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s=this.mlContextCache.findIndex(o=>o.mlContext===n);s!==-1&&this.mlContextCache.splice(s,1)}}getMLContext(e){return this.mlContextBySessionId.get(e)}getMLOpSupportLimits(e){return this.mlOpSupportLimitsBySessionId.get(e)}reserveTensorId(){return this.tensorManager.reserveTensorId()}releaseTensorId(e){kn("verbose",()=>`[WebNN] releaseTensorId {tensorId: ${e}}`),this.tensorManager.releaseTensorId(e)}async ensureTensor(e,n,r,s,o){let c=Mu.get(r);if(!c)throw new Error(`Unsupported ONNX data type: ${r}`);return this.tensorManager.ensureTensor(e??this.currentSessionId,n,c,s,o)}async createTemporaryTensor(e,n,r){kn("verbose",()=>`[WebNN] createTemporaryTensor {onnxDataType: ${n}, shape: ${r}}`);let s=Mu.get(n);if(!s)throw new Error(`Unsupported ONNX data type: ${n}`);let o=this.tensorManager.reserveTensorId();await this.tensorManager.ensureTensor(e,o,s,r,!1);let c=this.temporarySessionTensorIds.get(e);return 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"+e),(this.use_regex?e.match(this.pattern)||[]:[e]).map(s=>Array.from(this.text_encoder.encode(s),o=>this.byte_encoder[o]).join(""))}},BC=FC,PC=class extends sr{pre_tokenize_text(e,n){return e.match(/\w+|[^\w\s]+/g)||[]}},RC=PC,UC=class extends sr{constructor(e){super(),this.replacement=e.replacement??"▁",this.str_rep=e.str_rep||this.replacement,this.prepend_scheme=e.prepend_scheme??"always"}pre_tokenize_text(e,n){const{section_index:r=void 0}=n??{};let s=e.replaceAll(" ",this.str_rep);return!s.startsWith(this.replacement)&&(this.prepend_scheme==="always"||this.prepend_scheme==="first"&&r===0)&&(s=this.str_rep+s),[s]}},IC=UC,GC=class extends sr{constructor(e){super(),this.config=e,this.pattern=Eh(this.config.pattern??{},this.config.invert??!0)}pre_tokenize_text(e){var n;return this.pattern===null?[]:this.config.invert?e.match(this.pattern)||[]:((n=this.config.behavior)==null?void 0:n.toLowerCase())==="removed"?e.split(this.pattern).filter(r=>r):rC(e,this.pattern)}},jC=GC,VC=class extends sr{constructor(e){super(),this.config=e,this.pattern=new RegExp(`[^${ph}]+|[${ph}]+`,"gu")}pre_tokenize_text(e){return e.match(this.pattern)||[]}},qC=VC,$C=class extends sr{constructor(e){super(),this.config=e;const n=`[^\\d]+|\\d${this.config.individual_digits?"":"+"}`;this.pattern=new RegExp(n,"gu")}pre_tokenize_text(e){return e.match(this.pattern)||[]}},HC=$C,YC=class extends sr{constructor(){super(),this.pattern=new RegExp(`[^\\s${ph}]+|[${ph}]`,"gu")}pre_tokenize_text(e,n){return e.trim().match(this.pattern)||[]}},XC=YC,QC=class extends sr{constructor(e){super(),this.config=e,this.pattern=Eh(this.config.pattern??{}),this.content=this.config.content??""}pre_tokenize_text(e){return this.pattern===null?[e]:[e.replaceAll(this.pattern,this.config.content??"")]}},WC=QC,ZC=class extends sr{constructor(e){super(),this.tokenizers=(e.pretokenizers??[]).map(n=>ex(n))}pre_tokenize_text(e,n){return this.tokenizers.reduce((r,s)=>s?s.pre_tokenize(r,n):r,[e])}},KC=ZC,JC=class extends sr{pre_tokenize_text(e){return sC(e)}},ek=JC,tk=class extends sr{constructor(e){super(),this.config=e,this._length=e.length}pre_tokenize_text(e){const n=[];for(let r=0;rthis.max_input_chars_per_word){n.push(this.unk_token);continue}let o=!1,c=0;const u=[];for(;c0&&(p=this.config.continuing_subword_prefix+p),this.tokens_to_ids.has(p)){h=p;break}--d}if(h===null){o=!0;break}u.push(h),c=d}o?n.push(this.unk_token):n.push(...u)}return n}},r1=sk,s1=class tx{constructor(n,r){this.is_leaf=n,this.children=r}static default(){return new tx(!1,new Map)}},ik=class{constructor(){this.root=s1.default()}extend(e){for(const n of e)this.push(n)}push(e){let n=this.root;for(const r of e){let s=n.children.get(r);s===void 0&&(s=s1.default(),n.children.set(r,s)),n=s}n.is_leaf=!0}*common_prefix_search(e){let n=this.root;if(n===void 0)return;let r="";for(const s of e){if(r+=s,n=n.children.get(s),n===void 0)return;n.is_leaf&&(yield r)}}},ok=ik,g_=class nx{constructor(n,r,s,o,c){this.token_id=n,this.node_id=r,this.pos=s,this.length=o,this.score=c,this.prev=null,this.backtrace_score=0}clone(){const n=new nx(this.token_id,this.node_id,this.pos,this.length,this.score);return n.prev=this.prev,n.backtrace_score=this.backtrace_score,n}},lk=class{constructor(e,n,r){this.chars=Array.from(e),this.len=this.chars.length,this.bos_token_id=n,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 g_(this.bos_token_id??0,0,0,0,0),o=new g_(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,n,r,s){const o=this.nodes.length,c=new g_(s,o,e,n,r);this.begin_nodes[e].push(c),this.end_nodes[e+n].push(c),this.nodes.push(c)}viterbi(){const e=this.len;let n=0;for(;n<=e;){if(this.begin_nodes[n].length==0)return[];for(let u of this.begin_nodes[n]){u.prev=null;let d=0,h=null;for(let p of this.end_nodes[n]){const g=p.backtrace_score+u.score;(h===null||g>d)&&(h=p.clone(),d=g)}if(h!==null)u.prev=h,u.backtrace_score=d;else return[]}++n}const r=[],o=this.begin_nodes[e][0].prev;if(o===null)return[];let c=o.clone();for(;c.prev!==null;)r.push(c.clone()),c=c.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(n=>this.piece(n))}token_ids(){return this.viterbi().map(n=>n.token_id)}},ck=lk;function uk(e){if(e.length===0)throw new Error("Array must not be empty");let n=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=n,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.unk_token=this.vocab[this.unk_token_id],this.min_score=uk(this.scores)[0],this.unk_score=this.min_score-10,this.scores[this.unk_token_id]=this.unk_score,this.trie=new ok,this.trie.extend(this.vocab),this.fuse_unk=!0}populate_nodes(e){const n=e.chars,r=1;let s=0;for(;sr>s,n=1/0){this._heap=[],this._comparator=e,this._max_size=n}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 n of e)if(this.size0&&this._swap(0,n),this._heap.pop(),this._sift_down(),e}replace(e){const n=this.peek();return this._heap[0]=e,this._sift_down(),n}_parent(e){return(e+1>>>1)-1}_left(e){return(e<<1)+1}_right(e){return e+1<<1}_greater(e,n){return this._comparator(this._heap[e],this._heap[n])}_swap(e,n){const r=this._heap[e];this._heap[e]=this._heap[n],this._heap[n]=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()}},mk=pk,_k=class extends Ch{constructor(e){super(e),this.tokens_to_ids=jg(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 n=Array.isArray(e.merges[0]);this.merges=n?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 mk(this.cache_capacity)}clear_cache(){this.cache.clear()}bpe(e){if(e.length===0)return[];const n=this.cache.get(e);if(n!==void 0)return n;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 hk((d,h)=>d.score`<0x${u.toString(16).toUpperCase().padStart(2,"0")}>`);c.every(u=>this.tokens_to_ids.has(u))?n.push(...c):n.push(this.unk_token)}else n.push(this.unk_token)}return n}},o1=_k,gk=class extends Ch{constructor(e,n){super(e);const r=e.vocab;this.tokens_to_ids=jg(n.target_lang?r[n.target_lang]:r),this.bos_token=n.bos_token,this.bos_token_id=this.tokens_to_ids.get(this.bos_token),this.eos_token=n.eos_token,this.eos_token_id=this.tokens_to_ids.get(this.eos_token),this.pad_token=n.pad_token,this.pad_token_id=this.tokens_to_ids.get(this.pad_token),this.unk_token=n.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}},vk=gk;function yk(e,n){switch(e.type){case"WordPiece":return new r1(e);case"Unigram":return new i1(e,n.eos_token);case"BPE":return new o1(e);default:if(e.vocab)return Array.isArray(e.vocab)?new i1(e,n.eos_token):Object.hasOwn(e,"continuing_subword_prefix")&&Object.hasOwn(e,"unk_token")?Object.hasOwn(e,"merges")?new o1(e):new r1(e):new vk(e,{target_lang:n.target_lang,bos_token:n.bos_token,eos_token:n.eos_token,pad_token:n.pad_token,unk_token:n.unk_token});throw new Error(`Unknown TokenizerModel type: ${e==null?void 0:e.type}`)}}var wk=yk,bk=class extends Hu{constructor(e){super(),this.config=e}_call(e,...n){return this.post_process(e,...n)}},Yu=bk,Mk=class extends Yu{post_process(e,n=null,r=!0){const s=n===null?this.config.single:this.config.pair;let o=[],c=[];for(const u of s)"SpecialToken"in u?r&&(o.push(u.SpecialToken.id),c.push(u.SpecialToken.type_id)):"Sequence"in u&&(u.Sequence.id==="A"?(o=nr(o,e),c=nr(c,new Array(e.length).fill(u.Sequence.type_id))):u.Sequence.id==="B"&&(o=nr(o,n),c=nr(c,new Array(n.length).fill(u.Sequence.type_id))));return{tokens:o,token_type_ids:c}}},xk=Mk,Tk=class extends Yu{post_process(e,n=null){return{tokens:e,tokens_pair:n}}},Sk=Tk,Ek=class extends Yu{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,n=null,r=!0){r&&(e=nr([this.cls[0]],e,[this.sep[0]]));let s=new Array(e.length).fill(0);if(n){const o=[],c=r?[this.sep[0]]:[];e=nr(e,o,n,c),s=nr(s,new Array(n.length+o.length+c.length).fill(1))}return{tokens:e,token_type_ids:s}}},Ak=Ek,Ck=class extends Yu{constructor(e){super(e),this.sep=e.sep,this.cls=e.cls}post_process(e,n,r=!0){r&&(e=nr([this.cls[0]],e,[this.sep[0]]));let s=new Array(e.length).fill(0);if(n){const o=r?[this.sep[0]]:[],c=r?[this.sep[0]]:[];e=nr(e,o,n,c),s=nr(s,new Array(n.length+o.length+c.length).fill(1))}return{tokens:e,token_type_ids:s}}},kk=Ck,Ok=class extends Yu{constructor(e){super(e),this.processors=(e.processors??[]).map(n=>ax(n))}post_process(e,n=null,r=!0){let s={tokens:e,tokens_pair:n};for(const o of this.processors)s=o.post_process(s.tokens,s.tokens_pair,r);return s}},zk=Ok;function Lk(e){if(e===null)return null;switch(e.type){case"TemplateProcessing":return new xk(e);case"ByteLevel":return new Sk(e);case"BertProcessing":return new Ak(e);case"RobertaProcessing":return new kk(e);case"Sequence":return new zk(e);default:throw new Error(`Unknown PostProcessor type: ${e.type}`)}}var ax=Lk,Nk=class extends Hu{constructor(e){super(),this.config=e,this.added_tokens=[],this.end_of_word_suffix=null,this.trim_offsets="trim_offsets"in e?e.trim_offsets:!1}_call(e){return this.decode(e)}decode(e){return this.decode_chain(e).join("")}},ir=Nk,Dk=class extends ir{constructor(e){super(e),this.byte_decoder=WA,this.text_decoder=new TextDecoder("utf-8",{fatal:!1,ignoreBOM:!0}),this.end_of_word_suffix=null}convert_tokens_to_string(e){const n=e.join(""),r=new Uint8Array([...n].map(s=>this.byte_decoder[s]));return this.text_decoder.decode(r)}decode_chain(e){const n=[];let r=[];for(const s of e)this.added_tokens.find(o=>o.content===s)!==void 0?(r.length>0&&(n.push(this.convert_tokens_to_string(r)),r=[]),n.push(s)):r.push(s);return r.length>0&&n.push(this.convert_tokens_to_string(r)),n}},Fk=Dk,Bk=class extends ir{constructor(e){super(e),this.cleanup=e.cleanup}decode_chain(e){return e.map((n,r)=>{if(r!==0){const s=this.config.prefix;s&&n.startsWith(s)?n=n.replace(s,""):n=" "+n}return this.cleanup&&(n=Gg(n)),n})}},Pk=Bk,Rk=class extends ir{constructor(e){super(e),this.replacement=e.replacement??"