error(`Unknown window type ${t}.`)}if(r&&(u=u.subarray(0,e)),s===null)return u;if(e>s)throw new Error(`Length of the window (${e}) may not be larger than frame_length (${s})`);return u}function Az(e,t){const r=e.reduce((l,u)=>l+u.length,0),s=new ArrayBuffer(44),o=new DataView(s);return bf(o,0,"RIFF"),o.setUint32(4,36+r*4,!0),bf(o,8,"WAVE"),bf(o,12,"fmt "),o.setUint32(16,16,!0),o.setUint16(20,3,!0),o.setUint16(22,1,!0),o.setUint32(24,t,!0),o.setUint32(28,t*4,!0),o.setUint16(32,4,!0),o.setUint16(34,32,!0),bf(o,36,"data"),o.setUint32(40,r*4,!0),new Blob([s,...e.map(l=>l.buffer)],{type:"audio/wav"})}function bf(e,t,r){for(let s=0;ss+o.length,0),t=new Float32Array(e);let r=0;for(const s of this.audio)t.set(s,r),r+=s.length;return t}else return this.audio}toBlob(){let e=this.audio;return e instanceof Float32Array&&(e=[e]),Az(e,this.sampling_rate)}async save(e){return dx(e,this.toBlob())}},kz=class extends zn{constructor(e){super(e);const t=this.config.sampling_rate,r=Er(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=os(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(e,t){return is(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e){qn(e,"ASTFeatureExtractor");const t=await this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){const r=this.std*2,s=t.data;for(let o=0;o0)if(r==="rand_trunc"){const u=Math.floor(W_.random()*(l+1));e=e.subarray(u,u+t),o=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${r}" not implemented`);else{if(l<0){let u=new Float64Array(t);if(u.set(e),s==="repeat")for(let d=e.length;dt&&(e=e.slice(0,t)),s&&e.length%o!==0){const d=o-e.length%o,f=new Float64Array(e.length+d);f.set(e),this.config.padding_value!==0&&f.fill(this.config.padding_value,e.length),e=f}const l=await this._extract_fbank_features(e,this.config.max_length),u=On([1,l.dims[0]],!0);return{input_features:l.unsqueeze_(0),input_features_mask:u}}},Fz=class extends zn{constructor(e){super(e);const{n_fft:t,win_length:r,n_mels:s,sample_rate:o}=e.melspec_kwargs;this.mel_filters=Er(Math.floor(1+t/2),s,0,o/2,o,null,"htk");const l=os(r,"hann");this.window=new Float64Array(t);const u=Math.floor((t-r)/2);this.window.set(l,u)}async _call(e){qn(e,"GraniteSpeechFeatureExtractor");const{n_fft:t,hop_length:r,n_mels:s}=this.config.melspec_kwargs,o=1+Math.floor((e.length-1)/r),l=o-o%2;return{input_features:(await is(e,this.window,t,r,{power:2,mel_filters:this.mel_filters,log_mel:"log10_max_norm",transpose:!0,max_num_frames:l,do_pad:!1})).view(-1,2*s).unsqueeze_(0)}}},Nz=class extends zn{async _call(e){qn(e,"MoonshineFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const t=[1,e.length];return{input_values:new me("float32",e,t)}}},Dz=1e-5,Rz=class extends zn{constructor(e){super(e),this.config.mel_filters??=Er(Math.floor(1+this.config.n_fft/2),this.config.feature_size,0,this.config.sampling_rate/2,this.config.sampling_rate,"slaney","slaney");const t=os(this.config.win_length,"hann",{periodic:!1});this.window=new Float64Array(this.config.n_fft);const r=Math.floor((this.config.n_fft-this.config.win_length)/2);this.window.set(t,r)}async _extract_fbank_features(e){const t=this.config.preemphasis;e=new Float64Array(e);for(let s=e.length-1;s>=1;--s)e[s]-=t*e[s-1];return await is(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){qn(e,"ParakeetFeatureExtractor");const t=await this._extract_fbank_features(e),r=Math.floor((e.length+Math.floor(this.config.n_fft/2)*2-this.config.n_fft)/this.config.hop_length),s=t.data;s.fill(0,r*t.dims[1]);const[o,l]=t.dims,u=new Float64Array(l),d=new Float64Array(l);for(let g=0;g1?r-1:1;for(let g=0;g({id:d,start:f*r,end:p*r,confidence:g/(p-f)})))}return s}},Bz=class extends zn{constructor(e){super(e);const t=this.config.sampling_rate,r=Er(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=os(400,"povey",{periodic:!1})}async _extract_fbank_features(e,t){return e=e.map(r=>r*32768),is(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:t,transpose:!0})}async _call(e,{padding:t=!0,pad_to_multiple_of:r=2,do_normalize_per_mel_bins:s=!0,return_attention_mask:o=!0}={}){qn(e,"SeamlessM4TFeatureExtractor");let l=await this._extract_fbank_features(e,this.config.max_length);if(s){const[b,S]=l.dims,E=l.data;for(let z=0;z0){const k=new Float32Array(S*(b+z));k.set(E),k.fill(this.config.padding_value,E.length);const L=b+z;l=new me(l.type,k,[L,S]),o&&(u=new me("int64",new BigInt64Array(L),[1,L]),u.data.fill(1n,0,b))}}const[d,f]=l.dims,p=this.config.stride;if(d%p!==0)throw new Error(`The number of frames (${d}) must be a multiple of the stride (${p}).`);const y=l.view(1,Math.floor(d/p),f*p),w={input_features:y};if(o){const b=y.dims[1],S=new BigInt64Array(b);if(u){const E=u.data;for(let z=1,k=0;zo+l,0)/e.length,s=e.reduce((o,l)=>o+(l-r)**2,0)/e.length;return e.map(o=>(o-r)/Math.sqrt(s+1e-7))}async _call(e){qn(e,"Wav2Vec2FeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));let t=e;this.config.do_normalize&&(t=this._zero_mean_unit_var_norm(t));const r=[1,t.length];return{input_values:new me("float32",t,r),attention_mask:new me("int64",new BigInt64Array(t.length).fill(1n),r)}}},Gz=class extends zn{constructor(e){super(e);const t=this.config.sampling_rate,r=Er(257,this.config.num_mel_bins,20,Math.floor(t/2),t,null,"kaldi",!0);this.mel_filters=r,this.window=os(400,"hamming",{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(e){return e=e.map(t=>t*32768),is(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,transpose:!0,min_num_frames:this.min_num_frames})}async _call(e){qn(e,"WeSpeakerFeatureExtractor");const t=(await this._extract_fbank_features(e)).unsqueeze_(0);if(this.config.fbank_centering_span===null){const r=t.mean(1).data,s=t.data,[o,l,u]=t.dims;for(let d=0;ds?(e.length>this.config.n_samples&&Re.warn("Attempting to extract features for audio longer than 30 seconds. 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Mr{constructor(t,r,s,o){this.data=t,this.width=r,this.height=s,this.channels=o}get size(){return[this.width,this.height]}static async read(t){if(t instanceof Mr)return t;if(typeof t=="string"||t instanceof URL)return await this.fromURL(t);if(t instanceof Blob)return await this.fromBlob(t);if(typeof HTMLCanvasElement<"u"&&t instanceof HTMLCanvasElement||typeof OffscreenCanvas<"u"&&t instanceof OffscreenCanvas)return this.fromCanvas(t);throw new Error(`Unsupported input type: ${typeof t}`)}static fromCanvas(t){if(!We.IS_WEB_ENV)throw new Error("fromCanvas() is only supported in browser environments.");const s=t.getContext("2d").getImageData(0,0,t.width,t.height).data;return new Mr(s,t.width,t.height,4)}static async fromURL(t){const r=await bu(t);if(r.status!==200)throw new Error(`Unable to read image from "${t}" (${r.status} ${r.statusText})`);const s=await r.blob();return this.fromBlob(s)}static async fromBlob(t){if(We.IS_WEB_ENV){const r=await Xs(t),s=ji(r.width,r.height).getContext("2d");return s.drawImage(r,0,0),new this(s.getImageData(0,0,r.width,r.height).data,r.width,r.height,4)}else{const r=g_(await t.arrayBuffer());return await Xs(r)}}static fromTensor(t,r="CHW"){if(t.dims.length!==3)throw new Error(`Tensor should have 3 dimensions, but has ${t.dims.length} dimensions.`);if(r==="CHW")t=t.transpose(1,2,0);else if(r!=="HWC")throw new Error(`Unsupported channel format: ${r}`);if(!(t.data instanceof Uint8ClampedArray||t.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${t.type}`);switch(t.dims[2]){case 1:case 2:case 3:case 4:return new Mr(t.data,t.dims[1],t.dims[0],t.dims[2]);default:throw new Error(`Unsupported number of channels: ${t.dims[2]}`)}}grayscale(){if(this.channels===1)return this;const t=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let r=0,s=0;r=0?f=s:g=-s,o>=0?p=o:y=-o,d.drawImage(u,f,p,t,r,g,y,t,r),new Mr(d.getImageData(0,0,t,r).data,t,r,4).convert(l)}else{let l=this.toSharp();if(s>=0&&o>=0)l=l.extract({left:Math.floor(s),top:Math.floor(o),width:t,height:r});else if(s<=0&&o<=0){const u=Math.floor(-o),d=Math.floor(-s);l=l.extend({top:u,left:d,right:t-this.width-d,bottom:r-this.height-u})}else{let u=[0,0],d=0;o<0?(u[0]=Math.floor(-o),u[1]=r-this.height-u[0]):d=Math.floor(o);let f=[0,0],p=0;s<0?(f[0]=Math.floor(-s),f[1]=t-this.width-f[0]):p=Math.floor(s),l=l.extend({top:u[0],bottom:u[1],left:f[0],right:f[1]}).extract({left:p,top:d,width:t,height:r})}return await Xs(l)}}async toBlob(t="image/png",r=1){if(!We.IS_WEB_ENV)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:t,quality:r})}toTensor(t="CHW"){let r=new me("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if(t!=="HWC")if(t==="CHW")r=r.permute(2,0,1);else throw new Error(`Unsupported channel format: ${t}`);return r}toCanvas(){if(!We.IS_WEB_ENV)throw new Error("toCanvas() is only supported in browser environments.");const t=this.clone().rgba(),r=ji(t.width,t.height),s=new gx(t.data,t.width,t.height);return r.getContext("2d").putImageData(s,0,0),r}split(){const{data:t,width:r,height:s,channels:o}=this,l=t.constructor,u=t.length/o,d=Array.from({length:o},()=>new l(u));for(let f=0;fnew Mr(f,r,s,1))}_update(t,r,s,o=null){return this.data=t,this.width=r,this.height=s,o!==null&&(this.channels=o),this}clone(){return new Mr(this.data.slice(),this.width,this.height,this.channels)}convert(t){if(this.channels===t)return this;switch(t){case 1:this.grayscale();break;case 3:this.rgb();break;case 4:this.rgba();break;default:throw new Error(`Conversion failed due to unsupported number of channels: ${this.channels}`)}return this}async save(t){if(We.IS_WEB_ENV){if(We.IS_WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const 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0);o.push({segmentation:g,labels:S})}return o}function Qz(e,t,r,s){const o=[],l=[],u=[];for(let d=0;dr&&(o.push(p),l.push(w),u.push(g))}return[o,l,u]}function Wz(e,t,r,s=.5,o=.8){const l=[];let u=0,d=0;const f=t[r].data;for(let g=0;g=s&&++d;let p=u>0&&d>0;return p&&(p=u/d>o),[p,l]}function Yz(e,t,r,s,o,l=null,u=null){const[d,f]=u??e[0].dims,p=new me("int32",new Int32Array(d*f),[d,f]),g=[];if(u!==null)for(let E=0;Ew[L]&&(y[L]=E,w[L]=k[L])}let b=0;const S=p.data;for(let E=0;E200)throw new Error(`absolute aspect ratio must be smaller than 200, got ${Math.max(e,t)/Math.min(e,t)}`);let l=Math.round(e/r)*r,u=Math.round(t/r)*r;if(l*u>o){const d=Math.sqrt(e*t/o);l=Math.floor(e/d/r)*r,u=Math.floor(t/d/r)*r}else if(l*uo?f=Math.floor(o*d/s):o>s&&(d=Math.floor(s*f/o)),await e.resize(f,d,{resample:r}))}async crop_margin(e,t=200){const r=e.clone().grayscale(),s=f_(r.data)[0],l=Ht(r.data)[0]-s;if(l===0)return e;const u=t/255;let d=r.width,f=r.height,p=0,g=0;const y=r.data;for(let w=0;wthis.preprocess(o)));return{pixel_values:Ji(r.map(o=>o.pixel_values),0),original_sizes:r.map(o=>o.original_size),reshaped_input_sizes:r.map(o=>o.reshaped_input_size)}}static async from_pretrained(e,t={}){const r=await ss(e,Mu,!0,t);return new this(r)}},Gf={};Al(Gf,{BeitFeatureExtractor:()=>Xz,BitImageProcessor:()=>Zz,CLIPFeatureExtractor:()=>Jz,CLIPImageProcessor:()=>xx,ChineseCLIPFeatureExtractor:()=>Kz,ConvNextFeatureExtractor:()=>eL,ConvNextImageProcessor:()=>Tx,DINOv3ViTImageProcessor:()=>aL,DPTFeatureExtractor:()=>sL,DPTImageProcessor:()=>Ax,DeiTFeatureExtractor:()=>tL,DeiTImageProcessor:()=>Sx,DetrFeatureExtractor:()=>nL,DetrImageProcessor:()=>Ex,DonutFeatureExtractor:()=>rL,DonutImageProcessor:()=>ng,EfficientNetImageProcessor:()=>iL,GLPNFeatureExtractor:()=>oL,GroundingDinoImageProcessor:()=>lL,Idefics3ImageProcessor:()=>i1,ImageFeatureExtractor:()=>Ve,ImageProcessor:()=>Ve,JinaCLIPImageProcessor:()=>uL,Lfm2VlImageProcessor:()=>mL,LlavaOnevisionImageProcessor:()=>_L,Mask2FormerImageProcessor:()=>yL,MaskFormerFeatureExtractor:()=>gL,MaskFormerImageProcessor:()=>ag,MobileNetV1FeatureExtractor:()=>vL,MobileNetV1ImageProcessor:()=>Cx,MobileNetV2FeatureExtractor:()=>wL,MobileNetV2ImageProcessor:()=>kx,MobileNetV3FeatureExtractor:()=>bL,MobileNetV3ImageProcessor:()=>Ox,MobileNetV4FeatureExtractor:()=>ML,MobileNetV4ImageProcessor:()=>zx,MobileViTFeatureExtractor:()=>xL,MobileViTImageProcessor:()=>Lx,NougatImageProcessor:()=>TL,OwlViTFeatureExtractor:()=>SL,OwlViTImageProcessor:()=>rg,Owlv2ImageProcessor:()=>EL,Phi3VImageProcessor:()=>CL,PixtralImageProcessor:()=>kL,PvtImageProcessor:()=>OL,Qwen2VLImageProcessor:()=>zL,RTDetrImageProcessor:()=>LL,Sam2ImageProcessor:()=>Jm,Sam3ImageProcessor:()=>Jm,SamImageProcessor:()=>Jm,SapiensFeatureExtractor:()=>FL,SapiensImageProcessor:()=>Fx,SegformerFeatureExtractor:()=>NL,SegformerImageProcessor:()=>Nx,SiglipImageProcessor:()=>DL,SmolVLMImageProcessor:()=>i1,Swin2SRImageProcessor:()=>RL,VLMImageProcessor:()=>cL,ViTFeatureExtractor:()=>BL,ViTImageProcessor:()=>Dx,VitMatteImageProcessor:()=>PL,VitPoseImageProcessor:()=>IL,YolosFeatureExtractor:()=>UL,YolosImageProcessor:()=>Rx});var