▁"}decode_chain(e){const n=[];for(let r=0;rn.replaceAll(this.suffix,r===e.length-1?"":" "))}},Gk=Ik,jk=class extends ir{constructor(e){super(e),this.pad_token=e.pad_token??"",this.word_delimiter_token=e.word_delimiter_token??"",this.cleanup=e.cleanup}convert_tokens_to_string(e){if(e.length===0)return"";const n=[e[0]];for(let o=1;oo!==this.pad_token).join("");return this.cleanup&&(s=Gg(s).replaceAll(this.word_delimiter_token," ").trim()),s}decode_chain(e){return[this.convert_tokens_to_string(e)]}},Vk=jk,qk=class extends ir{constructor(e){super(e),this.decoders=(e.decoders??[]).map(n=>rx(n))}decode_chain(e){return this.decoders.reduce((n,r)=>r.decode_chain(n),e)}},$k=qk,Hk=class extends ir{decode_chain(e){const n=Eh(this.config.pattern),r=this.config.content??"";return n===null?e:e.map(s=>s.replaceAll(n,r))}},Yk=Hk,Xk=class extends ir{decode_chain(e){return[e.join("")]}},Qk=Xk,Wk=class extends ir{constructor(e){super(e),this.content=e.content??"",this.start=e.start??0,this.stop=e.stop??0}decode_chain(e){return e.map(n=>{let r=0;for(let o=0;o")){const c=parseInt(s.slice(3,5),16);isNaN(c)||(o=c)}if(o!==null)r.push(o);else{if(r.length>0){const c=this.text_decoder.decode(Uint8Array.from(r));n.push(c),r=[]}n.push(s)}}if(r.length>0){const s=this.text_decoder.decode(Uint8Array.from(r));n.push(s),r=[]}return n}},Jk=Kk;function eO(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 Uk(e);case"BPEDecoder":return new Gk(e);case"CTC":return new Vk(e);case"Sequence":return new $k(e);case"Replace":return new Yk(e);case"Fuse":return new Qk(e);case"Strip":return new Zk(e);case"ByteFallback":return new Jk(e);default:throw new Error(`Unknown Decoder type: ${e.type}`)}}var rx=eO,tO=class{constructor(e,n){const r=a1(e,"Tokenizer",["model","decoder","post_processor","pre_tokenizer","normalizer"]);if(r)throw new Error(r);const s=a1(n,"Config");if(s)throw new Error(s);this.tokenizer=e,this.config=n,this.normalizer=JM(this.tokenizer.normalizer),this.pre_tokenizer=ex(this.tokenizer.pre_tokenizer),this.model=wk(this.tokenizer.model,this.config),this.post_processor=ax(this.tokenizer.post_processor),this.decoder=rx(this.tokenizer.decoder),this.special_tokens=[],this.all_special_ids=[],this.added_tokens=[];const o=[],c=[];this.added_tokens_map=new Map;for(const u of this.tokenizer.added_tokens){const d=new XA(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 h=this.normalizer(d.content);c.push(h),this.added_tokens_map.set(h,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 t1(o),this.splitter_normalized=new t1(c),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:n=null,add_special_tokens:r=!0,return_token_type_ids:s=null}={}){const{tokens:o,token_type_ids:c}=this.tokenize_helper(e,{text_pair:n,add_special_tokens:r}),u=o.map(h=>{var p;return((p=this.added_tokens_map.get(h))==null?void 0:p.id)??this.model.tokens_to_ids.get(h)??this.model.unk_token_id}),d={ids:u,tokens:o,attention_mask:new Array(u.length).fill(1)};return s&&c&&(d.token_type_ids=c),d}decode(e,n={}){if(!Array.isArray(e)||e.length===0||!tC(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);n.skip_special_tokens&&(r=r.filter(o=>!this.special_tokens.includes(o)));let s=this.decoder?this.decoder(r):r.join(" ");return 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E1=Promise.resolve();async function _x(e,n){const r=()=>e.run(n);return await(px?E1=E1.then(r):r())}function gx(e){return e instanceof ii.Tensor}var vt=ii==null?void 0:ii.env;vt.logLevel=O3[hx];var W1;if(vt!=null&&vt.wasm){if(!(typeof ServiceWorkerGlobalScope<"u"&&self instanceof ServiceWorkerGlobalScope)&&((W1=vt.versions)!=null&&W1.web)&&!vt.wasm.wasmPaths){const e=`https://cdn.jsdelivr.net/npm/onnxruntime-web@${vt.versions.web}/dist/`;vt.wasm.wasmPaths=Nt.IS_SAFARI?{mjs:`${e}ort-wasm-simd-threaded.mjs`,wasm:`${e}ort-wasm-simd-threaded.wasm`}:{mjs:`${e}ort-wasm-simd-threaded.asyncify.mjs`,wasm:`${e}ort-wasm-simd-threaded.asyncify.wasm`}}vt.wasm.proxy=!1}vt!=null&&vt.webgpu&&(vt.webgpu.powerPreference="high-performance");function Vg(){var e;return(e=vt==null?void 0:vt.wasm)==null?void 0:e.proxy}pa.backends.onnx=vt;var ni=async(e,n,r)=>{const s=await mx(new Uint8Array(e),n);return(async o=>{const 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this._bilinear_interpolate_4d||(this._bilinear_interpolate_4d=ni([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=ni([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=ni([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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c.constructor(c.length/u[r]);o!==null&&h.fill(o);for(let p=0;p=0;--y){const S=u[y];if(y!==r){const E=w%S;g+=E*b,b*=d[y]}w=Math.floor(w/S)}h[g]=e(h[g],c[p],p,g)}return s||d.splice(r,1),[n.type,h,d]}function I3(e,n=null,r=1,s=!1){const o=e.data,c=e.dims;if(n===null){const b=o.reduce((z,D)=>z+D,0)/o.length,S=Math.sqrt(o.reduce((z,D)=>z+(D-b)**2,0)/(o.length-r)),E=new we(e.type,[b],[]);return[new we(e.type,[S],[]),E]}n=Or(n,c.length);const u=qg(e,n,s),d=u.data,[h,p,g]=Gu((w,b,S,E)=>w+(b-d[E])**2,e,n,s);for(let w=0;wp+g,0);return new we(e.type,[h/o.length],[])}n=Or(n,s.length);const[c,u,d]=Gu((h,p)=>h+p,e,n,r);if(s[n]!==1)for(let h=0;h=0;--r)n[r]=s,s*=e[r];return n}function $g(e,n,r,s){const o=e.reduce((c,u)=>c*u,1);return new we(r,new s(o).fill(n),e)}function zn(e,n){let r,s;if(typeof n=="number")r="float32",s=Float32Array;else if(typeof n=="bigint")r="int64",s=BigInt64Array;else if(typeof n=="boolean")r="bool",s=Uint8Array;else throw new Error(`Unsupported data type: ${typeof n}`);return 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Specify `power` to fix this issue.");if(!g)throw new Error("`preemphasis_htk_flavor=false` is not currently supported.");if(u)switch(d){case"reflect":{const R=Math.floor((o-1)/2)+1;e=Wz(e,R,R);break}case"constant":{const R=Math.floor(o/2),te=new e.constructor(e.length+2*R);te.set(e,R),e=te;break}default:throw new Error(`pad_mode="${d}" not implemented yet.`)}let ce=Math.floor(1+Math.floor((e.length-r)/s));D!==null&&cece?j&&(me=P):me=he=P);const pe=new _3(o),ne=new Float64Array(o),ee=new Float64Array(pe.outputBufferSize),Me=new Float32Array(oe*me);for(let R=0;R=1;--H)ne[H]-=p*ne[H-1];ne[0]*=1-p}for(let H=0;HMath.pow(d,.85));break;default:throw new Error(`Unknown window type ${n}.`)}if(r&&(u=u.subarray(0,e)),s===null)return u;if(e>s)throw new Error(`Length of the window (${e}) may not be larger than frame_length (${s})`);return u}function Jz(e,n){const r=e.reduce((c,u)=>c+u.length,0),s=new ArrayBuffer(44),o=new DataView(s);return Uf(o,0,"RIFF"),o.setUint32(4,36+r*4,!0),Uf(o,8,"WAVE"),Uf(o,12,"fmt "),o.setUint32(16,16,!0),o.setUint16(20,3,!0),o.setUint16(22,1,!0),o.setUint32(24,n,!0),o.setUint32(28,n*4,!0),o.setUint16(32,4,!0),o.setUint16(34,32,!0),Uf(o,36,"data"),o.setUint32(40,r*4,!0),new Blob([s,...e.map(c=>c.buffer)],{type:"audio/wav"})}function Uf(e,n,r){for(let s=0;ss+o.length,0),n=new Float32Array(e);let r=0;for(const s of this.audio)n.set(s,r),r+=s.length;return n}else return this.audio}toBlob(){let e=this.audio;return e instanceof Float32Array&&(e=[e]),Jz(e,this.sampling_rate)}async save(e){return Cx(e,this.toBlob())}},tL=class extends Jn{constructor(e){super(e);const n=this.config.sampling_rate,r=li(257,this.config.num_mel_bins,20,Math.floor(n/2),n,null,"kaldi",!0);this.mel_filters=r,this.window=no(400,"hann",{periodic:!1}),this.mean=this.config.mean,this.std=this.config.std}async _extract_fbank_features(e,n){return to(e,this.window,400,160,{fft_length:512,power:2,center:!1,preemphasis:.97,mel_filters:this.mel_filters,log_mel:"log",mel_floor:1192092955078125e-22,remove_dc_offset:!0,max_num_frames:n,transpose:!0})}async _call(e){Pa(e,"ASTFeatureExtractor");const n=await this._extract_fbank_features(e,this.config.max_length);if(this.config.do_normalize){const r=this.std*2,s=n.data;for(let o=0;o0)if(r==="rand_trunc"){const u=Math.floor(Math.random()*(c+1));e=e.subarray(u,u+n),o=await this._extract_fbank_features(e,this.mel_filters_slaney,this.config.nb_max_samples)}else throw new Error(`Truncation strategy "${r}" not implemented`);else{if(c<0){let u=new Float64Array(n);if(u.set(e),s==="repeat")for(let d=e.length;dn&&(e=e.slice(0,n)),s&&e.length%o!==0){const d=o-e.length%o,h=new Float64Array(e.length+d);h.set(e),this.config.padding_value!==0&&h.fill(this.config.padding_value,e.length),e=h}const c=await this._extract_fbank_features(e,this.config.max_length),u=zn([1,c.dims[0]],!0);return{input_features:c.unsqueeze_(0),input_features_mask:u}}},sL=class extends Jn{async _call(e){Pa(e,"MoonshineFeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));const n=[1,e.length];return{input_values:new we("float32",e,n)}}},iL=1e-5,oL=class extends Jn{constructor(e){var s;super(e),(s=this.config).mel_filters??(s.mel_filters=li(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 n=no(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(n,r)}async _extract_fbank_features(e){const n=this.config.preemphasis;e=new Float64Array(e);for(let s=e.length-1;s>=1;--s)e[s]-=n*e[s-1];return await to(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){Pa(e,"ParakeetFeatureExtractor");const n=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=n.data;s.fill(0,r*n.dims[1]);const[o,c]=n.dims,u=new Float64Array(c),d=new Float64Array(c);for(let g=0;g1?r-1:1;for(let g=0;g({id:d,start:h*r,end:p*r,confidence:g/(p-h)})))}return s}},lL=class extends Jn{constructor(e){super(e);const n=this.config.sampling_rate,r=li(257,this.config.num_mel_bins,20,Math.floor(n/2),n,null,"kaldi",!0);this.mel_filters=r,this.window=no(400,"povey",{periodic:!1})}async _extract_fbank_features(e,n){return e=e.map(r=>r*32768),to(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:n,transpose:!0})}async _call(e,{padding:n=!0,pad_to_multiple_of:r=2,do_normalize_per_mel_bins:s=!0,return_attention_mask:o=!0}={}){Pa(e,"SeamlessM4TFeatureExtractor");let c=await this._extract_fbank_features(e,this.config.max_length);if(s){const[b,S]=c.dims,E=c.data;for(let O=0;O0){const z=new Float32Array(S*(b+O));z.set(E),z.fill(this.config.padding_value,E.length);const D=b+O;c=new we(c.type,z,[D,S]),o&&(u=new we("int64",new BigInt64Array(D),[1,D]),u.data.fill(1n,0,b))}}const[d,h]=c.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=c.view(1,Math.floor(d/p),h*p),w={input_features:y};if(o){const b=y.dims[1],S=new BigInt64Array(b);if(u){const E=u.data;for(let O=1,z=0;Oo+c,0)/e.length,s=e.reduce((o,c)=>o+(c-r)**2,0)/e.length;return e.map(o=>(o-r)/Math.sqrt(s+1e-7))}async _call(e){Pa(e,"Wav2Vec2FeatureExtractor"),e instanceof Float64Array&&(e=new Float32Array(e));let n=e;this.config.do_normalize&&(n=this._zero_mean_unit_var_norm(n));const r=[1,n.length];return{input_values:new we("float32",n,r),attention_mask:new we("int64",new BigInt64Array(n.length).fill(1n),r)}}},fL=class extends Jn{constructor(e){super(e);const n=this.config.sampling_rate,r=li(257,this.config.num_mel_bins,20,Math.floor(n/2),n,null,"kaldi",!0);this.mel_filters=r,this.window=no(400,"hamming",{periodic:!1}),this.min_num_frames=this.config.min_num_frames}async _extract_fbank_features(e){return e=e.map(n=>n*32768),to(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){Pa(e,"WeSpeakerFeatureExtractor");const n=(await this._extract_fbank_features(e)).unsqueeze_(0);if(this.config.fbank_centering_span===null){const r=n.mean(1).data,s=n.data,[o,c,u]=n.dims;for(let d=0;ds?(e.length>this.config.n_samples&&console.warn("Attempting to extract features for audio longer than 30 seconds. 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Please report this at ${Yg}.`);return new o(r)}},Vf,pL=(Vf=class extends At{async _call(e,n=null){const r=this.tokenizer(e),s=n?await this.feature_extractor(n):{};return{...r,...s}}},L(Vf,"tokenizer_class",$e),L(Vf,"feature_extractor_class",ms),Vf),mL={},_g=mL,qi,Dx,ai,Ja=Nt.IS_BROWSER_ENV||Nt.IS_WEBWORKER_ENV;if(Ja)qi=(e,n)=>{if(!self.OffscreenCanvas)throw new Error("OffscreenCanvas not supported by this browser.");return new self.OffscreenCanvas(e,n)},ai=self.createImageBitmap,Dx=self.ImageData;else if(_g)ai=async e=>{const r=(await e.metadata()).channels,{data:s,info:o}=await e.rotate().raw().toBuffer({resolveWithObject:!0}),c=new rr(new Uint8ClampedArray(s),o.width,o.height,o.channels);return r!==void 0&&r!==o.channels&&c.convert(r),c};else throw new Error("Unable to load image processing library.");var _L={0:"nearest",1:"lanczos",2:"bilinear",3:"bicubic",4:"box",5:"hamming"},gL=new Map([["png","image/png"],["jpg","image/jpeg"],["jpeg","image/jpeg"],["gif","image/gif"]]),rr=class kr{constructor(n,r,s,o){this.data=n,this.width=r,this.height=s,this.channels=o}get size(){return[this.width,this.height]}static async read(n){if(n instanceof kr)return n;if(typeof n=="string"||n instanceof URL)return await this.fromURL(n);if(n instanceof Blob)return await this.fromBlob(n);if(typeof HTMLCanvasElement<"u"&&n instanceof HTMLCanvasElement||typeof OffscreenCanvas<"u"&&n instanceof OffscreenCanvas)return this.fromCanvas(n);throw new Error(`Unsupported input type: ${typeof n}`)}static fromCanvas(n){if(!Ja)throw new Error("fromCanvas() is only supported in browser environments.");const s=n.getContext("2d").getImageData(0,0,n.width,n.height).data;return new kr(s,n.width,n.height,4)}static async fromURL(n){const r=await vh(n);if(r.status!==200)throw new Error(`Unable to read image from "${n}" (${r.status} ${r.statusText})`);const s=await r.blob();return this.fromBlob(s)}static async fromBlob(n){if(Ja){const r=await ai(n),s=qi(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 n.arrayBuffer());return await ai(r)}}static fromTensor(n,r="CHW"){if(n.dims.length!==3)throw new Error(`Tensor should have 3 dimensions, but has ${n.dims.length} dimensions.`);if(r==="CHW")n=n.transpose(1,2,0);else if(r!=="HWC")throw new Error(`Unsupported channel format: ${r}`);if(!(n.data instanceof Uint8ClampedArray||n.data instanceof Uint8Array))throw new Error(`Unsupported tensor type: ${n.type}`);switch(n.dims[2]){case 1:case 2:case 3:case 4:return new kr(n.data,n.dims[1],n.dims[0],n.dims[2]);default:throw new Error(`Unsupported number of channels: ${n.dims[2]}`)}}grayscale(){if(this.channels===1)return this;const n=new Uint8ClampedArray(this.width*this.height*1);switch(this.channels){case 3:case 4:for(let r=0,s=0;r=0?h=s:g=-s,o>=0?p=o:y=-o,d.drawImage(u,h,p,n,r,g,y,n,r),new kr(d.getImageData(0,0,n,r).data,n,r,4).convert(c)}else{let c=this.toSharp();if(s>=0&&o>=0)c=c.extract({left:Math.floor(s),top:Math.floor(o),width:n,height:r});else if(s<=0&&o<=0){const u=Math.floor(-o),d=Math.floor(-s);c=c.extend({top:u,left:d,right:n-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 h=[0,0],p=0;s<0?(h[0]=Math.floor(-s),h[1]=n-this.width-h[0]):p=Math.floor(s),c=c.extend({top:u[0],bottom:u[1],left:h[0],right:h[1]}).extract({left:p,top:d,width:n,height:r})}return await ai(c)}}async toBlob(n="image/png",r=1){if(!Ja)throw new Error("toBlob() is only supported in browser environments.");return await this.toCanvas().convertToBlob({type:n,quality:r})}toTensor(n="CHW"){let r=new we("uint8",new Uint8Array(this.data),[this.height,this.width,this.channels]);if(n!=="HWC")if(n==="CHW")r=r.permute(2,0,1);else throw new Error(`Unsupported channel format: ${n}`);return r}toCanvas(){if(!Ja)throw new Error("toCanvas() is only supported in browser environments.");const n=this.clone().rgba(),r=qi(n.width,n.height),s=new Dx(n.data,n.width,n.height);return r.getContext("2d").putImageData(s,0,0),r}split(){const{data:n,width:r,height:s,channels:o}=this,c=n.constructor,u=n.length/o,d=Array.from({length:o},()=>new c(u));for(let h=0;hnew kr(h,r,s,1))}_update(n,r,s,o=null){return this.data=n,this.width=r,this.height=s,o!==null&&(this.channels=o),this}clone(){return new kr(this.data.slice(),this.width,this.height,this.channels)}convert(n){if(this.channels===n)return this;switch(n){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(n){if(Ja){if(Nt.IS_WEBWORKER_ENV)throw new Error("Unable to save an image from a Web Worker.");const r=n.split(".").pop().toLowerCase(),s=gL.get(r)??"image/png",o=await this.toBlob(s);return Cx(n,o)}else if(Nt.IS_FS_AVAILABLE)await this.toSharp().toFile(n);else throw new Error("Unable to save the image because filesystem is disabled in this environment.")}toSharp(){if(Ja)throw new Error("toSharp() is only supported in server-side environments.");return _g(this.data,{raw:{width:this.width,height:this.height,channels:this.channels}})}};rr.read.bind(rr);function D1(e,n,r=0,s=null){const o=e/n;let c=v3(o)*n;return s!==null&&c>s&&(c=Math.floor(o)*n),cn&&z.push(P)}else{let P=Qt(O.data)[1];if(P===h-1||(D=bn(O.data),D[P]G*y[(K+1)%2])),w.boxes.push(j),w.classes.push(P),w.scores.push(D[P])}}p.push(w)}return p}function Bx(e,n=null){const r=e.logits,s=r.dims[0];if(n!==null&&n.length!==s)throw Error("Make sure that you pass in as many target sizes as the batch dimension of the logits");const o=[];for(let c=0;cy[z]&&(y[z]=O[z],w[z]=E)}const b=new Array(d.dims[0]);for(let E=0;EE!==void 0);o.push({segmentation:g,labels:S})}return o}function vL(e,n,r,s){const o=[],c=[],u=[];for(let d=0;dr&&(o.push(p),c.push(w),u.push(g))}return[o,c,u]}function yL(e,n,r,s=.5,o=.8){const c=[];let u=0,d=0;const h=n[r].data;for(let g=0;g=s&&++d;let p=u>0&&d>0;return p&&(p=u/d>o),[p,c]}function wL(e,n,r,s,o,c=null,u=null){const[d,h]=u??e[0].dims,p=new we("int32",new Int32Array(d*h),[d,h]),g=[];if(u!==null)for(let E=0;Ew[D]&&(y[D]=E,w[D]=z[D])}let b=0;const S=p.data;for(let E=0;E200)throw new Error(`absolute aspect ratio must be smaller than 200, got ${Math.max(e,n)/Math.min(e,n)}`);let c=Math.round(e/r)*r,u=Math.round(n/r)*r;if(c*u>o){const d=Math.sqrt(e*n/o);c=Math.floor(e/d/r)*r,u=Math.floor(n/d/r)*r}else if(c*uo?h=Math.floor(o*d/s):o>s&&(d=Math.floor(s*h/o)),await e.resize(h,d,{resample:r}))}async crop_margin(e,n=200){const r=e.clone().grayscale(),s=fg(r.data)[0],c=Qt(r.data)[0]-s;if(c===0)return e;const u=n/255;let d=r.width,h=r.height,p=0,g=0;const y=r.data;for(let w=0;wthis.preprocess(o)));return{pixel_values:Cl(r.map(o=>o.pixel_values),0),original_sizes:r.map(o=>o.original_size),reshaped_input_sizes:r.map(o=>o.reshaped_input_size)}}static async from_pretrained(e,n={}){const r=await Lr(e,Qg,!0,n);return new this(r)}},bh={};Sl(bh,{BeitFeatureExtractor:()=>ML,BitImageProcessor:()=>xL,CLIPFeatureExtractor:()=>SL,CLIPImageProcessor:()=>Ux,ChineseCLIPFeatureExtractor:()=>TL,ConvNextFeatureExtractor:()=>EL,ConvNextImageProcessor:()=>Ix,DINOv3ViTImageProcessor:()=>kL,DPTFeatureExtractor:()=>zL,DPTImageProcessor:()=>Vx,DeiTFeatureExtractor:()=>AL,DeiTImageProcessor:()=>Gx,DetrFeatureExtractor:()=>CL,DetrImageProcessor:()=>jx,DonutFeatureExtractor:()=>OL,DonutImageProcessor:()=>Zg,EfficientNetImageProcessor:()=>LL,GLPNFeatureExtractor:()=>NL,GroundingDinoImageProcessor:()=>DL,Idefics3ImageProcessor:()=>F1,ImageFeatureExtractor:()=>He,ImageProcessor:()=>He,JinaCLIPImageProcessor:()=>BL,LlavaOnevisionImageProcessor:()=>PL,Mask2FormerImageProcessor:()=>UL,MaskFormerFeatureExtractor:()=>RL,MaskFormerImageProcessor:()=>Kg,MobileNetV1FeatureExtractor:()=>IL,MobileNetV1ImageProcessor:()=>qx,MobileNetV2FeatureExtractor:()=>GL,MobileNetV2ImageProcessor:()=>$x,MobileNetV3FeatureExtractor:()=>jL,MobileNetV3ImageProcessor:()=>Hx,MobileNetV4FeatureExtractor:()=>VL,MobileNetV4ImageProcessor:()=>Yx,MobileViTFeatureExtractor:()=>qL,MobileViTImageProcessor:()=>Xx,NougatImageProcessor:()=>$L,OwlViTFeatureExtractor:()=>HL,OwlViTImageProcessor:()=>Jg,Owlv2ImageProcessor:()=>YL,Phi3VImageProcessor:()=>QL,PixtralImageProcessor:()=>WL,PvtImageProcessor:()=>ZL,Qwen2VLImageProcessor:()=>KL,RTDetrImageProcessor:()=>JL,Sam2ImageProcessor:()=>x_,Sam3ImageProcessor:()=>x_,SamImageProcessor:()=>x_,SapiensFeatureExtractor:()=>e4,SapiensImageProcessor:()=>Qx,SegformerFeatureExtractor:()=>t4,SegformerImageProcessor:()=>Wx,SiglipImageProcessor:()=>n4,SmolVLMImageProcessor:()=>F1,Swin2SRImageProcessor:()=>a4,VLMImageProcessor:()=>FL,ViTFeatureExtractor:()=>r4,ViTImageProcessor:()=>Zx,VitMatteImageProcessor:()=>s4,VitPoseImageProcessor:()=>i4,YolosFeatureExtractor:()=>o4,YolosImageProcessor:()=>Kx});var ML=class extends He{},xL=class extends He{},TL=class extends He{},Ux=class extends He{},SL=class extends Ux{},Ix=class extends He{constructor(e){super(e),this.crop_pct=this.config.crop_pct??224/256}async resize(e){var r;const n=(r=this.size)==null?void 0:r.shortest_edge;if(n===void 0)throw new Error("Size dictionary must contain 'shortest_edge' key.");if(n<384){const s=Math.floor(n/this.crop_pct),[o,c]=this.get_resize_output_image_size(e,{shortest_edge:s});e=await e.resize(o,c,{resample:this.resample}),e=await e.center_crop(n,n)}else e=await e.resize(n,n,{resample:this.resample});return e}},EL=class extends Ix{},Gx=class extends He{},AL=class extends Gx{},jx=class extends He{async _call(e){const n=await super._call(e),r=[n.pixel_values.dims[0],64,64],s=zn(r,1n);return{...n,pixel_mask:s}}post_process_object_detection(...e){return Oh(...e)}post_process_panoptic_segmentation(...e){return Px(...e)}post_process_instance_segmentation(...e){return Rx(...e)}},CL=class extends jx{},kL=class extends He{},Zg=class extends He{pad_image(e,n,r,s={}){const[o,c,u]=n;let d=this.image_mean;Array.isArray(this.image_mean)||(d=new Array(u).fill(d));let h=this.image_std;Array.isArray(h)||(h=new Array(u).fill(d));const p=d.map((g,y)=>-g/h[y]);return super.pad_image(e,n,r,{center:!0,constant_values:p,...s})}},OL=class extends Zg{},Vx=class extends He{},zL=class extends Vx{},LL=class extends He{constructor(e){super(e),this.include_top=this.config.include_top??!0,this.include_top&&(this.image_std=this.image_std.map(n=>n*n))}},NL=class extends He{},DL=class extends He{async _call(e){const n=await super._call(e),r=n.pixel_values.dims,s=Fa([r[0],r[2],r[3]]);return{...n,pixel_mask:s}}},F1=class extends He{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,n){let[r,s]=e.dims.slice(-2);const o=s/r;return s>=r?