Xz=class extends Ve{},Zz=class extends Ve{},Kz=class extends Ve{},xx=class extends Ve{},Jz=class extends xx{},Tx=class extends Ve{constructor(e){super(e),this.crop_pct=this.config.crop_pct??224/256}async resize(e){const t=this.size?.shortest_edge;if(t===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(t<384){const r=Math.floor(t/this.crop_pct),[s,o]=this.get_resize_output_image_size(e,{shortest_edge:r});e=await e.resize(s,o,{resample:this.resample}),e=await e.center_crop(t,t)}else e=await e.resize(t,t,{resample:this.resample});return e}},eL=class extends Tx{},Sx=class extends Ve{},tL=class extends Sx{},Ex=class extends Ve{async _call(e){const t=await super._call(e),r=[t.pixel_values.dims[0],64,64],s=On(r,1n);return{...t,pixel_mask:s}}post_process_object_detection(...e){return Jf(...e)}post_process_panoptic_segmentation(...e){return bx(...e)}post_process_instance_segmentation(...e){return Mx(...e)}},nL=class extends Ex{},aL=class extends Ve{},ng=class extends Ve{pad_image(e,t,r,s={}){const[o,l,u]=t;let d=this.image_mean;Array.isArray(this.image_mean)||(d=new Array(u).fill(d));let f=this.image_std;Array.isArray(f)||(f=new Array(u).fill(d));const p=d.map((g,y)=>-g/f[y]);return super.pad_image(e,t,r,{center:!0,constant_values:p,...s})}},rL=class extends ng{},Ax=class extends Ve{},sL=class extends Ax{},iL=class extends Ve{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(t=>t*t))}},oL=class extends Ve{},lL=class extends Ve{async _call(e){const t=await super._call(e),r=t.pixel_values.dims,s=ha([r[0],r[2],r[3]]);return{...t,pixel_mask:s}}},i1=class extends Ve{constructor(e){super(e),this.do_image_splitting=e.do_image_splitting??!0,this.max_image_size=e.max_image_size}get_resize_for_vision_encoder(e,t){let[r,s]=e.dims.slice(-2);const o=s/r;return s>=r?(s=Math.ceil(s/t)*t,r=Math.floor(s/o),r=Math.ceil(r/t)*t):(r=Math.ceil(r/t)*t,s=Math.floor(r*o),s=Math.ceil(s/t)*t),{height:r,width:s}}async _call(e,{do_image_splitting:t=null,return_row_col_info:r=!1}={}){let s;if(!Array.isArray(e))s=[[e]];else{if(e.length===0||!e[0])throw new Error("No images provided.");Array.isArray(e[0])?s=e:s=[e]}let o=[],l=[],u=[];const d=[],f=[];for(const z of s){let k=await Promise.all(z.map(N=>this.preprocess(N)));d.push(...k.map(N=>N.original_size)),f.push(...k.map(N=>N.reshaped_input_size)),k.forEach(N=>N.pixel_values.unsqueeze_(0));const{longest_edge:L}=this.max_image_size;let R;if(t??this.do_image_splitting){let N=new Array(k.length),B=new Array(k.length);R=await Promise.all(k.map(async(j,C)=>{const ue=this.get_resize_for_vision_encoder(j.pixel_values,L),oe=await Ya(j.pixel_values,{size:[ue.height,ue.width]}),{frames:he,num_splits_h:_e,num_splits_w:de}=await this.split_image(oe,this.max_image_size);return N[C]=_e,B[C]=de,zt(he,0)})),l.push(N),u.push(B)}else{const N=[L,L];R=await Promise.all(k.map(B=>Ya(B.pixel_values,{size:N}))),l.push(new Array(k.length).fill(0)),u.push(new Array(k.length).fill(0))}o.push(zt(R,0))}const p=o.length,[g,y,w,b]=o[0].dims;let S,E;if(p===1)S=o[0].unsqueeze_(0),E=On([p,g,w,b],!0);else{const z=Math.max(...o.map(R=>R.dims.at(0)));E=On([p,z,w,b],!0);const k=E.data,L=z*w*b;for(let R=0;Rr||u>s){d=Math.ceil(l/r),f=Math.ceil(u/s);const p=Math.ceil(l/d),g=Math.ceil(u/f);for(let b=0;bt*this.rescale_factor)}pad_image(e,t,r,s){return super.pad_image(e,t,r,{constant_values:this.constant_values,center:!0,...s})}},uL=class extends Ve{constructor(e){const{resize_mode:t,fill_color:r,interpolation:s,size:o,...l}=e,u=t==="squash"?{width:o,height:o}:t==="shortest"?{shortest_edge:o}:{longest_edge:o},d=s==="bicubic"?3:2;super({...l,size:u,resample:d,do_center_crop:!0,crop_size:o,do_normalize:!0})}};function o1(e,t){return Math.round(e/t)*t}function dL(e,t,r,s,o){let l=1/0,u=[1,1];const d=r*s;for(const f of t){const p=Math.abs(e-f[0]/f[1]);p.5*o*o*f[0]*f[1]&&(u=f)}return u}function fL(e,t){const r=[],s=new Set;for(let o=e;o<=t;++o)for(let l=1;l<=o;++l)for(let u=1;u<=o;++u){const d=l*u;if(d>=e&&d<=t){const f=l<<16|u;s.has(f)||(s.add(f),r.push([l,u]))}}return r.sort((o,l)=>o[0]*o[1]-l[0]*l[1])}function hL(e,t){const[r,s,o,l]=e.dims,u=Math.floor(o/t),d=Math.floor(l/t),f=t*t*s,p=e.data,g=new Float32Array(r*u*d*f),y=o*l;for(let w=0;wthis.max_image_tokens*(this.encoder_patch_size*this.downsample_factor)**2*this.max_pixels_tolerance}_get_grid_layout(e,t){const r=fL(this.min_tiles,this.max_tiles),[s,o]=dL(t/e,r,t,e,this.tile_size);return{grid_width:s,grid_height:o,target_width:this.tile_size*s,target_height:this.tile_size*o}}async _call(e,{return_row_col_info:t=null}={}){let r;Array.isArray(e)?Array.isArray(e[0])?r=e:r=[e]:r=[[e]];const s=[],o=[],l=[],u=[],d=[],f=[];for(const g of r){const y=await Promise.all(g.map(w=>this.preprocess(w,{do_pad:!1})));for(const{pixel_values:w}of y){const[,b,S]=w.dims,E=w.unsqueeze_(0),z=this.encoder_patch_size*this.downsample_factor,k=z**2,[L,R]=wx(Math.max(z,b),Math.max(z,S),z,this.min_image_tokens*k,this.max_image_tokens*k).map(oe=>Math.max(z,oe));let N,B=1,j=1;const C=this._is_image_too_large(b,S),ue=this.do_image_splitting&&!(this.min_tiles===1&&this.max_tiles===1);if(C&&ue){const{grid_width:oe,grid_height:he,target_width:_e,target_height:de}=this._get_grid_layout(b,S);B=he,j=oe;const re=await Ya(E,{size:[de,_e]});N=[];for(let W=0;W(p-this.image_mean[g])/this.image_std[g]);return super.pad_image(e,t,{width:d,height:u},{center:!0,constant_values:f,...s})}async _call(e,{num_crops:t=null}={}){if(this._num_crops=t??=this.config.num_crops,t<4||Km(t)%1!==0)throw new Error("num_crops must be a square number >= 4");Array.isArray(e)||(e=[e]);const r=e.length,s=await Promise.all(e.map(y=>this.preprocess(y))),o=s.map(y=>y.original_size),l=s.map(y=>y.reshaped_input_size),u=[];for(const{pixel_values:y}of s){y.unsqueeze_(0);const[w,b]=y.dims.slice(-2),S=await Ya(y,{size:[la,la],mode:"bicubic"});if(t>0){const E=[],z=Km(t),k=hl(b/z),L=hl(w/z);for(let N=0;Ny.map(w=>la*Zm(w/la))),p=new me("int64",f.flat(),[r,2]),g=f.map(([y,w])=>this.calc_num_image_tokens_from_image_size(w,y));return{pixel_values:d,original_sizes:o,reshaped_input_sizes:l,image_sizes:p,num_img_tokens:g}}},kL=class extends Ve{get_resize_output_image_size(e,t){const{longest_edge:r}=t;if(r===void 0)throw new Error("size must contain 'longest_edge'");const[s,o]=e.size,l=Math.max(s,o)/r;let u=s,d=o;l>1&&(u=Math.floor(s/l),d=Math.floor(o/l));const{patch_size:f,spatial_merge_size:p}=this.config;if(!p)throw new Error("config must contain 'spatial_merge_size'");const g=f*p,y=Math.floor((u-1)/g)+1,w=Math.floor((d-1)/g)+1;return[y*g,w*g]}},OL=class extends Ve{},zL=class extends Ve{constructor(e){super(e),this.min_pixels=e.min_pixels??e.size?.shortest_edge,this.max_pixels=e.max_pixels??e.size?.longest_edge,this.patch_size=e.patch_size,this.merge_size=e.merge_size}get_resize_output_image_size(e,t){const r=this.patch_size*this.merge_size;return wx(e.height,e.width,r,this.min_pixels,this.max_pixels)}async _call(e,...t){const{pixel_values:r,original_sizes:s,reshaped_input_sizes:o}=await super._call(e,...t);let l=r;const{temporal_patch_size:u,merge_size:d,patch_size:f}=this.config;l.dims[0]===1&&(l=zt(Array.from({length:u},()=>l),0));const p=l.dims[0]/u,g=l.dims[1],y=Math.floor(l.dims[2]/f),w=Math.floor(l.dims[3]/f),b=l.view(p,u,g,Math.floor(y/d),d,f,Math.floor(w/d),d,f).permute(0,3,6,4,7,2,1,5,8).view(p*y*w,g*u*f*f),S=new me("int64",[p,y,w],[1,3]);return{pixel_values:b,image_grid_thw:S,original_sizes:s,reshaped_input_sizes:o}}},LL=class extends Ve{post_process_object_detection(...e){return Jf(...e)}},Jm=class extends Ve{reshape_input_points(e,t,r,s=!1){e=structuredClone(e);let o=Sb(e);if(o.length===3)s||(o=[1,...o]),e=[e];else if(o.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 l=0;ls!==t.dims[o]))throw Error(`The first ${r.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new me("int64",e.flat(1/0).map(BigInt),r)}async _call(e,{input_points:t=null,input_labels:r=null,input_boxes:s=null}={}){const o=await super._call(e);if(t&&(o.input_points=this.reshape_input_points(t,o.original_sizes,o.reshaped_input_sizes)),r){if(!o.input_points)throw Error("`input_points` must be provided if `input_labels` are provided.");o.input_labels=this.add_input_labels(r,o.input_points)}return s&&(o.input_boxes=this.reshape_input_points(s,o.original_sizes,o.reshaped_input_sizes,!0)),o}async post_process_masks(e,t,r,{mask_threshold:s=0,binarize:o=!0,pad_size:l=null}={}){const u=[];l=l??this.pad_size??this.size;const d=[l.height,l.width];for(let f=0;fs&&(b[S]=1);y=new me("bool",b,y.dims)}u.push(y)}return u}generate_crop_boxes(e,t,{crop_n_layers:r=0,overlap_ratio:s=512/1500,points_per_crop:o=32,crop_n_points_downscale_factor:l=1}={}){}},Fx=class extends Ve{post_process_semantic_segmentation(...e){return vx(...e)}},FL=class extends Fx{},Nx=class extends Ve{post_process_semantic_segmentation(...e){return vx(...e)}},NL=class extends Nx{},DL=class extends Ve{},RL=class extends Ve{pad_image(e,t,r,s={}){const[o,l,u]=t;return super.pad_image(e,t,{width:l+(r-l%r)%r,height:o+(r-o%r)%r},{mode:"symmetric",center:!1,constant_values:-1,...s})}},Dx=class extends Ve{},BL=class extends Dx{},PL=class extends Ve{async _call(e,t){Array.isArray(e)||(e=[e]),Array.isArray(t)||(t=[t]);const r=await Promise.all(e.map(l=>this.preprocess(l))),s=await Promise.all(t.map(l=>this.preprocess(l,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:Ji(r.map((l,u)=>zt([l.pixel_values,s[u].pixel_values],0)),0),original_sizes:r.map(l=>l.original_size),reshaped_input_sizes:r.map(l=>l.reshaped_input_size)}}},IL=class extends Ve{post_process_pose_estimation(e,t,{threshold:r=null}={}){const s=e.tolist(),[o,l,u,d]=e.dims,f=[];for(let p=0;p/gm,bboxes:/([^<]+)?/gm},this.size_per_bin=1e3}construct_prompts(e){typeof e=="string"&&(e=[e]);const t=[];for(const r of e)if(this.task_prompts_without_inputs.has(r))t.push(this.task_prompts_without_inputs.get(r));else{for(const[s,o]of this.task_prompts_with_input)if(r.includes(s)){t.push(o.replaceAll("{input}",r).replaceAll(s,""));break}t.length!==e.length&&t.push(r)}return t}post_process_generation(e,t,r){const s=this.tasks_answer_post_processing_type.get(t)??"pure_text";e=e.replaceAll("","").replaceAll("","");let o;switch(s){case"pure_text":o=e;break;case"description_with_bboxes":case"bboxes":case"phrase_grounding":case"ocr":const l=s==="ocr"?"quad_boxes":"bboxes",u=e.matchAll(this.regexes[l]),d=[],f=[];for(const[p,g,...y]of u)d.push(g?g.trim():d.at(-1)??""),f.push(y.map((w,b)=>(Number(w)+.5)/this.size_per_bin*r[b%2]));o={labels:d,[l]:f};break;default:throw new Error(`Task "${t}" (of type "${s}") not yet implemented.`)}return{[t]:o}}async _call(e,t=null,r={}){if(!e&&!t)throw new Error("Either text or images must be provided");const s=await this.image_processor(e,r),o=t?this.tokenizer(this.construct_prompts(t),r):{};return{...s,...o}}},jL=class extends bt{static image_processor_class=Hn;static feature_extractor_class=er;static tokenizer_class=yt;static uses_processor_config=!0;static uses_chat_template_file=!0;constructor(e,t,r){super(e,t,r),this.audio_seq_length=this.config.audio_seq_length,this.image_seq_length=this.config.image_seq_length;const{audio_token_id:s,boa_token:o,audio_token:l,eoa_token:u,image_token_id:d,boi_token:f,image_token:p,eoi_token:g}=this.tokenizer.config;this.audio_token_id=s,this.boa_token=o,this.audio_token=l;const y=l.repeat(this.audio_seq_length);this.full_audio_sequence=` + +${o}${y}${u} + +`,this.image_token_id=d,this.boi_token=f,this.image_token=p;const w=p.repeat(this.image_seq_length);this.full_image_sequence=` + +${f}${w}${g} + +`}async _call(e,t=null,r=null,s={}){typeof e=="string"&&(e=[e]);let o;r&&(o=await this.feature_extractor(r,s),e=e.map(d=>d.replaceAll(this.audio_token,this.full_audio_sequence)));let l;return t&&(l=await this.image_processor(t,s),e=e.map(d=>d.replaceAll(this.image_token,this.full_image_sequence))),{...this.tokenizer(e,s),...l,...o}}},VL=class extends bt{static tokenizer_class=yt;static feature_extractor_class=er;static uses_processor_config=!0;_get_num_audio_features(e){const{hop_length:t}=this.feature_extractor.config.melspec_kwargs,{projector_window_size:r,projector_downsample_rate:s}=this.feature_extractor.config,o=Math.floor(r/s),l=Math.floor(e/t)+1,u=Math.floor(l/2);return Math.ceil(u/r)*o}async _call(e,t=null,r={}){if(Array.isArray(e))throw new Error("Batched inputs are not supported yet.");let s={};if(t){const{input_features:l}=await this.feature_extractor(t);s.input_features=l;const u=this._get_num_audio_features(t.length),d=new Uint8Array(u).fill(1);s.input_features_mask=new me("bool",d,[1,u]);const f=this.config.audio_token??"