(s=Math.ceil(s/n)*n,r=Math.floor(s/o),r=Math.ceil(r/n)*n):(r=Math.ceil(r/n)*n,s=Math.floor(r*o),s=Math.ceil(s/n)*n),{height:r,width:s}}async _call(e,{do_image_splitting:n=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=[],c=[],u=[];const d=[],h=[];for(const O of s){let z=await Promise.all(O.map(j=>this.preprocess(j)));d.push(...z.map(j=>j.original_size)),h.push(...z.map(j=>j.reshaped_input_size)),z.forEach(j=>j.pixel_values.unsqueeze_(0));const{longest_edge:D}=this.max_image_size;let P;if(n??this.do_image_splitting){let j=new Array(z.length),G=new Array(z.length);P=await Promise.all(z.map(async(K,k)=>{const ce=this.get_resize_for_vision_encoder(K.pixel_values,D),oe=await oi(K.pixel_values,{size:[ce.height,ce.width]}),{frames:he,num_splits_h:me,num_splits_w:pe}=await this.split_image(oe,this.max_image_size);return j[k]=me,G[k]=pe,Pt(he,0)})),c.push(j),u.push(G)}else{const j=[D,D];P=await Promise.all(z.map(G=>oi(G.pixel_values,{size:j}))),c.push(new Array(z.length).fill(0)),u.push(new Array(z.length).fill(0))}o.push(Pt(P,0))}const p=o.length,[g,y,w,b]=o[0].dims;let S,E;if(p===1)S=o[0].unsqueeze_(0),E=zn([p,g,w,b],!0);else{const O=Math.max(...o.map(P=>P.dims.at(0)));E=zn([p,O,w,b],!0);const z=E.data,D=O*w*b;for(let P=0;Pr||u>s){d=Math.ceil(c/r),h=Math.ceil(u/s);const p=Math.ceil(c/d),g=Math.ceil(u/h);for(let b=0;bn*this.rescale_factor)}pad_image(e,n,r,s){return super.pad_image(e,n,r,{constant_values:this.constant_values,center:!0,...s})}},BL=class extends He{constructor(e){const{resize_mode:n,fill_color:r,interpolation:s,size:o,...c}=e,u=n==="squash"?{width:o,height:o}:n==="shortest"?{shortest_edge:o}:{longest_edge:o},d=s==="bicubic"?3:2;super({...c,size:u,resample:d,do_center_crop:!0,crop_size:o,do_normalize:!0})}},PL=class extends He{},Kg=class extends He{post_process_panoptic_segmentation(...e){return Px(...e)}post_process_instance_segmentation(...e){return Rx(...e)}},RL=class extends Kg{},UL=class extends Kg{},qx=class extends He{},IL=class extends qx{},$x=class extends He{},GL=class extends $x{},Hx=class extends He{},jL=class extends Hx{},Yx=class extends He{},VL=class extends Yx{},Xx=class extends He{},qL=class extends Xx{},$L=class extends Zg{},Jg=class extends He{post_process_object_detection(...e){return Oh(...e)}},HL=class extends Jg{},YL=class extends Jg{},ua=336,XL=[2,3],{ceil:b_,floor:ml,sqrt:M_}=Math,QL=class extends He{constructor(e){super({...e,do_normalize:!0,do_pad:!0,pad_size:"custom",do_convert_rgb:!0,do_resize:!0}),this._num_crops=e.num_crops}calc_num_image_tokens_from_image_size(e,n){const{num_img_tokens:r}=this.config;return ml((ml(n/ua)*ml(e/ua)+1)*r+1+(ml(n/ua)+1)*M_(r))}get_resize_output_image_size(e,n){const r=this._num_crops,[s,o]=e.size;let c=s/o,u=1;for(;u*Math.ceil(u/c)<=r;)u+=1;u-=1;const d=Math.floor(u*336),h=Math.floor(d/c);return[d,h]}pad_image(e,n,r,s={}){const[o,c]=n,u=ua*b_(o/ua),d=ua*b_(c/ua),h=[1,1,1].map((p,g)=>(p-this.image_mean[g])/this.image_std[g]);return super.pad_image(e,n,{width:d,height:u},{center:!0,constant_values:h,...s})}async _call(e,{num_crops:n=null}={}){if(this._num_crops=n??(n=this.config.num_crops),n<4||M_(n)%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),c=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 oi(y,{size:[ua,ua],mode:"bicubic"});if(n>0){const E=[],O=M_(n),z=ml(b/O),D=ml(w/O);for(let j=0;jy.map(w=>ua*b_(w/ua))),p=new we("int64",h.flat(),[r,2]),g=h.map(([y,w])=>this.calc_num_image_tokens_from_image_size(w,y));return{pixel_values:d,original_sizes:o,reshaped_input_sizes:c,image_sizes:p,num_img_tokens:g}}},WL=class extends He{get_resize_output_image_size(e,n){const{longest_edge:r}=n;if(r===void 0)throw new Error("size must contain 'longest_edge'");const[s,o]=e.size,c=Math.max(s,o)/r;let u=s,d=o;c>1&&(u=Math.floor(s/c),d=Math.floor(o/c));const{patch_size:h,spatial_merge_size:p}=this.config;if(!p)throw new Error("config must contain 'spatial_merge_size'");const g=h*p,y=Math.floor((u-1)/g)+1,w=Math.floor((d-1)/g)+1;return[y*g,w*g]}},ZL=class extends He{},KL=class extends He{async _call(e,...n){const{pixel_values:r,original_sizes:s,reshaped_input_sizes:o}=await super._call(e,...n);let c=r;const{temporal_patch_size:u,merge_size:d,patch_size:h}=this.config;c.dims[0]===1&&(c=Pt(Array.from({length:u},()=>c),0));const p=c.dims[0]/u,g=c.dims[1],y=Math.floor(c.dims[2]/h),w=Math.floor(c.dims[3]/h),b=c.view(p,u,g,Math.floor(y/d),d,h,Math.floor(w/d),d,h).permute(0,3,6,4,7,2,1,5,8).view(p*y*w,g*u*h*h),S=new we("int64",[p,y,w],[1,3]);return{pixel_values:b,image_grid_thw:S,original_sizes:s,reshaped_input_sizes:o}}},JL=class extends He{post_process_object_detection(...e){return Oh(...e)}},x_=class extends He{reshape_input_points(e,n,r,s=!1){e=structuredClone(e);let o=w1(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 c=0;cs!==n.dims[o]))throw Error(`The first ${r.length} dimensions of 'input_points' and 'input_labels' must be the same.`);return new we("int64",e.flat(1/0).map(BigInt),r)}async _call(e,{input_points:n=null,input_labels:r=null,input_boxes:s=null}={}){const o=await super._call(e);if(n&&(o.input_points=this.reshape_input_points(n,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,n,r,{mask_threshold:s=0,binarize:o=!0,pad_size:c=null}={}){const u=[];c=c??this.pad_size??this.size;const d=[c.height,c.width];for(let h=0;hs&&(b[S]=1);y=new we("bool",b,y.dims)}u.push(y)}return u}generate_crop_boxes(e,n,{crop_n_layers:r=0,overlap_ratio:s=512/1500,points_per_crop:o=32,crop_n_points_downscale_factor:c=1}={}){}},Qx=class extends He{post_process_semantic_segmentation(...e){return Bx(...e)}},e4=class extends Qx{},Wx=class extends He{post_process_semantic_segmentation(...e){return Bx(...e)}},t4=class extends Wx{},n4=class extends He{},a4=class extends He{pad_image(e,n,r,s={}){const[o,c,u]=n;return super.pad_image(e,n,{width:c+(r-c%r)%r,height:o+(r-o%r)%r},{mode:"symmetric",center:!1,constant_values:-1,...s})}},Zx=class extends He{},r4=class extends Zx{},s4=class extends He{async _call(e,n){Array.isArray(e)||(e=[e]),Array.isArray(n)||(n=[n]);const r=await Promise.all(e.map(c=>this.preprocess(c))),s=await Promise.all(n.map(c=>this.preprocess(c,{do_normalize:!1,do_convert_rgb:!1,do_convert_grayscale:!0})));return{pixel_values:Cl(r.map((c,u)=>Pt([c.pixel_values,s[u].pixel_values],0)),0),original_sizes:r.map(c=>c.original_size),reshaped_input_sizes:r.map(c=>c.reshaped_input_size)}}},i4=class extends He{post_process_pose_estimation(e,n,{threshold:r=null}={}){const s=e.tolist(),[o,c,u,d]=e.dims,h=[];for(let p=0;p/gm,bboxes:/([^<]+)?/gm},this.size_per_bin=1e3}construct_prompts(e){typeof e=="string"&&(e=[e]);const n=[];for(const r of e)if(this.task_prompts_without_inputs.has(r))n.push(this.task_prompts_without_inputs.get(r));else{for(const[s,o]of this.task_prompts_with_input)if(r.includes(s)){n.push(o.replaceAll("{input}",r).replaceAll(s,""));break}n.length!==e.length&&n.push(r)}return n}post_process_generation(e,n,r){const s=this.tasks_answer_post_processing_type.get(n)??"pure_text";e=e.replaceAll("","").replaceAll("","");let 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return new we("int64",BigInt64Array.from(e.map(n=>BigInt(n))),[1,e.length])}function o2(e){return new we("bool",[e],[1])}var ye={EncoderOnly:0,EncoderDecoder:1,Seq2Seq:2,Vision2Seq:3,DecoderOnly:4,DecoderOnlyWithoutHead:5,MaskGeneration:6,ImageTextToText:7,Musicgen:8,MultiModality:9,Phi3V:10,AudioTextToText:11,AutoEncoder:12,ImageAudioTextToText:13,Supertonic:14,Chatterbox:15},U1={[ye.DecoderOnly]:{can_generate:!0,forward:hs,prepare_inputs:Mh},[ye.DecoderOnlyWithoutHead]:{can_generate:!1,forward:hs,prepare_inputs:Mh},[ye.Seq2Seq]:{can_generate:!0,forward:Gf,prepare_inputs:xh},[ye.Vision2Seq]:{can_generate:!0,forward:Gf,prepare_inputs:xh},[ye.Musicgen]:{can_generate:!0,forward:Gf},[ye.EncoderDecoder]:{can_generate:!1,forward:Gf},[ye.ImageTextToText]:{can_generate:!0,forward:fN,prepare_inputs:jf},[ye.AudioTextToText]:{can_generate:!0,forward:dN,prepare_inputs:jf},[ye.Phi3V]:{can_generate:!0,prepare_inputs:jf},[ye.ImageAudioTextToText]:{can_generate:!0,prepare_inputs:jf},[ye.MultiModality]:{can_generate:!0},[ye.AutoEncoder]:{can_generate:!1,forward:uN},[ye.Chatterbox]:{can_generate:!0,forward:ci},default:{can_generate:!1,forward:ci}},xl=new Map,tv=new Map,Ml=new Map,Y=class extends Ba{constructor(n,r,s){super();L(this,"main_input_name","input_ids");L(this,"forward_params",["input_ids","attention_mask"]);L(this,"_return_dict_in_generate_keys",null);this.config=n,this.sessions=r,this.configs=s;const o=Ml.get(this.constructor),c=xl.get(o),u=U1[c]??U1.default;this.can_generate=u.can_generate,this._forward=u.forward,this._prepare_inputs_for_generation=u.prepare_inputs,this.can_generate&&this.forward_params.push("past_key_values"),this.custom_config=this.config["transformers.js_config"]??{}}async dispose(){var r;const n=[];for(const s of Object.values(this.sessions))n.push((r=s.release)==null?void 0:r.call(s));return await Promise.all(n)}static async from_pretrained(n,{progress_callback:r=null,config:s=null,cache_dir:o=null,local_files_only:c=!1,revision:u="main",model_file_name:d=null,subfolder:h="onnx",device:p=null,dtype:g=null,use_external_data_format:y=null,session_options:w={}}={}){const b={progress_callback:r,config:s,cache_dir:o,local_files_only:c,revision:u,model_file_name:d,subfolder:h,device:p,dtype:g,use_external_data_format:y,session_options:w},S=Ml.get(this),E=xl.get(S);s=b.config=await n2.from_pretrained(n,b);let O;if(E===ye.DecoderOnly)O=await Promise.all([Zn(n,{model:b.model_file_name??"model"},b,"model"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.Seq2Seq||E===ye.Vision2Seq)O=await Promise.all([Zn(n,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},b,"decoder_model_merged"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.MaskGeneration)O=await Promise.all([Zn(n,{model:"vision_encoder",prompt_encoder_mask_decoder:"prompt_encoder_mask_decoder"},b)]);else if(E===ye.EncoderDecoder)O=await Promise.all([Zn(n,{model:"encoder_model",decoder_model_merged:"decoder_model_merged"},b,"decoder_model_merged")]);else if(E===ye.ImageTextToText){const z={embed_tokens:"embed_tokens",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};s.is_encoder_decoder&&(z.model="encoder_model"),O=await Promise.all([Zn(n,z,b,"decoder_model_merged"),ds(n,{generation_config:"generation_config.json"},b)])}else if(E===ye.AudioTextToText){const z={embed_tokens:"embed_tokens",audio_encoder:"audio_encoder",decoder_model_merged:"decoder_model_merged"};O=await Promise.all([Zn(n,z,b,"decoder_model_merged"),ds(n,{generation_config:"generation_config.json"},b)])}else if(E===ye.ImageAudioTextToText){const z={embed_tokens:"embed_tokens",audio_encoder:"audio_encoder",vision_encoder:"vision_encoder",decoder_model_merged:"decoder_model_merged"};O=await Promise.all([Zn(n,z,b),ds(n,{generation_config:"generation_config.json"},b)])}else if(E===ye.Musicgen)O=await Promise.all([Zn(n,{model:"text_encoder",decoder_model_merged:"decoder_model_merged",encodec_decode:"encodec_decode"},b,"decoder_model_merged"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.MultiModality)O=await Promise.all([Zn(n,{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"},b,"model"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.Phi3V)O=await Promise.all([Zn(n,{prepare_inputs_embeds:"prepare_inputs_embeds",model:"model",vision_encoder:"vision_encoder"},b,"model"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.Chatterbox)O=await Promise.all([Zn(n,{embed_tokens:"embed_tokens",speech_encoder:"speech_encoder",model:"language_model",conditional_decoder:"conditional_decoder"},b,"model"),ds(n,{generation_config:"generation_config.json"},b)]);else if(E===ye.AutoEncoder)O=await Promise.all([Zn(n,{encoder_model:"encoder_model",decoder_model:"decoder_model"},b)]);else if(E===ye.Supertonic)O=await Promise.all([Zn(n,{text_encoder:"text_encoder",latent_denoiser:"latent_denoiser",voice_decoder:"voice_decoder"},b)]);else{if(E===void 0){const z=S??