<|audio|>";if(!e.includes(f))throw new Error(`The input text does not contain the audio token ${f}.`);e=e.replaceAll(f,f.repeat(u))}return{...this.tokenizer(e,{add_special_tokens:!1,...r}),...s}}};function qL(e,t){const s=e.dims.at(-1)-1,o=e.tolist();o.fill(!1,0,1),o.fill(!1,s);const l=t.tolist();return o.map((u,d)=>u?d:null).filter(u=>u!==null).map(u=>l[u])}var HL=class extends bt{static tokenizer_class=yt;static image_processor_class=Hn;async _call(e,t,r={}){const s=e?await this.image_processor(e,r):{};return{...t?this.tokenizer(t,r):{},...s}}post_process_grounded_object_detection(e,t,{box_threshold:r=.25,text_threshold:s=.25,target_sizes:o=null}={}){const{logits:l,pred_boxes:u}=e,d=l.dims[0];if(o!==null&&o.length!==d)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const f=l.dims.at(1),p=l.sigmoid(),g=p.max(-1).tolist(),y=u.tolist().map(b=>b.map(S=>yx(S))),w=[];for(let b=0;bR.map((N,B)=>N*S[(B+1)%2])));const E=g[b],z=[],k=[],L=[];for(let R=0;R`+o.repeat(e);u+=` +`}return u+=` +${s}${l}`+o.repeat(e)+`${s}`,u}function QL(e,t,r,s){return`${t}${s}`+r.repeat(e)+`${t}`}function WL(e,t,r,s,o,l){return e===0&&t===0?QL(r,s,o,l):$L(r,e,t,s,o,l)}var l1=class extends bt{static image_processor_class=Hn;static tokenizer_class=yt;static uses_processor_config=!0;fake_image_token="";image_token="";global_img_token="";async _call(e,t=null,r={}){r.return_row_col_info??=!0;let s;t&&(s=await this.image_processor(t,r)),Array.isArray(e)||(e=[e]);const o=s.rows??[new Array(e.length).fill(0)],l=s.cols??[new Array(e.length).fill(0)],u=this.config.image_seq_len,d=[],f=[];for(let g=0;gWL(k,b[L],u,this.fake_image_token,this.image_token,this.global_img_token)),E=y.split(this.image_token);if(E.length===0)throw new Error("The image token should be present in the text.");let z=E[0];for(let k=0;kE.images).flatMap(E=>E.images).map(E=>Xa.read(E)));const s=this.tokenizer,o=s.apply_chat_template(e,{tokenize:!1,add_generation_prompt:!0,chat_template:r}),l=E=>s.encode(E,{add_special_tokens:!1}),u=o.split(this.image_tag),d=u.length-1;if(t.length!==d)throw new Error(`Number of images provided (${t.length}) does not match number of "${this.image_tag}" image tags 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t={embed_tokens:"embed_tokens",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};return e.is_encoder_decoder&&(t.model="encoder_model"),t},cache_sessions:{decoder_model_merged:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.AudioTextToText]:{can_generate:!0,forward:ZF,prepare_inputs:fu,sessions:()=>({embed_tokens:"embed_tokens",audio_encoder:"audio_encoder",decoder_model_merged:"decoder_model_merged"}),cache_sessions:{decoder_model_merged:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.ImageAudioTextToText]:{can_generate:!0,prepare_inputs:fu,sessions:()=>({embed_tokens:"embed_tokens",audio_encoder:"audio_encoder",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"}),optional_configs:{generation_config:"generation_config.json"}},[ve.Phi3V]:{can_generate:!0,prepare_inputs:fu,sessions:()=>({prepare_inputs_embeds:"prepare_inputs_embeds",model:"model",vision_encoder:"vision_encoder"}),cache_sessions:{model:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.MultiModality]:{can_generate:!0,sessions:()=>({prepare_inputs_embeds:"prepare_inputs_embeds",model:"language_model",lm_head:"lm_head",gen_head:"gen_head",gen_img_embeds:"gen_img_embeds",image_decode:"image_decode"}),cache_sessions:{model:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.AutoEncoder]:{can_generate:!1,forward:XF,sessions:()=>({encoder_model:"encoder_model",decoder_model:"decoder_model"})},[ve.Supertonic]:{sessions:()=>({text_encoder:"text_encoder",latent_denoiser:"latent_denoiser",voice_decoder:"voice_decoder"})},[ve.Chatterbox]:{can_generate:!0,forward:Js,sessions:()=>({embed_tokens:"embed_tokens",speech_encoder:"speech_encoder",model:"language_model",conditional_decoder:"conditional_decoder"}),cache_sessions:{model:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.MultimodalLanguageModelOnly]:{can_generate:!0,forward:f1,prepare_inputs:fu,sessions:()=>({embed_tokens:"embed_tokens",decoder_model_merged:"decoder_model_merged"}),cache_sessions:{decoder_model_merged:!0},optional_configs:{generation_config:"generation_config.json"}},[ve.VoxtralRealtime]:{can_generate:!0,prepare_inputs:yu,sessions:()=>({embed_tokens:"embed_tokens",audio_encoder:"audio_encoder",decoder_model_merged:"decoder_model_merged"}),cache_sessions:{decoder_model_merged:!0,audio_encoder:!0},optional_configs:{generation_config:"generation_config.json"}},default:{can_generate:!1,forward:Js,sessions:(e,t)=>({model:t.model_file_name??"model"})}};function YF(e,t,r={}){const s=vl[e]??vl.default;return{sessions:s.sessions(t,r),cache_sessions:s.cache_sessions,optional_configs:s.optional_configs}}var ns=new Map,sg=new Map,Tl=new Map,H=class extends Oa{main_input_name="input_ids";forward_params=["input_ids","attention_mask"];_return_dict_in_generate_keys=null;constructor(e,t,r){super(),this.config=e,this.sessions=t,this.configs=r;const s=Tl.get(this.constructor),o=ns.get(s),l=vl[o]??vl.default;this.can_generate=l.can_generate,this._forward=l.forward,this._prepare_inputs_for_generation=l.prepare_inputs,this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){const e=[];for(const t of Object.values(this.sessions))e.push(t.release?.());return await Promise.all(e)}static async from_pretrained(e,{progress_callback:t=null,config:r=null,cache_dir:s=null,local_files_only:o=!1,revision:l="main",model_file_name:u=null,subfolder:d="onnx",device:f=null,dtype:p=null,use_external_data_format:g=null,session_options:y={}}={}){const w={progress_callback:t,config:r,cache_dir:s,local_files_only:o,revision:l,model_file_name:u,subfolder:d,device:f,dtype:p,use_external_data_format:g,session_options:y},b=Tl.get(this),S=ns.get(b);r=w.config=await xu.from_pretrained(e,w);const E=vl[S]??vl.default;if(S===void 0){const R=b??r?.model_type;R!=="custom"&&Re.warn(`Model type for '${R}' not found, assuming encoder-only architecture. Please report this at ${Kf}.`)}const z=E.sessions(r,w),k=[CF(e,z,w,E.cache_sessions)];E.optional_configs&&k.push(JF(e,E.optional_configs,w));const L=await Promise.all(k);return new this(r,...L)}async _call(e){return await this.forward(e)}async forward(e){return await this._forward(this,e)}get generation_config(){return this.configs?.generation_config??null}_get_logits_processor(e,t,r=null){const s=new w_;if(e.repetition_penalty!==null&&e.repetition_penalty!==1&&s.push(new RF(e.repetition_penalty)),e.no_repeat_ngram_size!==null&&e.no_repeat_ngram_size>0&&s.push(new DF(e.no_repeat_ngram_size)),e.bad_words_ids!==null&&s.push(new IF(e.bad_words_ids,e.eos_token_id)),e.min_length!==null&&e.eos_token_id!==null&&e.min_length>0&&s.push(new BF(e.min_length,e.eos_token_id)),e.min_new_tokens!==null&&e.eos_token_id!==null&&e.min_new_tokens>0&&s.push(new PF(t,e.min_new_tokens,e.eos_token_id)),e.forced_bos_token_id!==null&&s.push(new LF(e.forced_bos_token_id)),e.forced_eos_token_id!==null&&s.push(new FF(e.max_length,e.forced_eos_token_id)),e.begin_suppress_tokens!==null){const o=t>1||e.forced_bos_token_id===null?t:t+1;s.push(new qx(e.begin_suppress_tokens,o))}return e.guidance_scale!==null&&e.guidance_scale>1&&s.push(new UF(e.guidance_scale)),e.temperature===0&&e.do_sample&&(Re.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&&s.push(new GF(e.temperature)),r!==null&&s.extend(r),s}_prepare_generation_config(e,t,r=Hx){const s={...this.config};for(const l of["decoder","generator","text_config"])l in s&&Object.assign(s,s[l]);const o=new r(s);return Object.assign(o,this.generation_config??{}),e&&Object.assign(o,e),t&&Object.assign(o,yn(t,Object.getOwnPropertyNames(o))),o}_get_stopping_criteria(e,t=null){const r=new $x;return e.max_length!==null&&r.push(new jF(e.max_length,this.config.max_position_embeddings??null)),e.eos_token_id!==null&&r.push(new VF(e.eos_token_id)),t&&r.extend(t),r}_validate_model_class(){if(!this.can_generate){const e=[yl.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,yl.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,yl.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,yl.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES].filter(Boolean),t=Tl.get(this.constructor),r=new Set,s=this.config.model_type;for(const l of e){const u=l?.get(s);u&&r.add(u)}let o=`The current model class (${t}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw r.size>0&&(o+=` Please use the following class instead: ${[...r].join(", ")}`),Error(o)}}prepare_inputs_for_generation(...e){if(!this._prepare_inputs_for_generation)throw new Error("prepare_inputs_for_generation is not implemented for this model.");return this._prepare_inputs_for_generation(this,...e)}_update_model_kwargs_for_generation({generated_input_ids:e,outputs:t,model_inputs:r,is_encoder_decoder:s}){return r.past_key_values=this.getPastKeyValues(t,r.past_key_values),r.input_ids=new me("int64",e.flat(),[e.length,1]),s||(r.attention_mask=zt([r.attention_mask,ha([r.attention_mask.dims[0],1])],1)),r.position_ids=null,r}_prepare_model_inputs({inputs:e,bos_token_id:t,model_kwargs:r}){const s=yn(r,this.forward_params),o=this.main_input_name;if(o in s){if(e)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else s[o]=e;return{inputs_tensor:s[o],model_inputs:s,model_input_name:o}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:e,model_inputs:t,model_input_name:r,generation_config:s}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!t.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:l,pixel_values:u,attention_mask:d,...f}=t,p=await this._prepare_inputs_embeds(t);t={...f,...yn(p,["inputs_embeds","attention_mask"])}}let{last_hidden_state:o}=await Js(this,t);if(s.guidance_scale!==null&&s.guidance_scale>1)o=zt([o,m_(o,0)],0),"attention_mask"in t&&(t.attention_mask=zt([t.attention_mask,rx(t.attention_mask)],0));else if(t.decoder_input_ids){const l=b_(t.decoder_input_ids).dims[0];if(l!==o.dims[0]){if(o.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${o.dims[0]}) than the decoder inputs (${l}).`);o=zt(Array.from({length:l},()=>o),0)}}return t.encoder_outputs=o,t}_prepare_decoder_input_ids_for_generation({batch_size:e,model_input_name:t,model_kwargs:r,decoder_start_token_id:s,bos_token_id:o,generation_config:l}){let{decoder_input_ids:u,...d}=r;if(!(u instanceof me)){if(u)Array.isArray(u[0])||(u=Array.from({length:e},()=>u));else if(s??=o,this.config.model_type==="musicgen")u=Array.from({length:e*this.config.decoder.num_codebooks},()=>[s]);else if(Array.isArray(s)){if(s.length!==e)throw new Error(`\`decoder_start_token_id\` expcted to have length ${e} but got ${s.length}`);u=s}else u=Array.from({length:e},()=>[s]);u=b_(u)}return r.decoder_attention_mask=nx(u),{input_ids:u,model_inputs:d}}async generate({inputs:e=null,generation_config:t=null,logits_processor:r=null,stopping_criteria:s=null,streamer:o=null,...l}){this._validate_model_class(),t=this._prepare_generation_config(t,l);let{inputs_tensor:u,model_inputs:d,model_input_name:f}=this._prepare_model_inputs({inputs:e,model_kwargs:l});const p=this.config.is_encoder_decoder;p&&("encoder_outputs"in d||(d=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:u,model_inputs:d,model_input_name:f,generation_config:t})));let g;p?{input_ids:g,model_inputs:d}=this._prepare_decoder_input_ids_for_generation({batch_size:d[f].dims.at(0),model_input_name:f,model_kwargs:d,decoder_start_token_id:t.decoder_start_token_id,bos_token_id:t.bos_token_id,generation_config:t}):g=d[f];let y=g.dims.at(-1);t.max_new_tokens!==null&&(t.max_length=y+t.max_new_tokens);const w=this._get_logits_processor(t,y,r),b=this._get_stopping_criteria(t,s),S=d[f].dims.at(0),E=nh.getSampler(t),z=new Array(S).fill(0),k=g.tolist();o&&o.put(k);let L,R={},N={};for(;;){if(d=this.prepare_inputs_for_generation(k,d,t),L=await this.forward(d),t.return_dict_in_generate)if(t.output_attentions){const _e=this.getAttentions(L);for(const de in _e)de in R||(R[de]=[]),R[de].push(_e[de])}else this._return_dict_in_generate_keys&&Object.assign(N,yn(L,this._return_dict_in_generate_keys));const C=L.logits.slice(null,-1,null).to("float32"),ue=w(k,C),oe=[];for(let _e=0;_e_e))break;d=this._update_model_kwargs_for_generation({generated_input_ids:oe,outputs:L,model_inputs:d,is_encoder_decoder:p})}o&&o.end();const B=this.getPastKeyValues(L,d.past_key_values,!0),j=new me("int64",k.flat(),[k.length,k[0].length]);if(t.return_dict_in_generate)return{sequences:j,past_key_values:B,...R,...N};for(const C of Object.values(L))C.location==="gpu-buffer"&&C.dispose();return j}getPastKeyValues(e,t,r=!1){const s=Object.create(null);for(const o in e)if(o.startsWith("present")){const l=o.replace("present_ssm","past_ssm").replace("present_conv","past_conv").replace("present_recurrent","past_recurrent").replace("present","past_key_values"),u=o.includes("encoder");if(u&&t?s[l]=t[l]:s[l]=e[o],t&&(!u||r)){const d=t[l];d.location==="gpu-buffer"&&d.dispose()}}return new Wx(s)}getAttentions(e){const t={};for(const r of["cross_attentions","encoder_attentions","decoder_attentions"])for(const s in e)s.startsWith(r)&&(r in t||(t[r]=[]),t[r].push(e[s]));return t}addPastKeyValues(e,t){if(t)Object.assign(e,t);else{const r=this.sessions.decoder_model_merged??this.sessions.model,s=(e[this.main_input_name]??e.attention_mask)?.dims?.[0]??1,o=r?.config?.kv_cache_dtype??"float32",l=o==="float16"?Sl.float16:Sl.float32,u=eh(this.config,{batch_size:s});for(const d in u){const f=u[d].reduce((p,g)=>p*g,1);e[d]=new me(o,new l(f),u[d])}}}async _encode_input(e,t,r){if(!Object.hasOwn(this.sessions,e))throw new Error(`Model does not have a ${e} session.`);const s=this.sessions[e];return(await st(s,yn(t,s.inputNames)))[r]}async encode_image(e){return this._encode_input("vision_encoder",e,"image_features")}async encode_text(e){return this._encode_input("embed_tokens",e,"inputs_embeds")}async encode_audio(e){return this._encode_input("audio_encoder",e,"audio_features")}};async function Tf(e,t){let{encoder_outputs:r,input_ids:s,decoder_input_ids:o,...l}=t;if(!r){const u=yn(t,e.sessions.model.inputNames);r=(await Js(e,u)).last_hidden_state}return l.input_ids=o,l.encoder_hidden_states=r,e.sessions.decoder_model_merged.inputNames.includes("encoder_attention_mask")&&(l.encoder_attention_mask=t.attention_mask),await as(e,l,!0)}async function Js(e,t){const r=e.sessions.model,s=yn(t,r.inputNames);if(r.inputNames.includes("inputs_embeds")&&!s.inputs_embeds){if(!t.input_ids)throw new Error("Both `input_ids` and `inputs_embeds` are missing in the model inputs.");s.inputs_embeds=await e.encode_text({input_ids:t.input_ids})}if(r.inputNames.includes("token_type_ids")&&!s.token_type_ids){if(!s.input_ids)throw new Error("Both `input_ids` and `token_type_ids` are missing in the model inputs.");s.token_type_ids=rx(s.input_ids)}if(r.inputNames.includes("pixel_mask")&&!s.pixel_mask){if(!s.pixel_values)throw new Error("Both `pixel_values` and `pixel_mask` are missing in the model inputs.");const o=s.pixel_values.dims;s.pixel_mask=ha([o[0],o[2],o[3]])}return await st(r,s)}async function XF(e,t){const r=await e.encode(t);return await e.decode(r)}async function as(e,t,r=!1){const s=e.sessions[r?"decoder_model_merged":"model"],{past_key_values:o,...l}=t;if(s.inputNames.includes("use_cache_branch")&&(l.use_cache_branch=Yx(!!o)),s.inputNames.includes("position_ids")&&l.attention_mask&&!l.position_ids){const d=["paligemma","gemma3_text","gemma3"].includes(e.config.model_type)?1:0;l.position_ids=KF(l,o,d)}s.inputNames.includes("num_logits_to_keep")&&!l.num_logits_to_keep&&(l.num_logits_to_keep=new me("int64",[0n],[])),e.addPastKeyValues(l,o);const u=yn(l,s.inputNames);return await st(s,u)}async function Xx(e,{encode_function:t,merge_function:r,modality_input_names:s,modality_output_name:o,input_ids:l=null,attention_mask:u=null,position_ids:d=null,inputs_embeds:f=null,past_key_values:p=null,generation_config:g=null,logits_processor:y=null,...w}){if(!f){f=await e.encode_text({input_ids:l,...w});const S=yn(w,s);if(Object.keys(S).length>0){if(l.dims[1]!==1){const E=await t({...S,...w});({inputs_embeds:f,attention_mask:u}=r({[o]:E,inputs_embeds:f,input_ids:l,attention_mask:u}))}else if(p&&l.dims[1]===1){const E=l.dims[1],z=p.get_seq_length();u=zt([ha([l.dims[0],z]),u.slice(null,[u.dims[1]-E,u.dims[1]])],1)}}}if(!d&&["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"].includes(e.config.model_type)){const{image_grid_thw:S,video_grid_thw:E}=w;[d]=e.get_rope_index(l,S,E,u)}return await as(e,{inputs_embeds:f,past_key_values:p,attention_mask:u,position_ids:d,generation_config:g,logits_processor:y},!0)}async function ZF(e,t){return await Xx(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 f1(e,t){return await Xx(e,{...t,modality_input_names:["pixel_values"],modality_output_name:"image_features",encode_function:e.encode_image.bind(e),merge_function:e._merge_input_ids_with_image_features.bind(e)})}function Zx(e,t=0){const[r,s]=e.dims,o=e.data,l=new BigInt64Array(o.length);for(let u=0;uu.dims[1]||o[o.at(-1)])),{...r,decoder_input_ids:b_(t)}}function fu(e,...t){return e.config.is_encoder_decoder?jf(e,...t):yu(e,...t)}function Kx({modality_token_id:e,inputs_embeds:t,modality_features:r,input_ids:s,attention_mask:o}){const l=s.tolist().map(p=>p.reduce((g,y,w)=>(y==e&&g.push(w),g),[])),u=l.reduce((p,g)=>p+g.length,0),d=r.dims[0];if(u!==d)throw new Error(`Number of tokens and features do not match: tokens: ${u}, features ${d}`);let f=0;for(let p=0;p{const o=await ss(e,t[s],!1,r);return[s,o]})))}var 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del:()=>Jy,TableTransformerForObjectDetection:()=>h8,TableTransformerModel:()=>f8,TableTransformerObjectDetectionOutput:()=>nT,TableTransformerPreTrainedModel:()=>ev,TrOCRForCausalLM:()=>p8,TrOCRPreTrainedModel:()=>aT,UltravoxModel:()=>Yg,UltravoxPreTrainedModel:()=>w2,UniSpeechForCTC:()=>_8,UniSpeechForSequenceClassification:()=>g8,UniSpeechModel:()=>m8,UniSpeechPreTrainedModel:()=>yh,UniSpeechSatForAudioFrameClassification:()=>b8,UniSpeechSatForCTC:()=>v8,UniSpeechSatForSequenceClassification:()=>w8,UniSpeechSatModel:()=>y8,UniSpeechSatPreTrainedModel:()=>Nu,VaultGemmaForCausalLM:()=>x8,VaultGemmaModel:()=>M8,VaultGemmaPreTrainedModel:()=>tv,ViTForImageClassification:()=>E8,ViTMAEModel:()=>A8,ViTMAEPreTrainedModel:()=>rT,ViTMSNForImageClassification:()=>k8,ViTMSNModel:()=>C8,ViTMSNPreTrainedModel:()=>av,ViTModel:()=>S8,ViTPreTrainedModel:()=>nv,VisionEncoderDecoderModel:()=>T8,VitMatteForImageMatting:()=>O8,VitMattePreTrainedModel:()=>sT,VitPoseForPoseEstimation:()=>z8,VitPosePreTrainedModel:()=>iT,VitsModel:()=>L8,VitsModelOutput:()=>oT,VitsPreTrainedModel:()=>lT,VoxtralForConditionalGeneration:()=>F8,VoxtralRealtimeForConditionalGeneration:()=>uT,VoxtralRealtimePreTrainedModel:()=>cT,Wav2Vec2BertForCTC:()=>G8,Wav2Vec2BertForSequenceClassification:()=>j8,Wav2Vec2BertModel:()=>U8,Wav2Vec2BertPreTrainedModel:()=>vh,Wav2Vec2ForAudioFrameClassification:()=>qD,Wav2Vec2ForCTC:()=>jD,Wav2Vec2ForSequenceClassification:()=>VD,Wav2Vec2Model:()=>GD,Wav2Vec2PreTrainedModel:()=>ei,WavLMForAudioFrameClassification:()=>Q8,WavLMForCTC:()=>q8,WavLMForSequenceClassification:()=>H8,WavLMForXVector:()=>$8,WavLMModel:()=>V8,WavLMPreTrainedModel:()=>jl,WeSpeakerResNetModel:()=>W8,WeSpeakerResNetPreTrainedModel:()=>fT,WhisperForConditionalGeneration:()=>hT,WhisperModel:()=>X8,WhisperPreTrainedModel:()=>rv,XLMForQuestionAnswering:()=>nP,XLMForSequenceClassification:()=>eP,XLMForTokenClassification:()=>tP,XLMModel:()=>K8,XLMPreTrainedModel:()=>Vl,XLMRobertaForMaskedLM:()=>rP,XLMRobertaForQuestionAnswering:()=>oP,XLMRobertaForSequenceClassification:()=>sP,XLMRobertaForTokenClassification:()=>iP,XLMRobertaModel:()=>aP,XLMRobertaPreTrainedModel:()=>ql,XLMWithLMHeadModel:()=>J8,XVectorOutput:()=>dT,YolosForObjectDetection:()=>cP,YolosModel:()=>lP,YolosObjectDetectionOutput:()=>pT,YolosPreTrainedModel:()=>sv,YoutuForCausalLM:()=>dP,YoutuModel:()=>uP,YoutuPreTrainedModel:()=>iv});var Au=class extends H{},eN=class extends Au{},tN=class extends Au{async _call(e){return new Ne(await super._call(e))}},nN=class extends Au{async _call(e){return new Ln(await super._call(e))}},aN=class extends Au{async _call(e){return new dn(await super._call(e))}},lg=class extends H{},rN=class extends lg{},sN=class extends lg{},cg=class extends H{},iN=class extends cg{},oN=class extends cg{},ug=class extends H{},lN=class extends ug{},cN=class extends ug{},dg=class extends H{},uN=class extends dg{},dN=class extends dg{},ah=class extends H{},fN=class extends ah{},hN=class extends ah{},pN=class extends ah{async _call(e){return new Ne(await super._call(e))}},fg=class extends H{},mN=class extends fg{},_N=class extends fg{async _call(e){return new Ne(await super._call(e))}},zl=class extends H{},gN=class extends zl{},yN=class extends zl{async _call(e){return new dn(await super._call(e))}},vN=class extends zl{async _call(e){return new Ne(await super._call(e))}},wN=class extends zl{async _call(e){return new nn(await super._call(e))}},bN=class extends zl{async _call(e){return new Ln(await super._call(e))}},hg=class extends H{},MN=class extends hg{},xN=class extends hg{},pg=class extends H{},TN=class extends pg{},SN=class extends pg{},mg=class extends H{},EN=class extends mg{},AN=class extends mg{},Ll=class extends H{},CN=class extends Ll{},kN=class extends Ll{async _call(e){return new dn(await super._call(e))}},ON=class extends Ll{async _call(e){return new Ne(await super._call(e))}},zN=class extends Ll{async _call(e){return new nn(await super._call(e))}},LN=class extends Ll{async _call(e){return new Ln(await super._call(e))}},FN=4299n,h1=6561n,e2=class extends H{forward_params=["input_ids","inputs_embeds","attention_mask","position_ids","audio_values","exaggeration","audio_features","audio_tokens","speaker_embeddings","speaker_features","past_key_values"];main_input_name="input_ids";_return_dict_in_generate_keys=["audio_tokens","speaker_embeddings","speaker_features"]},t2=class extends e2{async encode_speech(e){return st(this.sessions.speech_encoder,{audio_values:e})}async forward({input_ids:e=null,attention_mask:t=null,audio_values:r=null,exaggeration:s=null,position_ids:o=null,inputs_embeds:l=null,past_key_values:u=null,generation_config:d=null,logits_processor:f=null,audio_features:p=null,audio_tokens:g=null,speaker_embeddings:y=null,speaker_features:w=null,...b}){let S;if(!l){const z=this.sessions.embed_tokens.inputNames,k={input_ids:e};if(z.includes("exaggeration")){if(!(s instanceof me)){const L=e.dims[0];if(s==null)s=On([L],.5);else if(typeof s=="number")s=On([L],s);else if(Array.isArray(s))s=new me("float32",s,[L]);else throw new Error("Unsupported type for `exaggeration` input")}k.exaggeration=s}if(z.includes("position_ids")&&(k.position_ids=o),{inputs_embeds:l}=await st(this.sessions.embed_tokens,k),p&&g&&y&&w&&(S={audio_features:p,audio_tokens:g,speaker_embeddings:y,speaker_features:w}),S||r)S??=await this.encode_speech(r),l=zt([S.audio_features,l],1),t=ha([l.dims[0],l.dims[1]]);else{const L=l.dims[1];if(!u||L!