(s==null?void 0:s.model_type);z!=="custom"&&console.warn(`Model type for '${z}' not found, assuming encoder-only architecture. Please report this at ${Yg}.`)}O=await Promise.all([Zn(n,{model:b.model_file_name??"model"},b)])}return new this(s,...O)}async _call(n){return await this.forward(n)}async forward(n){return await this._forward(this,n)}get generation_config(){var n;return((n=this.configs)==null?void 0:n.generation_config)??null}_get_logits_processor(n,r,s=null){const o=new vg;if(n.repetition_penalty!==null&&n.repetition_penalty!==1&&o.push(new Z4(n.repetition_penalty)),n.no_repeat_ngram_size!==null&&n.no_repeat_ngram_size>0&&o.push(new W4(n.no_repeat_ngram_size)),n.bad_words_ids!==null&&o.push(new eN(n.bad_words_ids,n.eos_token_id)),n.min_length!==null&&n.eos_token_id!==null&&n.min_length>0&&o.push(new K4(n.min_length,n.eos_token_id)),n.min_new_tokens!==null&&n.eos_token_id!==null&&n.min_new_tokens>0&&o.push(new J4(r,n.min_new_tokens,n.eos_token_id)),n.forced_bos_token_id!==null&&o.push(new Y4(n.forced_bos_token_id)),n.forced_eos_token_id!==null&&o.push(new X4(n.max_length,n.forced_eos_token_id)),n.begin_suppress_tokens!==null){const c=r>1||n.forced_bos_token_id===null?r:r+1;o.push(new r2(n.begin_suppress_tokens,c))}return n.guidance_scale!==null&&n.guidance_scale>1&&o.push(new tN(n.guidance_scale)),n.temperature===0&&n.do_sample&&(console.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`."),n.do_sample=!1),n.do_sample&&n.temperature!==null&&n.temperature!==1&&o.push(new nN(n.temperature)),s!==null&&o.extend(s),o}_prepare_generation_config(n,r,s=s2){const o={...this.config};for(const u of["decoder","generator","text_config"])u in o&&Object.assign(o,o[u]);const c=new s(o);return Object.assign(c,this.generation_config??{}),n&&Object.assign(c,n),r&&Object.assign(c,Kn(r,Object.getOwnPropertyNames(c))),c}_get_stopping_criteria(n,r=null){const s=new aN;return n.max_length!==null&&s.push(new rN(n.max_length,this.config.max_position_embeddings??null)),n.eos_token_id!==null&&s.push(new sN(n.eos_token_id)),r&&s.extend(r),s}_validate_model_class(){if(!this.can_generate){const n=[Ru.MODEL_FOR_CAUSAL_LM_MAPPING_NAMES,Ru.MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES,Ru.MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING_NAMES,Ru.MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES].filter(Boolean),r=Ml.get(this.constructor),s=new Set,o=this.config.model_type;for(const u of n){const d=u==null?void 0:u.get(o);d&&s.add(d)}let c=`The current model class (${r}) is not compatible with \`.generate()\`, as it doesn't have a language model head.`;throw s.size>0&&(c+=` Please use the following class instead: ${[...s].join(", ")}`),Error(c)}}prepare_inputs_for_generation(...n){if(!this._prepare_inputs_for_generation)throw new Error("prepare_inputs_for_generation is not implemented for this model.");return this._prepare_inputs_for_generation(this,...n)}_update_model_kwargs_for_generation({generated_input_ids:n,outputs:r,model_inputs:s,is_encoder_decoder:o}){return s.past_key_values=this.getPastKeyValues(r,s.past_key_values),s.input_ids=new we("int64",n.flat(),[n.length,1]),o||(s.attention_mask=Pt([s.attention_mask,Fa([s.attention_mask.dims[0],1])],1)),s.position_ids=null,s}_prepare_model_inputs({inputs:n,bos_token_id:r,model_kwargs:s}){const o=Kn(s,this.forward_params),c=this.main_input_name;if(c in o){if(n)throw new Error("`inputs`: {inputs}` were passed alongside {input_name} which is not allowed. Make sure to either pass {inputs} or {input_name}=...")}else o[c]=n;return{inputs_tensor:o[c],model_inputs:o,model_input_name:c}}async _prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:n,model_inputs:r,model_input_name:s,generation_config:o}){if(this.sessions.model.inputNames.includes("inputs_embeds")&&!r.inputs_embeds&&"_prepare_inputs_embeds"in this){const{input_ids:u,pixel_values:d,attention_mask:h,...p}=r,g=await this._prepare_inputs_embeds(r);r={...p,...Kn(g,["inputs_embeds","attention_mask"])}}let{last_hidden_state:c}=await ci(this,r);if(o.guidance_scale!==null&&o.guidance_scale>1)c=Pt([c,pg(c,0)],0),"attention_mask"in r&&(r.attention_mask=Pt([r.attention_mask,Mx(r.attention_mask)],0));else if(r.decoder_input_ids){const u=yg(r.decoder_input_ids).dims[0];if(u!==c.dims[0]){if(c.dims[0]!==1)throw new Error(`The encoder outputs have a different batch size (${c.dims[0]}) than the decoder inputs (${u}).`);c=Pt(Array.from({length:u},()=>c),0)}}return r.encoder_outputs=c,r}_prepare_decoder_input_ids_for_generation({batch_size:n,model_input_name:r,model_kwargs:s,decoder_start_token_id:o,bos_token_id:c,generation_config:u}){let{decoder_input_ids:d,...h}=s;if(!(d instanceof we)){if(d)Array.isArray(d[0])||(d=Array.from({length:n},()=>d));else if(o??(o=c),this.config.model_type==="musicgen")d=Array.from({length:n*this.config.decoder.num_codebooks},()=>[o]);else if(Array.isArray(o)){if(o.length!==n)throw new Error(`\`decoder_start_token_id\` expcted to have length ${n} but got ${o.length}`);d=o}else d=Array.from({length:n},()=>[o]);d=yg(d)}return s.decoder_attention_mask=wx(d),{input_ids:d,model_inputs:h}}async generate({inputs:n=null,generation_config:r=null,logits_processor:s=null,stopping_criteria:o=null,streamer:c=null,...u}){this._validate_model_class(),r=this._prepare_generation_config(r,u);let{inputs_tensor:d,model_inputs:h,model_input_name:p}=this._prepare_model_inputs({inputs:n,model_kwargs:u});const g=this.config.is_encoder_decoder;g&&("encoder_outputs"in h||(h=await this._prepare_encoder_decoder_kwargs_for_generation({inputs_tensor:d,model_inputs:h,model_input_name:p,generation_config:r})));let y;g?{input_ids:y,model_inputs:h}=this._prepare_decoder_input_ids_for_generation({batch_size:h[p].dims.at(0),model_input_name:p,model_kwargs:h,decoder_start_token_id:r.decoder_start_token_id,bos_token_id:r.bos_token_id,generation_config:r}):y=h[p];let w=y.dims.at(-1);r.max_new_tokens!==null&&(r.max_length=w+r.max_new_tokens);const b=this._get_logits_processor(r,w,s),S=this._get_stopping_criteria(r,o),E=h[p].dims.at(0),O=zh.getSampler(r),z=new Array(E).fill(0),D=y.tolist();c&&c.put(D);let P,j={},G={};for(;;){if(h=this.prepare_inputs_for_generation(D,h,r),P=await this.forward(h),r.return_dict_in_generate)if(r.output_attentions){const pe=this.getAttentions(P);for(const ne in pe)ne in j||(j[ne]=[]),j[ne].push(pe[ne])}else this._return_dict_in_generate_keys&&Object.assign(G,Kn(P,this._return_dict_in_generate_keys));const ce=P.logits.slice(null,-1,null).to("float32"),oe=b(D,ce),he=[];for(let pe=0;pepe))break;h=this._update_model_kwargs_for_generation({generated_input_ids:he,outputs:P,model_inputs:h,is_encoder_decoder:g})}c&&c.end();const K=this.getPastKeyValues(P,h.past_key_values,!0),k=new we("int64",D.flat(),[D.length,D[0].length]);if(r.return_dict_in_generate)return{sequences:k,past_key_values:K,...j,...G};for(const ce of Object.values(P))ce.location==="gpu-buffer"&&ce.dispose();return k}getPastKeyValues(n,r,s=!1){const o=Object.create(null);for(const c in n)if(c.startsWith("present")){const u=c.replace("present_ssm","past_ssm").replace("present_conv","past_conv").replace("present","past_key_values"),d=c.includes("encoder");if(d&&r?o[u]=r[u]:o[u]=n[c],r&&(!d||s)){const h=r[u];h.location==="gpu-buffer"&&h.dispose()}}return o}getAttentions(n){const r={};for(const s of["cross_attentions","encoder_attentions","decoder_attentions"])for(const o in n)o.startsWith(s)&&(s in r||(r[s]=[]),r[s].push(n[o]));return r}addPastKeyValues(n,r){var s,o,c;if(r)Object.assign(n,r);else{const u=this.sessions.decoder_model_merged??this.sessions.model,d=((o=(s=n[this.main_input_name]??n.attention_mask)==null?void 0:s.dims)==null?void 0:o[0])??1,h=((c=u==null?void 0:u.config)==null?void 0:c.kv_cache_dtype)??"float32",p=h==="float16"?wh.float16:wh.float32,g=t2(this.config,{batch_size:d});for(const y in g){const w=g[y].reduce((b,S)=>b*S,1);n[y]=new we(h,new p(w),g[y])}}}async encode_image({pixel_values:n}){return(await rt(this.sessions.vision_encoder,{pixel_values:n})).image_features}async encode_text({input_ids:n}){return(await rt(this.sessions.embed_tokens,{input_ids:n})).inputs_embeds}async encode_audio({audio_values:n}){return(await rt(this.sessions.audio_encoder,{audio_values:n})).audio_features}};async function Gf(e,n){let{encoder_outputs:r,input_ids:s,decoder_input_ids:o,...c}=n;if(!r){const u=Kn(n,e.sessions.model.inputNames);r=(await ci(e,u)).last_hidden_state}return c.input_ids=o,c.encoder_hidden_states=r,e.sessions.decoder_model_merged.inputNames.includes("encoder_attention_mask")&&(c.encoder_attention_mask=n.attention_mask),await hs(e,c,!0)}async function ci(e,n){const r=e.sessions.model,s=Kn(n,r.inputNames);if(r.inputNames.includes("inputs_embeds")&&!s.inputs_embeds){if(!n.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:n.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=Mx(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=Fa([o[0],o[2],o[3]])}return await rt(r,s)}async function uN(e,n){const r=await e.encode(n);return await e.decode(r)}async function hs(e,n,r=!1){const s=e.sessions[r?"decoder_model_merged":"model"],{past_key_values:o,...c}=n;if(s.inputNames.includes("use_cache_branch")&&(c.use_cache_branch=o2(!!o)),s.inputNames.includes("position_ids")&&c.attention_mask&&!c.position_ids){const d=["paligemma","gemma3_text","gemma3"].includes(e.config.model_type)?1:0;c.position_ids=hN(c,o,d)}e.addPastKeyValues(c,o);const u=Kn(c,s.inputNames);return await rt(s,u)}async function l2(e,{encode_function:n,merge_function:r,modality_input_name:s,modality_output_name:o,input_ids:c=null,attention_mask:u=null,position_ids:d=null,inputs_embeds:h=null,past_key_values:p=null,generation_config:g=null,logits_processor:y=null,...w}){const b=w[s];if(!h){if(h=await e.encode_text({input_ids:c,...w}),b&&c.dims[1]!