==1)throw new Error("Incorrect state encountered during generation.");const R=u.get_seq_length();t=ha([l.dims[0],R+L])}}return{...await as(this,{inputs_embeds:l,past_key_values:u,attention_mask:t,generation_config:d,logits_processor:f},!1),...S}}prepare_inputs_for_generation(e,t,r){if(!t.position_ids&&this.sessions.embed_tokens.inputNames.includes("position_ids"))if(t.input_ids.dims[1]===1){const s=Array.from({length:e.length},(o,l)=>e[l].length-e[l].findLastIndex(u=>u==h1)-1);t.position_ids=new me("int64",s,[e.length,1])}else{const o=t.input_ids.tolist().map(l=>{let u=0;return l.map(d=>d>=h1?0:u++)});t.position_ids=new me("int64",o.flat(),t.input_ids.dims)}return t.input_ids.dims[1]===1&&(delete t.audio_values,delete t.audio_features,delete t.audio_tokens,delete t.speaker_embeddings,delete t.speaker_features),yu(this,e,t)}async generate(e){const{sequences:t,audio_tokens:r,speaker_embeddings:s,speaker_features:o}=await super.generate({...e,return_dict_in_generate:!0}),l=t.slice(null,[e.input_ids.dims[1],-1]),u=On([l.dims[0],3],FN),d=zt([r,l,u],1),{waveform:f}=await st(this.sessions.conditional_decoder,{speech_tokens:d,speaker_features:o,speaker_embeddings:s});return f}},n2=class extends H{},NN=class extends n2{},rh=class extends H{},DN=class extends rh{},a2=class extends rh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},r2=class extends rh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"audio_model"})}},to=class extends H{},RN=class extends to{},BN=class extends to{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},s2=class extends to{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},PN=class extends to{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},IN=class extends to{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},_g=class extends H{},UN=class extends _g{},GN=class extends _g{},gg=class extends H{},jN=class extends gg{},VN=class extends gg{},yg=class extends H{},qN=class extends yg{},HN=class extends yg{},vg=class extends H{},$N=class extends vg{},QN=class extends vg{},Fl=class extends H{},WN=class extends Fl{},YN=class extends Fl{async _call(e){return new dn(await super._call(e))}},XN=class 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H{main_input_name="input_values";forward_params=["input_values"]},o4=class extends sh{async encode(e){return new i2(await st(this.sessions.encoder_model,e))}async decode(e){return new o2(await st(this.sessions.decoder_model,e))}},l2=class extends sh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},c2=class extends sh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},Nl=class extends H{},l4=class extends Nl{},c4=class extends Nl{async _call(e){return new dn(await super._call(e))}},u4=class extends Nl{async _call(e){return new Ne(await super._call(e))}},d4=class extends Nl{async _call(e){return new nn(await super._call(e))}},f4=class extends Nl{async _call(e){return new Ln(await super._call(e))}},Dl=class extends H{},h4=class extends Dl{},p4=class extends Dl{async _call(e){return new dn(await super._call(e))}},m4=class extends Dl{async _call(e){return new Ne(await super._call(e))}},_4=class extends Dl{async _call(e){return new nn(await super._call(e))}},g4=class extends Dl{async _call(e){return new Ln(await super._call(e))}},u2=class extends H{},y4=class extends u2{},Tg=class extends H{},v4=class extends Tg{},w4=class extends Tg{async _call(e){return new Ne(await super._call(e))}},d2=class extends H{},b4=class extends d2{},f2=class extends H{},M4=class extends f2{},ih=class extends H{},x4=class extends ih{},T4=class extends ih{async _call(e){return new Sg(await super._call(e))}},S4=class extends ih{async _call(e){return new h2(await super._call(e))}},Sg=class extends tn{constructor({logits:e,pred_boxes:t}){super(),this.logits=e,this.pred_boxes=t}},h2=class extends tn{constructor({logits:e,pred_boxes:t,pred_masks:r}){super(),this.logits=e,this.pred_boxes=t,this.pred_masks=r}},Eg=class extends H{},E4=class extends Eg{},A4=class extends Eg{async _call(e){return new Ne(await super._call(e))}},Ag=class extends H{},C4=class extends Ag{},k4=class extends Ag{async _call(e){return new Ne(await super._call(e))}},p2=class extends H{},O4=class extends p2{},m2=class extends H{},z4=class extends m2{},Rl=class extends H{},L4=class extends Rl{},F4=class extends Rl{async _call(e){return new Ne(await super._call(e))}},N4=class extends Rl{async _call(e){return new nn(await super._call(e))}},D4=class extends Rl{async _call(e){return new Ln(await super._call(e))}},R4=class extends Rl{async _call(e){return new dn(await super._call(e))}},_2=class extends H{},B4=class extends _2{},Cg=class extends H{},P4=class extends Cg{},I4=class extends Cg{},kg=class extends H{},U4=class extends kg{},G4=class extends kg{async _call(e){return new Ne(await super._call(e))}},Bl=class extends H{},j4=class extends Bl{},V4=class extends Bl{async _call(e){return new dn(await super._call(e))}},q4=class extends Bl{async _call(e){return new Ne(await super._call(e))}},H4=class extends Bl{async _call(e){return new nn(await super._call(e))}},$4=class extends Bl{async _call(e){return new Ln(await super._call(e))}},Og=class extends H{},Q4=class extends Og{},W4=class extends Og{},ku=class extends H{},Y4=class extends ku{},X4=class extends ku{async _call(e){return new dn(await super._call(e))}},Z4=class extends ku{async _call(e){return new Ne(await super._call(e))}},K4=class extends ku{async _call(e){return new nn(await super._call(e))}},zg=class extends H{},J4=class extends zg{},eD=class extends zg{},Lg=class extends H{},tD=class extends Lg{},nD=class extends Lg{},Fg=class extends H{},aD=class extends Fg{},rD=class extends Fg{},Ng=class extends H{},sD=class extends Ng{},iD=class extends Ng{async _call(e){return new Ne(await super._call(e))}},g2=class extends H{forward_params=["input_ids","inputs_embeds","attention_mask","pixel_values","encoder_outputs","decoder_input_ids","decoder_inputs_embeds","decoder_attention_mask","past_key_values"];main_input_name="inputs_embeds"},oD=class extends g2{_merge_input_ids_with_image_features({inputs_embeds:e,image_features:t,input_ids:r,attention_mask:s}){return{inputs_embeds:zt([t,e],1),attention_mask:zt([ha(t.dims.slice(0,2)),s],1)}}async _prepare_inputs_embeds({input_ids:e,pixel_values:t,inputs_embeds:r,attention_mask:s}){if(!e&&!t)throw new Error("Either `input_ids` or `pixel_values` should be provided.");let o,l;return e&&(o=await this.encode_text({input_ids:e})),t&&(l=await this.encode_image({pixel_values:t})),o&&l?{inputs_embeds:r,attention_mask:s}=this._merge_input_ids_with_image_features({inputs_embeds:o,image_features:l,input_ids:e,attention_mask:s}):r=o||l,{inputs_embeds:r,attention_mask:s}}async forward({input_ids:e,pixel_values:t,attention_mask:r,decoder_input_ids:s,decoder_attention_mask:o,encoder_outputs:l,past_key_values:u,inputs_embeds:d,decoder_inputs_embeds:f}){if(d||({inputs_embeds:d,attention_mask:r}=await this._prepare_inputs_embeds({input_ids:e,pixel_values:t,inputs_embeds:d,attention_mask:r})),!l){let{last_hidden_state:g}=await Js(this,{inputs_embeds:d,attention_mask:r});l=g}if(!f){if(!s)throw new Error("Either `decoder_input_ids` or `decoder_inputs_embeds` should be provided.");f=await this.encode_text({input_ids:s})}return await as(this,{inputs_embeds:f,attention_mask:o,encoder_attention_mask:r,encoder_hidden_states:l,past_key_values:u},!0)}},Dg=class extends H{},lD=class extends Dg{},cD=class extends Dg{},Rg=class extends H{},uD=class extends Rg{},dD=class extends Rg{},Bg=class extends H{},fD=class extends Bg{},hD=class extends Bg{},y2=class extends H{forward_params=["input_ids","attention_mask","inputs_embeds","per_layer_inputs","position_ids","pixel_values","input_features","input_features_mask","past_key_values"]},Pg=class extends y2{async forward({input_ids:e=null,attention_mask:t=null,pixel_values:r=null,input_features:s=null,input_features_mask:o=null,position_ids:l=null,inputs_embeds:u=null,per_layer_inputs:d=null,past_key_values:f=null,generation_config:p=null,logits_processor:g=null,...y}){if((!u||!d)&&({inputs_embeds:u,per_layer_inputs:d}=await st(this.sessions.embed_tokens,{input_ids:e}),e.dims[1]!==1)){if(r){const{image_features:b}=await st(this.sessions.vision_encoder,{pixel_values:r});({inputs_embeds:u,attention_mask:t}=this._merge_input_ids_with_image_features({image_features:b,inputs_embeds:u,input_ids:e,attention_mask:t}))}if(s){const{audio_features:b}=await st(this.sessions.audio_encoder,{input_features:s,input_features_mask:o});({inputs_embeds:u,attention_mask:t}=this._merge_input_ids_with_audio_features({audio_features:b,inputs_embeds:u,input_ids:e,attention_mask:t}))}}return await as(this,{inputs_embeds:u,per_layer_inputs:d,past_key_values:f,attention_mask:t,position_ids:l,generation_config:p,logits_processor:g},!0)}_merge_input_ids_with_image_features(e){const t=e.image_features.dims.at(-1),r=e.image_features.view(-1,t);return ig({image_token_id:this.config.image_token_id,...e,image_features:r})}_merge_input_ids_with_audio_features(e){const t=e.audio_features.dims.at(-1),r=e.audio_features.view(-1,t);return Jx({audio_token_id:this.config.audio_token_id,...e,audio_features:r})}},v2=class extends Pg{},Ig=class extends H{},pD=class extends Ig{},mD=class extends Ig{},Ug=class extends H{},_D=class extends Ug{},gD=class extends Ug{},Gg=class extends H{},yD=class extends Gg{},vD=class extends Gg{},jg=class extends H{},wD=class extends jg{},bD=class extends jg{},Vg=class extends H{},MD=class extends Vg{},xD=class extends Vg{},qg=class extends H{},TD=class extends qg{},SD=class extends qg{},Hg=class extends H{},ED=class extends Hg{},AD=class extends Hg{},$g=class extends H{},CD=class extends $g{},kD=class extends $g{},Qg=class extends H{},OD=class extends Qg{},zD=class extends Qg{},Wg=class extends H{},LD=class extends Wg{},FD=class extends Wg{},w2=class extends H{forward_params=["input_ids","attention_mask","position_ids","audio_values","past_key_values"]},Yg=class extends w2{_merge_input_ids_with_audio_features(e){const t=e.audio_features.dims.at(-1),r=e.audio_features.view(-1,t);return Jx({audio_token_id:this.config.ignore_index??this.config.audio_token_id??this.config.audio_token_index,...e,audio_features:r})}},ND=class extends Yg{forward_params=["input_ids","attention_mask","input_features","past_key_values"]},b2=class extends H{},DD=class extends b2{},M2=class extends H{},RD=class extends M2{},Xg=class extends H{},BD=class extends Xg{},PD=class extends Xg{},Zg=class extends H{},ID=class extends Zg{},UD=class extends Zg{async _call(e){return new Ne(await super._call(e))}},ei=class extends H{},GD=class extends ei{},jD=class extends ei{async _call(e){return new eo(await super._call(e))}},VD=class extends ei{async _call(e){return new Ne(await super._call(e))}},qD=class extends ei{async _call(e){return new nn(await super._call(e))}},HD=class extends H{},$D=class extends ei{},QD=class extends ei{async _call(e){return new eo(await super._call(e))}},WD=class extends ei{async _call(e){return new Ne(await super._call(e))}},Kg=class extends H{},YD=class extends Kg{},XD=class extends Kg{},x2=class extends H{forward_params=["input_ids","attention_mask","pixel_values","position_ids","past_key_values"]},Xi=class extends x2{_merge_input_ids_with_image_features(e){const t=e.image_features.dims.at(-1),r=e.image_features.view(-1,t);return ig({image_token_id:this.config.image_token_index??this.config.image_token_id,...e,image_features:r})}},ZD=class extends Xi{},KD=class extends Xi{},JD=class extends Xi{forward_params=["input_ids","attention_mask","pixel_values","pixel_attention_mask","position_ids","past_key_values"]},Jg=class extends H{},e6=class extends Jg{},t6=class extends Jg{async _call(e){return new Ne(await super._call(e))}},ey=class extends H{},n6=class extends ey{},a6=class extends ey{},oh=class extends H{},r6=class extends oh{async forward(e){const t=!e.input_ids,r=!e.pixel_values;if(t&&r)throw new Error("Either `input_ids` or `pixel_values` should be provided.");if(t&&(e.input_ids=ha([e.pixel_values.dims[0],1])),r){const{image_size:f}=this.config.vision_config;e.pixel_values=On([0,3,f,f],0)}const{text_embeddings:s,image_embeddings:o,l2norm_text_embeddings:l,l2norm_image_embeddings:u}=await super.forward(e),d={};return t||(d.text_embeddings=s,d.l2norm_text_embeddings=l),r||(d.image_embeddings=o,d.l2norm_image_embeddings=u),d}},T2=class extends oh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},s6=class extends oh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},ty=class extends H{},i6=class extends ty{},o6=class extends ty{},ny=class extends H{},l6=class extends ny{},c6=class extends ny{},u6=class extends Xi{forward_params=["input_ids","attention_mask","pixel_values","pixel_attention_mask","spatial_shapes","position_ids","past_key_values"]},ay=class extends H{},d6=class extends ay{},f6=class extends ay{},S2=class extends H{},h6=class extends S2{},ry=class extends H{},p6=class extends ry{},m6=class extends ry{},sy=class extends H{},_6=class extends sy{},g6=class extends sy{},iy=class extends H{},y6=class extends iy{},v6=class extends iy{},oy=class extends H{},w6=class extends oy{},b6=class extends oy{},Ou=class extends H{},M6=class extends Ou{},x6=class extends Ou{},T6=class extends Ou{async _call(e){return new Ne(await super._call(e))}},S6=class extends Ou{},E2=class extends H{},E6=class extends E2{},A2=class extends H{},A6=class extends A2{},C2=class extends tn{constructor({char_logits:e,bpe_logits:t,wp_logits:r}){super(),this.char_logits=e,this.bpe_logits=t,this.wp_logits=r}get logits(){return[this.char_logits,this.bpe_logits,this.wp_logits]}},k2=class extends H{},C6=class extends k2{async _call(e){return new C2(await super._call(e))}},O2=class extends tn{constructor({audio_codes:e}){super(),this.audio_codes=e}},z2=class extends tn{constructor({audio_values:e}){super(),this.audio_values=e}},lh=class extends H{main_input_name="input_values";forward_params=["input_values"]},k6=class extends lh{async encode(e){return new O2(await st(this.sessions.encoder_model,e))}async decode(e){return new z2(await st(this.sessions.decoder_model,e))}},L2=class extends lh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},F2=class extends lh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},ly=class extends H{},O6=class extends ly{},z6=class extends ly{},zu=class extends H{},L6=class extends zu{},F6=class extends zu{async _call(e){return new dn(await super._call(e))}},N6=class extends zu{async _call(e){return new Ne(await super._call(e))}},D6=class extends zu{async _call(e){return new Ln(await super._call(e))}},cy=class extends H{},R6=class extends cy{},B6=class extends cy{},ch=class extends H{},P6=class extends ch{},I6=class extends ch{async _call(e){return new Ne(await super._call(e))}},U6=class extends ch{},uh=class extends H{},G6=class extends uh{},j6=class extends uh{async _call(e){return new Ne(await super._call(e))}},V6=class extends uh{},dh=class extends H{},q6=class extends dh{},H6=class extends dh{async _call(e){return new Ne(await super._call(e))}},$6=class extends dh{},fh=class extends H{},Q6=class extends fh{},W6=class extends fh{async _call(e){return new Ne(await super._call(e))}},Y6=class extends fh{},uy=class extends H{},X6=class extends uy{},Z6=class extends uy{async _call(e){return new Ne(await super._call(e))}},dy=class extends H{},K6=class extends dy{},J6=class extends dy{async _call(e){return new Ne(await super._call(e))}},Lu=class extends H{},eR=class extends Lu{},tR=class extends Lu{async _call(e){return new dn(await super._call(e))}},nR=class extends Lu{async _call(e){return new Ne(await super._call(e))}},aR=class extends Lu{async _call(e){return new nn(await super._call(e))}},fy=class extends H{},rR=class extends fy{},sR=class extends fy{},hy=class extends H{requires_attention_mask=!1;main_input_name="input_values";forward_params=["input_values","decoder_input_ids","past_key_values"]},iR=class extends hy{},oR=class extends hy{},Pl=class extends H{},lR=class extends Pl{},cR=class extends Pl{async _call(e){return new dn(await super._call(e))}},uR=class extends Pl{async _call(e){return new Ne(await super._call(e))}},dR=class extends Pl{async _call(e){return new nn(await super._call(e))}},fR=class extends Pl{async _call(e){return new Ln(await super._call(e))}},py=class extends H{},hR=class extends py{},pR=class extends py{},my=class extends H{},mR=class extends my{},_R=class extends my{},N2=class extends H{},gR=class extends N2{forward_params=["input_ids","pixel_values","images_seq_mask","images_emb_mask","attention_mask","position_ids","past_key_values"];constructor(...e){super(...e),this._generation_mode="text"}async forward(e){const t=this._generation_mode??"text";let r;if(t==="text"||!e.past_key_values){const d=this.sessions.prepare_inputs_embeds,f=yn(e,d.inputNames);r=await st(d,f)}else{const d=this.sessions.gen_img_embeds,f=yn({image_ids:e.input_ids},d.inputNames);r=await st(d,f)}const s={...e,...r},o=await as(this,s),l=this.sessions[t==="text"?"lm_head":"gen_head"];if(!l)throw new Error(`Unable to find "${l}" generation head`);const u=await st(l,yn(o,l.inputNames));return{...r,...o,...u}}prepare_inputs_for_generation(e,t,r){const s=!!t.past_key_values;return r.guidance_scale!==null&&r.guidance_scale>1&&(s?t.input_ids=zt([t.input_ids,t.input_ids],0):(t.input_ids=zt([t.input_ids,m_(t.input_ids,BigInt(r.pad_token_id))],0),t.attention_mask=zt([t.attention_mask,m_(t.attention_mask,0n)],0))),(s||!t.pixel_values)&&(t.pixel_values=On([0,0,3,384,384],1)),s&&(t.images_seq_mask=new me("bool",new Array(1).fill(!0).fill(!1,0,1),[1,1]),t.images_emb_mask=new me("bool",new Array(0).fill(!1),[1,1,0])),t}async generate(e){return this._generation_mode="text",super.generate(e)}async generate_images(e){this._generation_mode="image";const t=(e.inputs??e[this.main_input_name]).dims[1],s=(await super.generate(e)).slice(null,[t,null]),o=this.sessions.image_decode,{decoded_image:l}=await st(o,{generated_tokens:s}),u=l.add_(1).mul_(255/2).clamp_(0,255).to("uint8"),d=[];for(const f of u){const p=Xa.fromTensor(f);d.push(p)}return d}},_y=class extends H{},yR=class extends _y{},vR=class extends _y{},D2=class extends H{forward_params=["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"];_apply_and_filter_by_delay_pattern_mask(e){const[t,r]=e.dims,s=this.config.decoder.num_codebooks,o=r-s;let l=0;for(let f=0;f0&&y<=o&&(e.data[l++]=e.data[f])}const u=Math.floor(t/s),d=l/(u*s);return new me(e.type,e.data.slice(0,l),[u,s,d])}prepare_inputs_for_generation(e,t,r){const s=BigInt(this.config.decoder.pad_token_id);let o=structuredClone(e);for(let l=0;l=u&&(o[l][u]=s);return r.guidance_scale!==null&&r.guidance_scale>1&&(o=o.concat(o)),jf(this,o,t)}async generate(e){const t=await super.generate(e),r=this._apply_and_filter_by_delay_pattern_mask(t).unsqueeze_(0),{audio_values:s}=await st(this.sessions.encodec_decode,{audio_codes:r});return s}},gy=class extends H{},wR=class extends gy{},bR=class extends gy{},Il=class extends H{},MR=class extends Il{},xR=class extends Il{async _call(e){return new dn(await super._call(e))}},TR=class extends Il{async _call(e){return new Ne(await super._call(e))}},SR=class extends Il{async _call(e){return new nn(await super._call(e))}},ER=class extends Il{async _call(e){return new Ln(await super._call(e))}},R2=class extends H{},AR=class extends R2{},yy=class extends H{},CR=class extends yy{},kR=class extends yy{},vy=class extends H{},OR=class extends vy{},zR=class extends vy{},wy=class extends H{},LR=class extends wy{},FR=class extends wy{},by=class extends H{},NR=class extends by{},DR=class extends by{},My=class extends H{},RR=class extends My{},BR=class extends My{},xy=class extends H{},PR=class extends xy{},IR=class extends xy{},Ty=class extends H{},UR=class extends Ty{},GR=class extends Ty{},Sy=class extends H{},jR=class extends Sy{},VR=class extends Sy{},qR=class extends Xi{},B2=class extends H{},HR=class extends B2{async _call(e){return new eo(await super._call(e))}},Ey=class extends H{},$R=class extends Ey{},QR=class extends Ey{},Ay=class extends H{},WR=class extends Ay{},YR=class extends Ay{},Cy=class extends H{},XR=class extends Cy{},ZR=class extends Cy{},ky=class extends H{},KR=class extends ky{},JR=class extends ky{},P2=class extends H{forward_params=["input_ids","inputs_embeds","attention_mask","position_ids","pixel_values","image_sizes","past_key_values"]},I2=class extends P2{async forward({input_ids:e=null,attention_mask:t=null,pixel_values:r=null,image_sizes:s=null,position_ids:o=null,inputs_embeds:l=null,past_key_values:u=null,generation_config:d=null,logits_processor:f=null,...p}){if(!l){let y;if(r&&e.dims[1]!==1){if(!s)throw new Error("`image_sizes` must be provided when `pixel_values` is provided.");({image_features:y}=await st(this.sessions.vision_encoder,{pixel_values:r,image_sizes:s}))}else{const w=this.config.normalized_config.hidden_size;y=new me("float32",[],[0,w])}({inputs_embeds:l}=await st(this.sessions.prepare_inputs_embeds,{input_ids:e,image_features:y}))}return await as(this,{inputs_embeds:l,past_key_values:u,attention_mask:t,position_ids:o,generation_config:d,logits_processor:f},!1)}},Oy=class extends H{},eB=class extends Oy{},tB=class extends Oy{async _call(e){return new Ne(await super._call(e))}},zy=class extends H{},nB=class extends zy{},aB=class extends zy{async _call(e){return new nn(await super._call(e))}},Ly=class extends H{},rB=class extends Ly{},sB=class extends Ly{},Fy=class extends H{},iB=class extends Fy{},oB=class extends Fy{},U2=class extends H{forward_params=["input_ids","attention_mask","position_ids","past_key_values","pixel_values","image_grid_thw"]},Ny=class extends U2{image_grid_thw_name="grid_thw";get_rope_index(e,t,r,s){const{vision_config:o,image_token_id:l,video_token_id:u,vision_start_token_id:d}=this.config,f=o.spatial_merge_size??2,p=[];if(t||r){let g=e.tolist();s||(s=nx(e));const y=s.tolist(),w=Array.from({length:3},k=>Array.from({length:e.dims[0]},L=>Array.from({length:e.dims[1]},R=>1))),b=t?t.tolist():[],S=r?r.tolist():[];let E=0,z=0;for(let k=0;ky[k][I]==1),N=L.reduce((ee,I,$)=>(I==d&&ee.push($),ee),[]).map(ee=>L[ee+1]),B=N.filter(ee=>ee==l).length,j=N.filter(ee=>ee==u).length;let C=[],ue=0,oe=B,he=j;for(let ee=0;eeDt>ue&&an==l),$=L.findIndex((an,Dt)=>Dt>ue&&an==u),J=oe>0&&I!==-1?I:L.length+1,D=he>0&&$!==-1?$:L.length+1;let te,ae,ge,Me;J0?Ht(C.at(-1))[0]+1:0;C.push(Array.from({length:3*ke},(an,Dt)=>Ue+Dt%ke));const xt=ke+Ue,He=Ee*ze*et,Ye=Array.from({length:He},(an,Dt)=>xt+Math.floor(Dt/(ze*et))),bn=Array.from({length:He},(an,Dt)=>xt+Math.floor(Dt/et)%ze),za=Array.from({length:He},(an,Dt)=>xt+Dt%et);C.push([Ye,bn,za].flat()),ue=te+He}if(ue0?Ht(C.at(-1))[0]+1:0,I=L.length-ue;C.push(Array.from({length:3*I},($,J)=>ee+J%I))}const _e=C.reduce((ee,I)=>ee+I.length,0),de=new Array(_e);let re=0;for(let ee=0;ee<3;++ee)for(let I=0;Ig[E%g.length]),b=Array.from({length:y[0]},(S,E)=>Ht(g.subarray(y[1]*E,y[1]*(E+1)))[0]+1n+BigInt(y[1]));return[new me("int64",w,[3,...y]),new me("int64",b,[b.length,1])]}else{const[g,y]=e.dims,w=BigInt64Array.from({length:3*g*y},(b,S)=>BigInt(Math.floor(S%y/g)));return[new me("int64",w,[3,...e.dims]),ax([g,1])]}}async encode_image({pixel_values:e,image_grid_thw:t}){return(await st(this.sessions.vision_encoder,{pixel_values:e,[this.image_grid_thw_name]:t})).image_features}_merge_input_ids_with_image_features(e){return ig({image_token_id:this.config.image_token_id,...e})}prepare_inputs_for_generation(e,t,r){if(t.attention_mask&&!t.position_ids)if(!t.past_key_values)[t.position_ids,t.rope_deltas]=this.get_rope_index(t.input_ids,t.image_grid_thw,t.video_grid_thw,t.attention_mask);else{t.pixel_values=null;const s=t.past_key_values.get_seq_length();if(so+u);t.position_ids=Ji([l,l,l],0)}}return t}},Dy=class extends Ny{},G2=class extends Ny{image_grid_thw_name="image_grid_thw"},Ry=class extends Dy{image_grid_thw_name="image_grid_thw"},By=class extends H{},lB=class extends By{},cB=class extends By{},Py=class extends H{},uB=class extends Py{},dB=class extends Py{},Iy=class extends H{},fB=class extends Iy{},hB=class extends Iy{},Uy=class extends G2{},Gy=class extends Ry{},pB=class extends Uy{},j2=class extends Gy{},jy=class extends Uy{},Vy=class extends jy{},mB=class extends jy{},V2=class extends Vy{},qy=class extends H{},_B=class extends qy{},gB=class extends qy{async _call(e){return new Ne(await super._call(e))}},Hy=class extends H{},yB=class extends Hy{},vB=class extends Hy{async _call(e){return new q2(await super._call(e))}},q2=class extends Cu{},Ul=class extends H{},wB=class extends Ul{},bB=class extends Ul{async _call(e){return new dn(await super._call(e))}},MB=class extends Ul{async _call(e){return new Ne(await super._call(e))}},xB=class extends Ul{async _call(e){return new nn(await super._call(e))}},TB=class extends Ul{async _call(e){return new Ln(await super._call(e))}},Gl=class extends H{},SB=class extends Gl{},EB=class extends Gl{async _call(e){return new dn(await super._call(e))}},AB=class extends Gl{async _call(e){return new Ne(await super._call(e))}},CB=class extends Gl{async _call(e){return new nn(await super._call(e))}},kB=class extends Gl{async _call(e){return new Ln(await super._call(e))}},$y=class extends H{},OB=class extends $y{},zB=class extends $y{async _call(e){return new H2(await super._call(e))}},H2=class extends Cu{},$2=class extends tn{constructor({iou_scores:e,pred_masks:t}){super(),this.iou_scores=e,this.pred_masks=t}},Q2=class extends H{},LB=class extends Q2{async get_image_embeddings({pixel_values:e}){return await Js(this,{pixel_values:e})}async forward(e){!e.image_embeddings||!e.image_positional_embeddings?e={...e,...await this.get_image_embeddings(e)}:e={...e},e.input_labels??