==1){const E=await n({[s]:b,...w});({inputs_embeds:h,attention_mask:u}=r({[o]:E,inputs_embeds:h,input_ids:c,attention_mask:u}))}else if(p&&b&&c.dims[1]===1){const E=c.dims[1],O=Object.values(p)[0].dims.at(-2);u=Pt([Fa([c.dims[0],O]),u.slice(null,[u.dims[1]-E,u.dims[1]])],1)}}if(!d&&e.config.model_type==="qwen2_vl"){const{image_grid_thw:E,video_grid_thw:O}=w;[d]=e.get_rope_index(c,E,O,u)}return await hs(e,{inputs_embeds:h,past_key_values:p,attention_mask:u,position_ids:d,generation_config:g,logits_processor:y},!0)}async function dN(e,n){return await l2(e,{...n,modality_input_name:"audio_values",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 fN(e,n){return await l2(e,{...n,modality_input_name:"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 c2(e,n=0){const[r,s]=e.dims,o=e.data,c=new BigInt64Array(o.length);for(let u=0;uc.dims[1]||o[o.at(-1)])),{...r,decoder_input_ids:yg(n)}}function jf(e,...n){return e.config.is_encoder_decoder?xh(e,...n):Mh(e,...n)}function u2({modality_token_id:e,inputs_embeds:n,modality_features:r,input_ids:s,attention_mask:o}){const c=s.tolist().map(p=>p.reduce((g,y,w)=>(y==e&&g.push(w),g),[])),u=c.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 h=0;for(let p=0;p{const o=await Lr(e,n[s],!1,r);return[s,o]})))}var 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extends f2{async encode_speech(e){return rt(this.sessions.speech_encoder,{audio_values:e})}async forward({input_ids:e=null,attention_mask:n=null,audio_values:r=null,exaggeration:s=null,position_ids:o=null,inputs_embeds:c=null,past_key_values:u=null,generation_config:d=null,logits_processor:h=null,audio_features:p=null,audio_tokens:g=null,speaker_embeddings:y=null,speaker_features:w=null,...b}){let S;if(!c){const O=this.sessions.embed_tokens.inputNames,z={input_ids:e};if(O.includes("exaggeration")){if(!(s instanceof we)){const D=e.dims[0];if(s==null)s=zn([D],.5);else if(typeof s=="number")s=zn([D],s);else if(Array.isArray(s))s=new we("float32",s,[D]);else throw new Error("Unsupported type for `exaggeration` input")}z.exaggeration=s}if(O.includes("position_ids")&&(z.position_ids=o),{inputs_embeds:c}=await rt(this.sessions.embed_tokens,z),p&&g&&y&&w&&(S={audio_features:p,audio_tokens:g,speaker_embeddings:y,speaker_features:w}),S||r)S??(S=await this.encode_speech(r)),c=Pt([S.audio_features,c],1),n=Fa([c.dims[0],c.dims[1]]);else{const D=c.dims[1];if(!u||D!==1)throw new Error("Incorrect state encountered during generation.");const P=Object.values(u)[0].dims.at(-2);n=Fa([c.dims[0],P+D])}}return{...await hs(this,{inputs_embeds:c,past_key_values:u,attention_mask:n,generation_config:d,logits_processor:h},!1),...S}}prepare_inputs_for_generation(e,n,r){if(!n.position_ids&&this.sessions.embed_tokens.inputNames.includes("position_ids"))if(n.input_ids.dims[1]===1){const s=Array.from({length:e.length},(o,c)=>e[c].length-e[c].findLastIndex(u=>u==I1)-1);n.position_ids=new we("int64",s,[e.length,1])}else{const o=n.input_ids.tolist().map(c=>{let u=0;return c.map(d=>d>=I1?0:u++)});n.position_ids=new we("int64",o.flat(),n.input_ids.dims)}return n.input_ids.dims[1]===1&&(delete n.audio_values,delete n.audio_features,delete n.audio_tokens,delete n.speaker_embeddings,delete n.speaker_features),Mh(this,e,n)}async generate(e){const{sequences:n,audio_tokens:r,speaker_embeddings:s,speaker_features:o}=await super.generate({...e,return_dict_in_generate:!0}),c=n.slice(null,[e.input_ids.dims[1],-1]),u=zn([c.dims[0],3],$N),d=Pt([r,c,u],1),{waveform:h}=await rt(this.sessions.conditional_decoder,{speech_tokens:d,speaker_features:o,speaker_embeddings:s});return h}},p2=class extends Y{},HN=class extends p2{},Nh=class extends Y{},YN=class extends Nh{},m2=class extends Nh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"text_model"})}},_2=class extends Nh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"audio_model"})}},ro=class extends Y{},XN=class extends ro{},QN=class extends ro{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"text_model"})}},g2=class extends ro{static async from_pretrained(e,n={}){return 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Pe(await super._call(e))}},pv=class extends Y{},dD=class extends pv{},fD=class extends pv{async _call(e){return new Pe(await super._call(e))}},mv=class extends Y{},hD=class extends mv{},pD=class extends mv{async _call(e){return new Wu(await super._call(e))}},Wu=class extends rn{constructor({logits:e,pred_boxes:n}){super(),this.logits=e,this.pred_boxes=n}},_v=class extends Y{},mD=class extends _v{},_D=class extends _v{async _call(e){return new Wu(await super._call(e))}},v2=class extends rn{constructor({audio_codes:e}){super(),this.audio_codes=e}},y2=class extends rn{constructor({audio_values:e}){super(),this.audio_values=e}},Dh=class extends Y{constructor(){super(...arguments);L(this,"main_input_name","input_values");L(this,"forward_params",["input_values"])}},gD=class extends Dh{async encode(e){return new v2(await rt(this.sessions.encoder_model,e))}async decode(e){return new y2(await rt(this.sessions.decoder_model,e))}},w2=class extends Dh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"encoder_model"})}},b2=class extends Dh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"decoder_model"})}},Ll=class extends Y{},vD=class extends Ll{},yD=class extends Ll{async _call(e){return new dn(await super._call(e))}},wD=class extends Ll{async _call(e){return new Pe(await super._call(e))}},bD=class extends Ll{async _call(e){return new sn(await super._call(e))}},MD=class extends Ll{async _call(e){return new Ln(await super._call(e))}},Nl=class extends Y{},xD=class extends Nl{},TD=class extends Nl{async _call(e){return new dn(await super._call(e))}},SD=class extends Nl{async _call(e){return new Pe(await super._call(e))}},ED=class extends Nl{async _call(e){return new sn(await super._call(e))}},AD=class extends Nl{async _call(e){return new Ln(await super._call(e))}},M2=class extends Y{},CD=class extends M2{},gv=class extends Y{},kD=class extends gv{},OD=class extends gv{async _call(e){return new Pe(await super._call(e))}},x2=class extends Y{},zD=class extends x2{},T2=class extends Y{},LD=class extends T2{},Fh=class extends Y{},ND=class extends Fh{},DD=class extends Fh{async _call(e){return new vv(await super._call(e))}},FD=class extends Fh{async _call(e){return new S2(await super._call(e))}},vv=class extends rn{constructor({logits:e,pred_boxes:n}){super(),this.logits=e,this.pred_boxes=n}},S2=class extends rn{constructor({logits:e,pred_boxes:n,pred_masks:r}){super(),this.logits=e,this.pred_boxes=n,this.pred_masks=r}},yv=class extends Y{},BD=class extends yv{},PD=class extends yv{async _call(e){return new Pe(await super._call(e))}},wv=class extends Y{},RD=class extends wv{},UD=class extends wv{async _call(e){return new Pe(await super._call(e))}},E2=class extends Y{},ID=class extends E2{},A2=class extends Y{},GD=class extends A2{},Dl=class extends Y{},jD=class extends Dl{},VD=class extends Dl{async _call(e){return new Pe(await super._call(e))}},qD=class extends Dl{async _call(e){return new sn(await super._call(e))}},$D=class extends Dl{async _call(e){return new Ln(await super._call(e))}},HD=class extends Dl{async _call(e){return new dn(await super._call(e))}},C2=class extends Y{},YD=class extends C2{},bv=class extends Y{},XD=class extends bv{},QD=class extends bv{},Mv=class extends Y{},WD=class extends Mv{},ZD=class extends Mv{async _call(e){return new Pe(await super._call(e))}},Fl=class extends Y{},KD=class extends Fl{},JD=class extends Fl{async _call(e){return new dn(await super._call(e))}},eF=class extends Fl{async _call(e){return new Pe(await super._call(e))}},tF=class extends Fl{async _call(e){return new sn(await super._call(e))}},nF=class extends Fl{async _call(e){return new Ln(await super._call(e))}},xv=class extends Y{},aF=class extends xv{},rF=class extends xv{},Zu=class extends Y{},sF=class extends Zu{},iF=class extends Zu{async _call(e){return new dn(await super._call(e))}},oF=class extends Zu{async _call(e){return new Pe(await super._call(e))}},lF=class extends Zu{async _call(e){return new sn(await super._call(e))}},Tv=class extends Y{},cF=class extends Tv{},uF=class extends Tv{},Sv=class extends Y{},dF=class extends Sv{},fF=class extends Sv{},Ev=class extends Y{},hF=class extends Ev{},pF=class extends Ev{},Av=class extends Y{},mF=class extends Av{},_F=class extends Av{async _call(e){return new Pe(await super._call(e))}},k2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","inputs_embeds","attention_mask","pixel_values","encoder_outputs","decoder_input_ids","decoder_inputs_embeds","decoder_attention_mask","past_key_values"]);L(this,"main_input_name","inputs_embeds")}},gF=class extends k2{_merge_input_ids_with_image_features({inputs_embeds:e,image_features:n,input_ids:r,attention_mask:s}){return{inputs_embeds:Pt([n,e],1),attention_mask:Pt([Fa(n.dims.slice(0,2)),s],1)}}async _prepare_inputs_embeds({input_ids:e,pixel_values:n,inputs_embeds:r,attention_mask:s}){if(!e&&!n)throw new Error("Either `input_ids` or `pixel_values` should be provided.");let o,c;return e&&(o=await this.encode_text({input_ids:e})),n&&(c=await this.encode_image({pixel_values:n})),o&&c?{inputs_embeds:r,attention_mask:s}=this._merge_input_ids_with_image_features({inputs_embeds:o,image_features:c,input_ids:e,attention_mask:s}):r=o||c,{inputs_embeds:r,attention_mask:s}}async forward({input_ids:e,pixel_values:n,attention_mask:r,decoder_input_ids:s,decoder_attention_mask:o,encoder_outputs:c,past_key_values:u,inputs_embeds:d,decoder_inputs_embeds:h}){if(d||({inputs_embeds:d,attention_mask:r}=await this._prepare_inputs_embeds({input_ids:e,pixel_values:n,inputs_embeds:d,attention_mask:r})),!c){let{last_hidden_state:g}=await ci(this,{inputs_embeds:d,attention_mask:r});c=g}if(!h){if(!s)throw new Error("Either `decoder_input_ids` or `decoder_inputs_embeds` should be provided.");h=await this.encode_text({input_ids:s})}return await hs(this,{inputs_embeds:h,attention_mask:o,encoder_attention_mask:r,encoder_hidden_states:c,past_key_values:u},!0)}},Cv=class extends Y{},vF=class extends Cv{},yF=class extends Cv{},kv=class extends Y{},wF=class extends kv{},bF=class extends kv{},Ov=class extends Y{},MF=class extends Ov{},xF=class extends Ov{},O2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","inputs_embeds","per_layer_inputs","position_ids","pixel_values","input_features","input_features_mask","past_key_values"])}},z2=class extends O2{async forward({input_ids:e=null,attention_mask:n=null,pixel_values:r=null,input_features:s=null,input_features_mask:o=null,position_ids:c=null,inputs_embeds:u=null,per_layer_inputs:d=null,past_key_values:h=null,generation_config:p=null,logits_processor:g=null,...y}){if((!u||!d)&&({inputs_embeds:u,per_layer_inputs:d}=await rt(this.sessions.embed_tokens,{input_ids:e}),e.dims[1]!==1)){if(r){const{image_features:b}=await rt(this.sessions.vision_encoder,{pixel_values:r});({inputs_embeds:u,attention_mask:n}=this._merge_input_ids_with_image_features({image_features:b,inputs_embeds:u,input_ids:e,attention_mask:n}))}if(s){const{audio_features:b}=await rt(this.sessions.audio_encoder,{input_features:s,input_features_mask:o});({inputs_embeds:u,attention_mask:n}=this._merge_input_ids_with_audio_features({audio_features:b,inputs_embeds:u,input_ids:e,attention_mask:n}))}}return await hs(this,{inputs_embeds:u,per_layer_inputs:d,past_key_values:h,attention_mask:n,position_ids:c,generation_config:p,logits_processor:g},!0)}_merge_input_ids_with_image_features(e){const n=e.image_features.dims.at(-1),r=e.image_features.view(-1,n);return Xu({image_token_id:this.config.image_token_id,...e,image_features:r})}_merge_input_ids_with_audio_features(e){const n=e.audio_features.dims.at(-1),r=e.audio_features.view(-1,n);return d2({audio_token_id:this.config.audio_token_id,...e,audio_features:r})}},zv=class extends Y{},TF=class extends zv{},SF=class extends zv{},Lv=class extends Y{},EF=class extends Lv{},AF=class extends Lv{},Nv=class extends Y{},CF=class extends Nv{},kF=class extends Nv{},Dv=class extends Y{},OF=class extends Dv{},zF=class extends Dv{},Fv=class extends Y{},LF=class extends Fv{},NF=class extends Fv{},Bv=class extends Y{},DF=class extends Bv{},FF=class extends Bv{},Pv=class extends Y{},BF=class extends Pv{},PF=class extends Pv{},Rv=class extends Y{},RF=class extends Rv{},UF=class extends Rv{},Uv=class extends Y{},IF=class extends Uv{},GF=class extends Uv{},Iv=class extends Y{},jF=class extends Iv{},VF=class extends Iv{},L2=class extends Y{},qF=class extends L2{},N2=class extends Y{},$F=class extends N2{},Gv=class extends Y{},HF=class extends Gv{},YF=class extends Gv{},jv=class extends Y{},XF=class extends jv{},QF=class extends jv{async _call(e){return new Pe(await super._call(e))}},ui=class extends Y{},WF=class extends ui{},ZF=class extends ui{async _call(e){return new ao(await super._call(e))}},KF=class extends ui{async _call(e){return new Pe(await super._call(e))}},JF=class extends ui{async _call(e){return new sn(await super._call(e))}},e6=class extends Y{},t6=class extends ui{},n6=class extends ui{async _call(e){return new ao(await super._call(e))}},a6=class extends ui{async _call(e){return new Pe(await super._call(e))}},Vv=class extends Y{},r6=class extends Vv{},s6=class extends Vv{},D2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","pixel_values","pixel_attention_mask","position_ids","past_key_values"])}},F2=class extends D2{async encode_image({pixel_values:e,pixel_attention_mask:n}){return(await rt(this.sessions.vision_encoder,{pixel_values:e,pixel_attention_mask:n})).image_features}_merge_input_ids_with_image_features(e){const n=e.image_features.dims.at(-1),r=e.image_features.view(-1,n);return Xu({image_token_id:this.config.image_token_id,...e,image_features:r})}},i6=class extends F2{},qv=class extends Y{},o6=class extends qv{},l6=class extends qv{async _call(e){return new Pe(await super._call(e))}},$v=class extends Y{},c6=class extends $v{},u6=class extends $v{},Bh=class extends Y{},d6=class extends Bh{async forward(e){const n=!e.input_ids,r=!e.pixel_values;if(n&&r)throw new Error("Either `input_ids` or `pixel_values` should be provided.");if(n&&(e.input_ids=Fa([e.pixel_values.dims[0],1])),r){const{image_size:h}=this.config.vision_config;e.pixel_values=zn([0,3,h,h],0)}const{text_embeddings:s,image_embeddings:o,l2norm_text_embeddings:c,l2norm_image_embeddings:u}=await super.forward(e),d={};return n||(d.text_embeddings=s,d.l2norm_text_embeddings=c),r||(d.image_embeddings=o,d.l2norm_image_embeddings=u),d}},B2=class extends Bh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"text_model"})}},f6=class extends Bh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"vision_model"})}},Hv=class extends Y{},h6=class extends Hv{},p6=class extends Hv{},Yv=class extends Y{},m6=class extends Yv{},_6=class extends Yv{},Xv=class extends Y{},g6=class extends Xv{},v6=class extends Xv{},P2=class extends Y{},y6=class extends P2{},R2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","pixel_values","position_ids","past_key_values"])}},Th=class extends R2{_merge_input_ids_with_image_features(e){const n=e.image_features.dims.at(-1),r=e.image_features.view(-1,n);return Xu({image_token_id:this.config.image_token_index,...e,image_features:r})}},w6=class extends Th{},b6=class extends Th{},Qv=class extends Y{},M6=class extends Qv{},x6=class extends Qv{},Wv=class extends Y{},T6=class extends Wv{},S6=class extends Wv{},Zv=class extends Y{},E6=class extends Zv{},A6=class extends Zv{},Kv=class extends Y{},C6=class extends Kv{},k6=class extends Kv{},Ku=class extends Y{},O6=class extends Ku{},z6=class extends Ku{},L6=class extends Ku{async _call(e){return new Pe(await super._call(e))}},N6=class extends Ku{},U2=class extends Y{},D6=class extends U2{},I2=class extends Y{},F6=class extends I2{},G2=class extends rn{constructor({char_logits:e,bpe_logits:n,wp_logits:r}){super(),this.char_logits=e,this.bpe_logits=n,this.wp_logits=r}get logits(){return[this.char_logits,this.bpe_logits,this.wp_logits]}},j2=class extends Y{},B6=class extends j2{async _call(e){return new G2(await super._call(e))}},V2=class extends rn{constructor({audio_codes:e}){super(),this.audio_codes=e}},q2=class extends rn{constructor({audio_values:e}){super(),this.audio_values=e}},Ph=class extends Y{constructor(){super(...arguments);L(this,"main_input_name","input_values");L(this,"forward_params",["input_values"])}},P6=class extends Ph{async encode(e){return new V2(await rt(this.sessions.encoder_model,e))}async decode(e){return new q2(await rt(this.sessions.decoder_model,e))}},$2=class extends Ph{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"encoder_model"})}},H2=class extends Ph{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"decoder_model"})}},Jv=class extends Y{},R6=class extends Jv{},U6=class extends Jv{},Ju=class extends Y{},I6=class extends Ju{},G6=class extends Ju{async _call(e){return new dn(await super._call(e))}},j6=class extends Ju{async _call(e){return new Pe(await super._call(e))}},V6=class extends Ju{async _call(e){return new Ln(await super._call(e))}},ey=class extends Y{},q6=class extends ey{},$6=class extends ey{},Rh=class extends Y{},H6=class extends Rh{},Y6=class extends Rh{async _call(e){return new Pe(await super._call(e))}},X6=class extends Rh{},Uh=class extends Y{},Q6=class extends Uh{},W6=class extends Uh{async _call(e){return new Pe(await super._call(e))}},Z6=class extends Uh{},Ih=class extends Y{},K6=class extends Ih{},J6=class extends Ih{async _call(e){return new Pe(await super._call(e))}},eB=class extends Ih{},Gh=class extends Y{},tB=class extends Gh{},nB=class extends Gh{async _call(e){return new Pe(await super._call(e))}},aB=class extends Gh{},ty=class extends Y{},rB=class extends ty{},sB=class extends ty{async _call(e){return new Pe(await super._call(e))}},ny=class extends Y{},iB=class extends ny{},oB=class extends ny{async _call(e){return new Pe(await super._call(e))}},ed=class extends Y{},lB=class extends ed{},cB=class extends ed{async _call(e){return new dn(await super._call(e))}},uB=class extends ed{async _call(e){return new Pe(await super._call(e))}},dB=class extends ed{async _call(e){return new sn(await super._call(e))}},ay=class extends Y{},fB=class extends ay{},hB=class extends ay{},ry=class extends Y{constructor(){super(...arguments);L(this,"requires_attention_mask",!1);L(this,"main_input_name","input_values");L(this,"forward_params",["input_values","decoder_input_ids","past_key_values"])}},pB=class extends ry{},mB=class extends ry{},Bl=class extends Y{},_B=class extends Bl{},gB=class extends Bl{async _call(e){return new dn(await super._call(e))}},vB=class extends Bl{async _call(e){return new Pe(await super._call(e))}},yB=class extends Bl{async _call(e){return new sn(await super._call(e))}},wB=class extends Bl{async _call(e){return new Ln(await super._call(e))}},sy=class extends Y{},bB=class extends sy{},MB=class extends sy{},iy=class extends Y{},xB=class extends iy{},TB=class extends iy{},Y2=class extends Y{},SB=class extends Y2{constructor(...n){super(...n);L(this,"forward_params",["input_ids","pixel_values","images_seq_mask","images_emb_mask","attention_mask","position_ids","past_key_values"]);this._generation_mode="text"}async forward(n){const r=this._generation_mode??"text";let s;if(r==="text"||!n.past_key_values){const h=this.sessions.prepare_inputs_embeds,p=Kn(n,h.inputNames);s=await rt(h,p)}else{const h=this.sessions.gen_img_embeds,p=Kn({image_ids:n.input_ids},h.inputNames);s=await rt(h,p)}const o={...n,...s},c=await hs(this,o),u=this.sessions[r==="text"?"lm_head":"gen_head"];if(!u)throw new Error(`Unable to find "${u}" generation head`);const d=await rt(u,Kn(c,u.inputNames));return{...s,...c,...d}}prepare_inputs_for_generation(n,r,s){const o=!!r.past_key_values;return s.guidance_scale!==null&&s.guidance_scale>1&&(o?r.input_ids=Pt([r.input_ids,r.input_ids],0):(r.input_ids=Pt([r.input_ids,pg(r.input_ids,BigInt(s.pad_token_id))],0),r.attention_mask=Pt([r.attention_mask,pg(r.attention_mask,0n)],0))),(o||!r.pixel_values)&&(r.pixel_values=zn([0,0,3,384,384],1)),o&&(r.images_seq_mask=new we("bool",new Array(1).fill(!0).fill(!1,0,1),[1,1]),r.images_emb_mask=new we("bool",new Array(0).fill(!1),[1,1,0])),r}async generate(n){return this._generation_mode="text",super.generate(n)}async generate_images(n){this._generation_mode="image";const r=(n.inputs??n[this.main_input_name]).dims[1],o=(await super.generate(n)).slice(null,[r,null]),c=this.sessions.image_decode,{decoded_image:u}=await rt(c,{generated_tokens:o}),d=u.add_(1).mul_(255/2).clamp_(0,255).to("uint8"),h=[];for(const p of d){const g=rr.fromTensor(p);h.push(g)}return h}},oy=class extends Y{},EB=class extends oy{},AB=class extends oy{},X2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","encoder_outputs","decoder_input_ids","decoder_attention_mask","past_key_values"])}_apply_and_filter_by_delay_pattern_mask(n){const[r,s]=n.dims,o=this.config.decoder.num_codebooks,c=s-o;let u=0;for(let p=0;p0&&w<=c&&(n.data[u++]=n.data[p])}const d=Math.floor(r/o),h=u/(d*o);return new we(n.type,n.data.slice(0,u),[d,o,h])}prepare_inputs_for_generation(n,r,s){const 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extends dy{},fy=class extends Y{},jB=class extends fy{},VB=class extends fy{},hy=class extends Y{},qB=class extends hy{},$B=class extends hy{},py=class extends Y{},HB=class extends py{},YB=class extends py{},my=class extends Y{},XB=class extends my{},QB=class extends my{},W2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","pixel_values","position_ids","past_key_values"])}},WB=class extends