=ha(e.input_points.dims.slice(0,-1));const t={image_embeddings:e.image_embeddings,image_positional_embeddings:e.image_positional_embeddings};return e.input_points&&(t.input_points=e.input_points),e.input_labels&&(t.input_labels=e.input_labels),e.input_boxes&&(t.input_boxes=e.input_boxes),await st(this.sessions.prompt_encoder_mask_decoder,t)}async _call(e){return new $2(await super._call(e))}},W2=class extends tn{constructor({iou_scores:e,pred_masks:t,object_score_logits:r}){super(),this.iou_scores=e,this.pred_masks=t,this.object_score_logits=r}},Y2=class extends H{},Qy=class extends Y2{async get_image_embeddings({pixel_values:e}){return await Js(this,{pixel_values:e})}async forward(e){const{num_feature_levels:t}=this.config.vision_config;if(Array.from({length:t},(l,u)=>`image_embeddings.${u}`).some(l=>!e[l])?e={...e,...await this.get_image_embeddings(e)}:e={...e},e.input_points){if(e.input_boxes&&e.input_boxes.dims[1]!==1)throw new Error("When both `input_points` and `input_boxes` are provided, the number of boxes per image must be 1.");const l=e.input_points.dims;e.input_labels??=ha(l.slice(0,-1)),e.input_boxes??=On([l[0],0,4],0)}else if(e.input_boxes){const l=e.input_boxes.dims;e.input_labels=On([l[0],l[1],0],-1n),e.input_points=On([l[0],1,0,2],0)}else throw new Error("At least one of `input_points` or `input_boxes` must be provided.");const s=this.sessions.prompt_encoder_mask_decoder,o=yn(e,s.inputNames);return await st(s,o)}async _call(e){return new W2(await super._call(e))}},FB=class extends Qy{},NB=class extends Qy{},hh=class extends H{},DB=class extends hh{},RB=class extends hh{},BB=class extends hh{},ph=class extends H{},PB=class extends ph{},IB=class extends ph{},UB=class extends ph{},Wy=class extends H{},GB=class extends Wy{},X2=class extends Wy{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"text_model"})}},jB=class extends to{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"vision_model"})}},Yy=class extends H{},VB=class extends Yy{},qB=class extends Yy{},mh=class extends H{main_input_name="input_values";forward_params=["input_values"]},HB=class extends mh{async encode(e){return await st(this.sessions.encoder_model,e)}async decode(e){return await st(this.sessions.decoder_model,e)}},Z2=class extends mh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"encoder_model"})}},K2=class extends mh{static async from_pretrained(e,t={}){return super.from_pretrained(e,{...t,model_file_name:t.model_file_name??"decoder_model"})}},_h=class extends H{},$B=class extends _h{},QB=class extends _h{},WB=class extends _h{async generate_speech(e,t,{threshold:r=.5,minlenratio:s=0,maxlenratio:o=20,vocoder:l=null}={}){const u={input_ids:e},{encoder_outputs:d,encoder_attention_mask:f}=await Js(this,u),p=d.dims[1]/this.config.reduction_factor,g=Math.floor(p*o),y=Math.floor(p*s),w=this.config.num_mel_bins;let b=[],S=null,E=null,z=0;for(;;){++z;const R=Yx(!!E);let N;E?N=E.output_sequence_out:N=new me("float32",new Float32Array(w),[1,1,w]);let B={use_cache_branch:R,output_sequence:N,encoder_attention_mask:f,speaker_embeddings:t,encoder_hidden_states:d};this.addPastKeyValues(B,S),E=await st(this.sessions.decoder_model_merged,B),S=this.getPastKeyValues(E,S);const{prob:j,spectrum:C}=E;if(b.push(C),z>=y&&(Array.from(j.data).filter(ue=>ue>=r).length>0||z>=g))break}const k=zt(b),{waveform:L}=await st(l.sessions.model,{spectrogram:k});return{spectrogram:k,waveform:L}}},YB=class extends H{main_input_name="spectrogram"},Fu=class extends H{},XB=class extends Fu{},ZB=class extends Fu{async _call(e){return new dn(await super._call(e))}},KB=class extends Fu{async _call(e){return new Ne(await super._call(e))}},JB=class extends Fu{async _call(e){return new Ln(await super._call(e))}},Xy=class extends H{},e8=class extends Xy{},t8=class extends Xy{},Zy=class extends H{},n8=class extends Zy{},a8=class extends Zy{},J2=class extends H{},r8=class extends J2{},eT=class extends H{},tT=class extends eT{async generate_speech({input_ids:e,attention_mask:t,style:r,num_inference_steps:s=5,speed:o=1.05}){const{sampling_rate:l,chunk_compress_factor:u,base_chunk_size:d,latent_dim:f}=this.config,{last_hidden_state:p,durations:g}=await st(this.sessions.text_encoder,{input_ids:e,attention_mask:t,style:r}),y=g.div(o).mul_(l),w=d*u,b=y.data,S=Int32Array.from(b,oe=>Math.ceil(oe/w)),E=Math.max(...S),z=e.dims[0],k=new BigInt64Array(z*E);for(let oe=0;oez*k,1);f[S]=new me(p,new g(E),y[S])}const w=new me(p,new g(d*p1),[1,d,p1]),b=t[Symbol.asyncIterator]?.()??t[Symbol.iterator]?.();if(!b)throw new Error("input_features must be iterable or async iterable");return{encoder_session:o,enc_kv_cache:f,enc_padding_cache:w,enc_past_seq_len:0,audio_embed_queue:[],audio_embed_total_tokens:0,audio_queue_offset:0,audio_consumed:0,stream_exhausted:!1,chunks_iter:b,text_hidden_size:r.hidden_size}}async function R8(e,t){const r=t.dims[2],s=Math.floor((N8+r-3)/2)+1,o=new me("int64",BigInt64Array.from({length:s},(g,y)=>BigInt(e.enc_past_seq_len+y)),[1,s]),l=e.enc_past_seq_len+s,u=ha([1,l]),{audio_embeds:d,present_padding_cache:f,...p}=await st(e.encoder_session,{input_features:t,attention_mask:u,position_ids:o,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=f;for(const g in p)if(g.startsWith("present.")){const y=g.replace("present","past_key_values"),w=e.enc_kv_cache[y];w?.location==="gpu-buffer"&&w.dispose(),e.enc_kv_cache[y]=p[g]}return e.enc_past_seq_len=l,d}async function B8(e,t){for(;e.audio_embed_total_tokens0&&e.audio_embed_queue.length>0;){const u=e.audio_embed_queue[0],d=u.tokens-e.audio_queue_offset,f=Math.min(l,d),p=e.audio_queue_offset*e.text_hidden_size;for(let g=0;g=u.tokens&&(e.audio_embed_queue.shift(),e.audio_queue_offset=0)}e.audio_consumed+=r-l}var I8=class extends th{constructor(e){super(),this._s=e}_call(e){const t=this._s.stream_exhausted&&this._s.audio_embed_queue.length===0;return e.map(()=>t)}},cT=class extends H{forward_params=["input_ids","attention_mask","position_ids","past_key_values"]},uT=class extends cT{async forward({input_ids:e,past_key_values:t,...r}){const s=e.dims[1],o=t_.get(this);o&&await B8(o,o.audio_consumed+s);const{inputs_embeds:l}=await st(this.sessions.embed_tokens,{input_ids:e});o&&P8(o,l,s);const u={inputs_embeds:l,...r};this.addPastKeyValues(u,t);const d=this.sessions.decoder_model_merged,f=yn(u,d.inputNames);return await st(d,f)}async generate({input_features:e,stopping_criteria:t,...r}){if(!e)throw new Error("input_features (generator/iterable) must be provided");const s=D8(this,e);t_.set(this,s);const o=new $x;o.push(new I8(s)),t&&o.extend(t);try{return await super.generate({...r,stopping_criteria:o})}finally{s.enc_kv_cache.dispose(),t_.delete(this)}}},vh=class extends H{},U8=class extends vh{},G8=class extends vh{async _call(e){return new eo(await super._call(e))}},j8=class extends vh{async _call(e){return new Ne(await super._call(e))}},dT=class extends tn{constructor({logits:e,embeddings:t}){super(),this.logits=e,this.embeddings=t}},jl=class extends H{},V8=class extends jl{},q8=class extends jl{async _call(e){return new eo(await super._call(e))}},H8=class extends jl{async _call(e){return new Ne(await super._call(e))}},$8=class extends jl{async _call(e){return new dT(await super._call(e))}},Q8=class extends jl{async _call(e){return new nn(await super._call(e))}},fT=class extends H{},W8=class extends fT{},Y8=class extends Hx{return_timestamps=null;return_token_timestamps=null;num_frames=null;alignment_heads=null;task=null;language=null;no_timestamps_token_id=null;prompt_ids=null;is_multilingual=null;lang_to_id=null;task_to_id=null;max_initial_timestamp_index=1},rv=class extends H{requires_attention_mask=!1;main_input_name="input_features";forward_params=["input_features","attention_mask","decoder_input_ids","decoder_attention_mask","past_key_values"]},X8=class extends rv{},hT=class extends rv{_prepare_generation_config(e,t){return super._prepare_generation_config(e,t,Y8)}_retrieve_init_tokens(e){const t=[e.decoder_start_token_id];let r=e.language;const s=e.task;if(e.is_multilingual){r||(Re.warn("No language specified - defaulting to English (en)."),r="en");const l=`<|${cz(r)}|>`;t.push(e.lang_to_id[l]),t.push(e.task_to_id[s??"transcribe"])}else if(r||s)throw new Error("Cannot specify `task` or `language` for an English-only model. If the model is intended to be multilingual, pass `is_multilingual=true` to generate, or update the generation config.");return!e.return_timestamps&&e.no_timestamps_token_id&&t.at(-1)!==e.no_timestamps_token_id?t.push(e.no_timestamps_token_id):e.return_timestamps&&t.at(-1)===e.no_timestamps_token_id&&(Re.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),t.pop()),t.filter(o=>o!=null)}async generate({inputs:e=null,generation_config:t=null,logits_processor:r=null,stopping_criteria:s=null,...o}){t=this._prepare_generation_config(t,o);const l=o.decoder_input_ids??this._retrieve_init_tokens(t);if(t.return_timestamps&&(r??=new w_,r.push(new NF(t,l))),t.begin_suppress_tokens&&(r??=new w_,r.push(new qx(t.begin_suppress_tokens,l.length))),t.return_token_timestamps){if(!t.alignment_heads)throw new Error("Model generation config has no `alignment_heads`, token-level timestamps not available. See https://gist.github.com/hollance/42e32852f24243b748ae6bc1f985b13a on how to add this property to the generation config.");t.task==="translate"&&Re.warn("Token-level timestamps may not be reliable for task 'translate'."),t.output_attentions=!0,t.return_dict_in_generate=!0}const u=await super.generate({inputs:e,generation_config:t,logits_processor:r,decoder_input_ids:l,...o});return t.return_token_timestamps&&(u.token_timestamps=this._extract_token_timestamps(u,t.alignment_heads,t.num_frames)),u}_extract_token_timestamps(e,t,r=null,s=.02){if(!e.cross_attentions)throw new Error("Model outputs must contain cross attentions to extract timestamps. This is most likely because the model was not exported with `output_attentions=True`.");r==null&&Re.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 o=this.config.median_filter_width;o===void 0&&(Re.warn("Model config has no `median_filter_width`, using default value of 7."),o=7);const l=e.cross_attentions,u=Array.from({length:this.config.decoder_layers},(S,E)=>zt(l.map(z=>z[E]),2)),d=Ji(t.map(([S,E])=>{if(S>=u.length)throw new Error(`Layer index ${S} is out of bounds for cross attentions (length ${u.length}).