W2{_merge_input_ids_with_image_features(e){const n=e.image_features.dims.at(-1),r=e.image_features.view(-1,n);return Xu({image_token_id:this.config.image_token_index,...e,image_features:r})}},Z2=class extends Y{},ZB=class extends Z2{async _call(e){return new ao(await super._call(e))}},_y=class extends Y{},KB=class extends _y{},JB=class extends _y{},gy=class extends Y{},eP=class extends gy{},tP=class extends gy{},vy=class extends Y{},nP=class extends vy{},aP=class extends vy{},yy=class extends Y{},rP=class extends yy{},sP=class extends yy{},K2=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","inputs_embeds","attention_mask","position_ids","pixel_values","image_sizes","past_key_values"])}},J2=class extends K2{async forward({input_ids:e=null,attention_mask:n=null,pixel_values:r=null,image_sizes:s=null,position_ids:o=null,inputs_embeds:c=null,past_key_values:u=null,generation_config:d=null,logits_processor:h=null,...p}){if(!c){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 rt(this.sessions.vision_encoder,{pixel_values:r,image_sizes:s}))}else{const w=this.config.normalized_config.hidden_size;y=new we("float32",[],[0,w])}({inputs_embeds:c}=await rt(this.sessions.prepare_inputs_embeds,{input_ids:e,image_features:y}))}return await hs(this,{inputs_embeds:c,past_key_values:u,attention_mask:n,position_ids:o,generation_config:d,logits_processor:h},!1)}},wy=class extends Y{},iP=class extends wy{},oP=class extends wy{async _call(e){return new Pe(await super._call(e))}},by=class extends Y{},lP=class extends by{},cP=class extends by{async _call(e){return new sn(await super._call(e))}},My=class extends Y{},uP=class extends My{},dP=class extends My{},eT=class extends Y{constructor(){super(...arguments);L(this,"forward_params",["input_ids","attention_mask","position_ids","past_key_values","pixel_values","image_grid_thw"])}},fP=class extends eT{get_rope_index(e,n,r,s){const{vision_config:o,image_token_id:c,video_token_id:u,vision_start_token_id:d}=this.config,h=o.spatial_merge_size??2,p=[];if(n||r){let g=e.tolist();s||(s=wx(e));const y=s.tolist(),w=Array.from({length:3},z=>Array.from({length:e.dims[0]},D=>Array.from({length:e.dims[1]},P=>1))),b=n?n.tolist():[],S=r?r.tolist():[];let E=0,O=0;for(let z=0;zy[z][I]==1),j=D.reduce((W,I,R)=>(I==d&&W.push(R),W),[]).map(W=>D[W+1]),G=j.filter(W=>W==c).length,K=j.filter(W=>W==u).length;let k=[],ce=0,oe=G,he=K;for(let W=0;Wxt>ce&&Rt==c),R=D.findIndex((Rt,xt)=>xt>ce&&Rt==u),te=oe>0&&I!==-1?I:D.length+1,F=he>0&&R!==-1?R:D.length+1;let H,ue,de,be;te0?Qt(k.at(-1))[0]+1:0;k.push(Array.from({length:3*Qe},(Rt,xt)=>ht+xt%Qe));const Ct=Qe+ht,Ue=Oe*Ne*at,ze=Array.from({length:Ue},(Rt,xt)=>Ct+Math.floor(xt/(Ne*at))),Ye=Array.from({length:Ue},(Rt,xt)=>Ct+Math.floor(xt/at)%Ne),Ht=Array.from({length:Ue},(Rt,xt)=>Ct+xt%at);k.push([ze,Ye,Ht].flat()),ce=H+Ue}if(ce0?Qt(k.at(-1))[0]+1:0,I=D.length-ce;k.push(Array.from({length:3*I},(R,te)=>W+te%I))}const me=k.reduce((W,I)=>W+I.length,0),pe=new Array(me);let ne=0;for(let W=0;W<3;++W)for(let I=0;Ig[E%g.length]),b=Array.from({length:y[0]},(S,E)=>Qt(g.subarray(y[1]*E,y[1]*(E+1)))[0]+1n+BigInt(y[1]));return[new we("int64",w,[3,...y]),new we("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 we("int64",w,[3,...e.dims]),bx([g,1])]}}async encode_image({pixel_values:e,image_grid_thw:n}){return(await rt(this.sessions.vision_encoder,{pixel_values:e,grid_thw:n})).image_features}_merge_input_ids_with_image_features(e){return Xu({image_token_id:this.config.image_token_id,...e})}prepare_inputs_for_generation(e,n,r){if(n.attention_mask&&!n.position_ids)if(!n.past_key_values)[n.position_ids,n.rope_deltas]=this.get_rope_index(n.input_ids,n.image_grid_thw,n.video_grid_thw,n.attention_mask);else{n.pixel_values=null;const s=BigInt(Object.values(n.past_key_values)[0].dims.at(-2)),o=n.rope_deltas.map(c=>s+c);n.position_ids=Cl([o,o,o],0)}return n}},xy=class extends Y{},hP=class extends xy{},pP=class extends xy{},Ty=class extends Y{},mP=class extends Ty{},_P=class extends Ty{async _call(e){return new Pe(await super._call(e))}},Sy=class extends Y{},gP=class extends Sy{},vP=class extends Sy{async _call(e){return new tT(await super._call(e))}},tT=class extends Wu{},Rl=class extends Y{},yP=class extends Rl{},wP=class extends Rl{async _call(e){return new dn(await super._call(e))}},bP=class extends Rl{async _call(e){return new Pe(await super._call(e))}},MP=class extends Rl{async _call(e){return new sn(await super._call(e))}},xP=class extends Rl{async _call(e){return new Ln(await super._call(e))}},Ul=class extends Y{},TP=class extends Ul{},SP=class extends Ul{async _call(e){return new dn(await super._call(e))}},EP=class extends Ul{async _call(e){return new Pe(await super._call(e))}},AP=class extends Ul{async _call(e){return new sn(await super._call(e))}},CP=class extends Ul{async _call(e){return new Ln(await super._call(e))}},Ey=class extends Y{},kP=class extends Ey{},OP=class extends Ey{async _call(e){return new nT(await super._call(e))}},nT=class extends Wu{},aT=class extends rn{constructor({iou_scores:e,pred_masks:n}){super(),this.iou_scores=e,this.pred_masks=n}},rT=class extends Y{},zP=class extends rT{async get_image_embeddings({pixel_values:e}){return await ci(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??(e.input_labels=Fa(e.input_points.dims.slice(0,-1)));const n={image_embeddings:e.image_embeddings,image_positional_embeddings:e.image_positional_embeddings};return e.input_points&&(n.input_points=e.input_points),e.input_labels&&(n.input_labels=e.input_labels),e.input_boxes&&(n.input_boxes=e.input_boxes),await rt(this.sessions.prompt_encoder_mask_decoder,n)}async _call(e){return new aT(await super._call(e))}},sT=class extends rn{constructor({iou_scores:e,pred_masks:n,object_score_logits:r}){super(),this.iou_scores=e,this.pred_masks=n,this.object_score_logits=r}},iT=class extends Y{},Ay=class extends iT{async get_image_embeddings({pixel_values:e}){return await ci(this,{pixel_values:e})}async forward(e){const{num_feature_levels:n}=this.config.vision_config;if(Array.from({length:n},(c,u)=>`image_embeddings.${u}`).some(c=>!e[c])?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 c=e.input_points.dims;e.input_labels??(e.input_labels=Fa(c.slice(0,-1))),e.input_boxes??(e.input_boxes=zn([c[0],0,4],0))}else if(e.input_boxes){const c=e.input_boxes.dims;e.input_labels=zn([c[0],c[1],0],-1n),e.input_points=zn([c[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=Kn(e,s.inputNames);return await rt(s,o)}async _call(e){return new sT(await super._call(e))}},LP=class extends Ay{},NP=class extends Ay{},jh=class extends Y{},DP=class extends jh{},FP=class extends jh{},BP=class extends jh{},Vh=class extends Y{},PP=class extends Vh{},RP=class extends Vh{},UP=class extends Vh{},Cy=class extends Y{},IP=class extends Cy{},oT=class extends Cy{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"text_model"})}},GP=class extends ro{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"vision_model"})}},ky=class extends Y{},jP=class extends ky{},VP=class extends ky{},qh=class extends Y{constructor(){super(...arguments);L(this,"main_input_name","input_values");L(this,"forward_params",["input_values"])}},qP=class extends qh{async encode(e){return await rt(this.sessions.encoder_model,e)}async decode(e){return await rt(this.sessions.decoder_model,e)}},lT=class extends qh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"encoder_model"})}},cT=class extends qh{static async from_pretrained(e,n={}){return super.from_pretrained(e,{...n,model_file_name:n.model_file_name??"decoder_model"})}},$h=class extends Y{},$P=class extends $h{},HP=class extends $h{},YP=class extends $h{async generate_speech(e,n,{threshold:r=.5,minlenratio:s=0,maxlenratio:o=20,vocoder:c=null}={}){const u={input_ids:e},{encoder_outputs:d,encoder_attention_mask:h}=await ci(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,O=0;for(;;){++O;const P=o2(!!E);let j;E?j=E.output_sequence_out:j=new we("float32",new Float32Array(w),[1,1,w]);let G={use_cache_branch:P,output_sequence:j,encoder_attention_mask:h,speaker_embeddings:n,encoder_hidden_states:d};this.addPastKeyValues(G,S),E=await rt(this.sessions.decoder_model_merged,G),S=this.getPastKeyValues(E,S);const{prob:K,spectrum:k}=E;if(b.push(k),O>=y&&(Array.from(K.data).filter(ce=>ce>=r).length>0||O>=g))break}const z=Pt(b),{waveform:D}=await rt(c.sessions.model,{spectrogram:z});return{spectrogram:z,waveform:D}}},XP=class extends Y{constructor(){super(...arguments);L(this,"main_input_name","spectrogram")}},td=class extends Y{},QP=class extends td{},WP=class extends td{async _call(e){return new dn(await super._call(e))}},ZP=class extends td{async _call(e){return new Pe(await super._call(e))}},KP=class extends td{async _call(e){return new Ln(await super._call(e))}},Oy=class extends Y{},JP=class extends Oy{},e8=class extends Oy{},zy=class extends Y{},t8=class extends zy{},n8=class extends zy{},uT=class extends Y{},a8=class extends uT{},dT=class extends Y{},fT=class extends dT{async generate_speech({input_ids:e,attention_mask:n,style:r,num_inference_steps:s=5,speed:o=1.05}){const{sampling_rate:c,chunk_compress_factor:u,base_chunk_size:d,latent_dim:h}=this.config,{last_hidden_state:p,durations:g}=await rt(this.sessions.text_encoder,{input_ids:e,attention_mask:n,style:r}),y=g.div(o).mul_(c),w=d*u,b=y.data,S=Int32Array.from(b,oe=>Math.ceil(oe/w)),E=Math.max(...S),O=e.dims[0],z=new BigInt64Array(O*E);for(let oe=0;oe`;n.push(e.lang_to_id[c]),n.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&&n.at(-1)!==e.no_timestamps_token_id?n.push(e.no_timestamps_token_id):e.return_timestamps&&n.at(-1)===e.no_timestamps_token_id&&(console.warn("<|notimestamps|> prompt token is removed from generation_config since `return_timestamps` is set to `true`."),n.pop()),n.filter(o=>o!=null)}async generate({inputs:e=null,generation_config:n=null,logits_processor:r=null,stopping_criteria:s=null,...o}){n=this._prepare_generation_config(n,o);const c=o.decoder_input_ids??this._retrieve_init_tokens(n);if(n.return_timestamps&&(r??(r=new vg),r.push(new Q4(n,c))),n.begin_suppress_tokens&&(r??(r=new vg),r.push(new r2(n.begin_suppress_tokens,c.length))),n.return_token_timestamps){if(!n.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.");n.task==="translate"&&console.warn("Token-level timestamps may not be reliable for task 'translate'."),n.output_attentions=!0,n.return_dict_in_generate=!0}const u=await super.generate({inputs:e,generation_config:n,logits_processor:r,decoder_input_ids:c,...o});return n.return_token_timestamps&&(u.token_timestamps=this._extract_token_timestamps(u,n.alignment_heads,n.num_frames)),u}_extract_token_timestamps(e,n,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&&console.warn("`num_frames` has not been set, meaning the entire audio will be analyzed. 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