`);return r?u[S].slice(null,E,null,[0,r]):u[S].slice(null,E)})).transpose(1,0,2,3),[f,p]=pO(d,-2,0,!0),g=d.clone();for(let S=0;Sz[j+1]-z[j]),R=Sr([1],L).map(B=>!!B),N=[];for(let B=0;Be[0]);static BASE_IF_FAIL=!0},m1=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING_NAMES]},bP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES]},n_=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES]},MP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES]},xP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_TEXT_TO_SPECTROGRAM_MAPPING_NAMES]},TP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_TEXT_TO_WAVEFORM_MAPPING_NAMES]},HT=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES]},SP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_MASKED_LM_MAPPING_NAMES]},EP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES]},AP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES]},CP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING_NAMES]},_1=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_SEGMENTATION_MAPPING_NAMES]},g1=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_SEMANTIC_SEGMENTATION_MAPPING_NAMES]},y1=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_UNIVERSAL_SEGMENTATION_MAPPING_NAMES]},kP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_OBJECT_DETECTION_MAPPING_NAMES]},OP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING_NAMES]};(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_MASK_GENERATION_MAPPING_NAMES]});var zP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_CTC_MAPPING_NAMES]},LP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING_NAMES]};(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_AUDIO_XVECTOR_MAPPING_NAMES]});(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_AUDIO_FRAME_CLASSIFICATION_MAPPING_NAMES]});var FP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING_NAMES]};(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_MATTING_MAPPING_NAMES]});var NP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_TO_IMAGE_MAPPING_NAMES]},DP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_DEPTH_ESTIMATION_MAPPING_NAMES]};(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_NORMAL_ESTIMATION_MAPPING_NAMES]});(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_POSE_ESTIMATION_MAPPING_NAMES]});var RP=class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_FEATURE_EXTRACTION_MAPPING_NAMES]};(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_IMAGE_TEXT_TO_TEXT_MAPPING_NAMES]});(class extends ft{static MODEL_CLASS_MAPPINGS=[dt.MODEL_FOR_AUDIO_TEXT_TO_TEXT_MAPPING_NAMES]});async function tr(e){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(t=>Xa.read(t)))}async function vu(e,t){return Array.isArray(e)||(e=[e]),await Promise.all(e.map(r=>typeof r=="string"||r instanceof URL?yz(r,t):r instanceof Float64Array?new Float32Array(r):r))}function M_(e,t){t&&(e=e.map(u=>u|0));const[r,s,o,l]=e;return{xmin:r,ymin:s,xmax:o,ymax:l}}var Vt=class extends Oa{constructor({task:e,model:t,tokenizer:r=null,processor:s=null}){super(),this.task=e,this.model=t,this.tokenizer=r,this.processor=s}async dispose(){await this.model.dispose()}},BP=class extends Vt{async _call(e,{top_k:t=1}={}){const r=this.tokenizer(e,{padding:!0,truncation:!0}),s=await this.model(r),{problem_type:o,id2label:l}=this.model.config,u=o==="multi_label_classification"?f=>f.sigmoid():f=>new me("float32",wn(f.data),f.dims),d=[];for(const f of s.logits){const p=u(f),g=await Ol(p,t),y=g[0].tolist(),b=g[1].tolist().map((S,E)=>({label:l?l[S]:`LABEL_${S}`,score:y[E]}));t===1?d.push(...b):d.push(b)}return Array.isArray(e)||t===1?d:d[0]}},PP=class extends Vt{async _call(e,{ignore_labels:t=["O"]}={}){const r=Array.isArray(e),s=this.tokenizer(r?e:[e],{padding:!0,truncation:!0}),l=(await this.model(s)).logits,u=this.model.config.id2label,d=[];for(let f=0;fB==g),E=l[w].tolist(),z=u[w].tolist();for(let B=1;Bj==b[B])!==-1)&&(E[B]=-1/0,z[B]=-1/0);const k=wn(E).map((B,j)=>[B,j]),L=wn(z).map((B,j)=>[B,j]);k[0][0]=0,L[0][0]=0;const R=bA(k,L).filter(B=>B[0][1]<=B[1][1]).map(B=>[B[0][1],B[1][1],B[0][0]*B[1][0]]).sort((B,j)=>j[2]-B[2]),N=[];for(let B=0;BE==r);if(g===-1)throw Error(`Mask token (${s}) not found in text.`);const y=l[f][g],w=await Ol(new me("float32",wn(y.data),y.dims),t),b=w[0].tolist(),S=w[1].tolist();u.push(S.map((E,z)=>{const k=p.slice();return k[g]=E,{score:b[z],token:Number(E),token_str:this.tokenizer.decode([E]),sequence:this.tokenizer.decode(k,{skip_special_tokens:!0})}}))}return Array.isArray(e)?u:u[0]}},ov=class extends Vt{_key="generated_text";async _call(e,t={}){Array.isArray(e)||(e=[e]),this.model.config.prefix&&(e=e.map(d=>this.model.config.prefix+d));const r=this.model.config.task_specific_params;r&&r[this.task]&&r[this.task].prefix&&(e=e.map(d=>r[this.task].prefix+d));const s=this.tokenizer,o={padding:!0,truncation:!0};let l;this.task==="translation"&&"_build_translation_inputs"in s?l=s._build_translation_inputs(e,o,t):l=s(e,o);const u=await this.model.generate({...l,...t});return s.batch_decode(u,{skip_special_tokens:!0}).map(d=>({[this._key]:d}))}},GP=class extends ov{_key="summary_text"},jP=class extends ov{_key="translation_text"};function v1(e){return Array.isArray(e)&&e.every(t=>"role"in t&&"content"in t)}var VP=class extends Vt{async _call(e,t={}){let r=!1,s=!1,o=t.add_special_tokens??(this.tokenizer.add_bos_token||this.tokenizer.add_eos_token)??!1,l=t.tokenizer_encode_kwargs,u;if(typeof e=="string")u=e=[e];else if(Array.isArray(e)&&e.every(b=>typeof b=="string"))r=!0,u=e;else{if(v1(e))e=[e];else if(Array.isArray(e)&&e.every(v1))r=!0;else throw new Error("Input must be a string, an array of strings, a Chat, or an array of Chats");s=!0,u=e.map(b=>this.tokenizer.apply_chat_template(b,{tokenize:!1,add_generation_prompt:!0,...l})),o=!1,l=void 0}const d=s?!1:t.return_full_text??!0;this.tokenizer.padding_side="left";const f=this.tokenizer(u,{add_special_tokens:o,padding:!0,truncation:!0,...l}),p=await this.model.generate({...f,...t}),g=this.tokenizer.batch_decode(p,{skip_special_tokens:!0});let y;!d&&f.input_ids.dims.at(-1)>0&&(y=this.tokenizer.batch_decode(f.input_ids,{skip_special_tokens:!0}).map(b=>b.length));const w=Array.from({length:e.length},b=>[]);for(let b=0;b[t.toLowerCase(),r])),this.entailment_id=this.label2id.entailment,this.entailment_id===void 0&&(Re.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&&(Re.warn("Could not find 'contradiction' in label2id mapping. Using 0 as contradiction_id."),this.contradiction_id=0)}async _call(e,t,{hypothesis_template:r="This example is {}.",multi_label:s=!1}={}){const o=Array.isArray(e);o||(e=[e]),Array.isArray(t)||(t=[t]);const l=t.map(f=>r.replace("{}",f)),u=s||t.length===1,d=[];for(const f of e){const p=[];for(const w of l){const b=this.tokenizer(f,{text_pair:w,padding:!0,truncation:!0}),S=await this.model(b);u?p.push([S.logits.data[this.contradiction_id],S.logits.data[this.entailment_id]]):p.push(S.logits.data[this.entailment_id])}const y=(u?p.map(w=>wn(w)[1]):wn(p)).map((w,b)=>[w,b]).sort((w,b)=>b[0]-w[0]);d.push({sequence:f,labels:y.map(w=>t[w[1]]),scores:y.map(w=>w[0])})}return o?d:d[0]}},HP=class extends Vt{async _call(e,{top_k:t=5}={}){const r=this.processor.feature_extractor.config.sampling_rate,s=await vu(e,r),o=this.model.config.id2label,l=[];for(const u of s){const d=await this.processor(u),p=(await this.model(d)).logits[0],g=await Ol(new me("float32",wn(p.data),p.dims),t),y=g[0].tolist(),b=g[1].tolist().map((S,E)=>({label:o?o[S]:`LABEL_${S}`,score:y[E]}));l.push(b)}return Array.isArray(e)?l:l[0]}},$P=class extends Vt{async _call(e,t,{hypothesis_template:r="This is a sound of {}."}={}){const s=!Array.isArray(e);s&&(e=[e]);const o=t.map(p=>r.replace("{}",p)),l=this.tokenizer(o,{padding:!0,truncation:!0}),u=this.processor.feature_extractor.config.sampling_rate,d=await vu(e,u),f=[];for(const p of d){const g=await this.processor(p),y=await this.model({...l,...g}),w=wn(y.logits_per_audio.data);f.push([...w].map((b,S)=>({score:b,label:t[S]})))}return s?f[0]:f}},QP=class extends Vt{async _call(e,t={}){switch(this.model.config.model_type){case"whisper":case"lite-whisper":return this._call_whisper(e,t);case"wav2vec2":case"wav2vec2-bert":case"unispeech":case"unispeech-sat":case"hubert":case"parakeet_ctc":return this._call_wav2vec2(e,t);case"moonshine":return this._call_moonshine(e,t);default:throw new Error(`AutomaticSpeechRecognitionPipeline does not support model type '${this.model.config.model_type}'.`)}}async _call_wav2vec2(e,t){t.language&&Re.warn('`language` parameter is not yet supported for `wav2vec2` models, defaulting to "English".'),t.task&&Re.warn('`task` parameter is not yet supported for `wav2vec2` models, defaulting to "transcribe".');const r=!Array.isArray(e),s=r?[e]:e,o=this.processor.feature_extractor.config.sampling_rate,l=await vu(s,o),u=[];for(const d of l){const f=await this.processor(d),g=(await this.model(f)).logits[0],y=[];for(const b of g)y.push(Ht(b.data)[1]);const w=this.tokenizer.decode(y,{skip_special_tokens:!0}).trim();u.push({text:w})}return r?u[0]:u}async _call_whisper(e,t){const r=t.return_timestamps??!1,s=t.chunk_length_s??0,o=t.force_full_sequences??!1;let l=t.stride_length_s??null;const u={...t};r==="word"&&(u.return_token_timestamps=!0,u.return_timestamps=!1);const d=!Array.isArray(e),f=d?[e]:e,p=this.processor.feature_extractor.config,g=p.chunk_length/this.model.config.max_source_positions,y=p.hop_length,w=p.sampling_rate,b=await vu(f,w),S=[];for(const E of b){let z=[];if(s>0){if(l===null)l=s/6;else if(s<=l)throw Error("`chunk_length_s` must be larger than `stride_length_s`.");const R=w*s,N=w*l,B=R-2*N;let j=0;for(;;){const C=j+R,ue=E.subarray(j,C),oe=await this.processor(ue),he=j===0,_e=C>=E.length;if(z.push({stride:[ue.length,he?0:N,_e?0:N],input_features:oe.input_features,is_last:_e}),_e)break;j+=B}}else z=[{stride:[E.length,0,0],input_features:(await this.processor(E)).input_features,is_last:!0}];for(const R of z){u.num_frames=Math.floor(R.stride[0]/y);const N=await this.model.generate({inputs:R.input_features,...u});r==="word"?(R.tokens=N.sequences.tolist()[0],R.token_timestamps=N.token_timestamps.tolist()[0].map(B=>mu(B,2))):R.tokens=N[0].tolist(),R.stride=R.stride.map(B=>B/w)}const[k,L]=this.tokenizer._decode_asr(z,{time_precision:g,return_timestamps:r,force_full_sequences:o});S.push({text:k,...L})}return d?S[0]:S}async _call_moonshine(e,t){const r=!Array.isArray(e),s=r?[e]:e,o=this.processor.feature_extractor.config.sampling_rate,l=await vu(s,o),u=[];for(const d of l){const f=await this.processor(d),p=Math.floor(d.length/o)*6,g=await this.model.generate({max_new_tokens:p,...t,...f}),y=this.processor.batch_decode(g,{skip_special_tokens:!0})[0];u.push({text:y})}return r?u[0]:u}},WP=class extends Vt{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 rt.fetch(e)).arrayBuffer())),e instanceof Float32Array)e=new me("float32",e,[e.length]);else if(!(e instanceof me))throw new 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 new Error(`Expected speaker embeddings batch size to be 1 or ${t}, but got ${e.dims[0]}.`)}return e}_postprocess_waveform(e,t,r,s=null){const o=t.data,[l,u]=t.dims,d=s?s.data:null,f=[];for(let p=0;p({generated_text:p.trim()}));l.push(f)}return r?l:l[0]}},XP=class extends Vt{async _call(e,{top_k:t=5}={}){const r=await tr(e),{pixel_values:s}=await this.processor(r),o=await this.model({pixel_values:s}),{id2label:l}=this.model.config,u=[];for(const d of o.logits){const f=await Ol(new me("float32",wn(d.data),d.dims),t),p=f[0].tolist(),y=f[1].tolist().map((w,b)=>({label:l?l[w]:`LABEL_${w}`,score:p[b]}));u.push(y)}return Array.isArray(e)?u:u[0]}},w1={panoptic:"post_process_panoptic_segmentation",instance:"post_process_instance_segmentation",semantic:"post_process_semantic_segmentation"},$T=class extends Vt{async _call(e,{threshold:t=.5,mask_threshold:r=.5,overlap_mask_area_threshold:s=.8,label_ids_to_fuse:o=null,target_sizes:l=null,subtask:u=null}={}){if(Array.isArray(e)&&e.length!==1)throw Error("Image segmentation pipeline currently only supports a batch size of 1.");const f=await tr(e),p=f.map(k=>[k.height,k.width]),g=await this.processor(f),{inputNames:y,outputNames:w}=this.model.sessions.model;if(!y.includes("pixel_values")){if(y.length!==1)throw Error(`Expected a single input name, but got ${y.length} inputs: ${y}.`);const k=y[0];if(k in g)throw Error(`Input name ${k} already exists in the inputs.`);g[k]=g.pixel_values}const b=await this.model(g);let S=null;if(u!==null)S=w1[u];else if(this.processor.image_processor){for(const[k,L]of Object.entries(w1))if(L in this.processor.image_processor){S=this.processor.image_processor[L].bind(this.processor.image_processor),u=k;break}}const E=this.model.config.id2label,z=[];if(u)if(u==="panoptic"||u==="instance"){const k=S(b,t,r,s,o,l??p)[0],L=k.segmentation;for(const R of k.segments_info){const N=new Uint8ClampedArray(L.data.length);for(let j=0;jC<-1e-5||C>1+1e-5)&&B.sigmoid_();const j=await Xa.fromTensor(B.mul_(255).to("uint8")).resize(N[1],N[0]);z.push({label:null,score:null,mask:j})}}return z}},ZP=class extends $T{async _call(e,t={}){const r=await tr(e),s=await super._call(e,t),o=r.map((l,u)=>{const d=l.clone();return d.putAlpha(s[u].mask),d});return Array.isArray(e)?o:o[0]}},KP=class extends Vt{async _call(e,t,{hypothesis_template:r="This is a photo of {}"}={}){const s=Array.isArray(e),o=await tr(e),l=t.map(y=>r.replace("{}",y)),u=this.tokenizer(l,{padding:this.model.config.model_type==="siglip"?"max_length":!0,truncation:!0}),{pixel_values:d}=await this.processor(o),f=await 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