import{S as mo,i as fo,s as uo,e as o,k as p,w,t as r,M as ho,c as n,d as s,m as c,a,x as $,h as i,b as m,G as t,g as d,y as z,q as T,o as E,B as j,v as _o,L as ko}from"../../chunks/vendor-hf-doc-builder.js";import{D as Ne}from"../../chunks/Docstring-hf-doc-builder.js";import{C as Bs}from"../../chunks/CodeBlock-hf-doc-builder.js";import{I as qs}from"../../chunks/IconCopyLink-hf-doc-builder.js";import{E as go}from"../../chunks/ExampleCodeBlock-hf-doc-builder.js";function bo(Oe){let h,C,k,_,y;return _=new Bs({props:{code:`0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1
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| first sequence    | second sequence |`}}),{c(){h=o("p"),C=r("pair mask has the following format:"),k=p(),w(_.$$.fragment)},l(f){h=n(f,"P",{});var x=a(h);C=i(x,"pair mask has the following format:"),x.forEach(s),k=c(f),$(_.$$.fragment,f)},m(f,x){d(f,h,x),t(h,C),d(f,k,x),z(_,f,x),y=!0},p:ko,i(f){y||(T(_.$$.fragment,f),y=!0)},o(f){E(_.$$.fragment,f),y=!1},d(f){f&&s(h),f&&s(k),j(_,f)}}}function vo(Oe){let h,C,k,_,y,f,x,$e,ht,Re,B,D,ze,V,_t,Te,kt,We,pe,gt,Ue,ce,bt,Ve,A,P,vt,F,wt,$t,H,zt,Tt,Et,Ee,jt,Fe,b,yt,je,xt,qt,ye,Bt,Pt,xe,Jt,Lt,He,S,Ct,K,Dt,At,Ke,de,St,Xe,X,Ge,me,It,Qe,G,Ye,fe,Mt,Ze,ue,Q,Nt,he,Ot,Rt,et,I,Wt,Y,Ut,Vt,tt,J,M,qe,Z,Ft,Be,Ht,st,u,ee,Kt,Pe,Xt,Gt,te,Qt,_e,Yt,Zt,es,q,se,ts,Je,ss,os,oe,ke,ns,Le,as,rs,ge,is,Ce,ls,ps,N,ne,cs,De,ds,ms,v,ae,fs,Ae,us,hs,O,_s,L,ks,Se,gs,bs,Ie,vs,ws,$s,R,re,zs,ie,Ts,Me,Es,js,ot;return f=new qs({}),V=new qs({}),X=new Bs({props:{code:`import torch
from transformers import AutoModel, AutoTokenizer

bertjapanese = AutoModel.from_pretrained("cl-tohoku/bert-base-japanese")
tokenizer = AutoTokenizer.from_pretrained("cl-tohoku/bert-base-japanese")

## Input Japanese Text
line = "\u543E\u8F29\u306F\u732B\u3067\u3042\u308B\u3002"

inputs = tokenizer(line, return_tensors="pt")

print(tokenizer.decode(inputs["input_ids"][0]))

outputs = bertjapanese(**inputs)`,highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">import</span> torch
<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-keyword">from</span> transformers <span class="hljs-keyword">import</span> AutoModel, AutoTokenizer

<span class="hljs-meta">&gt;&gt;&gt; </span>bertjapanese = AutoModel.from_pretrained(<span class="hljs-string">&quot;cl-tohoku/bert-base-japanese&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;cl-tohoku/bert-base-japanese&quot;</span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment">## Input Japanese Text</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>line = <span class="hljs-string">&quot;\u543E\u8F29\u306F\u732B\u3067\u3042\u308B\u3002&quot;</span>

<span class="hljs-meta">&gt;&gt;&gt; </span>inputs = tokenizer(line, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(tokenizer.decode(inputs[<span class="hljs-string">&quot;input_ids&quot;</span>][<span class="hljs-number">0</span>]))
[CLS] \u543E\u8F29 \u306F \u732B \u3067 \u3042\u308B \u3002 [SEP]

<span class="hljs-meta">&gt;&gt;&gt; </span>outputs = bertjapanese(**inputs)`}}),G=new Bs({props:{code:`bertjapanese = AutoModel.from_pretrained("cl-tohoku/bert-base-japanese-char")
tokenizer = AutoTokenizer.from_pretrained("cl-tohoku/bert-base-japanese-char")

## Input Japanese Text
line = "\u543E\u8F29\u306F\u732B\u3067\u3042\u308B\u3002"

inputs = tokenizer(line, return_tensors="pt")

print(tokenizer.decode(inputs["input_ids"][0]))

outputs = bertjapanese(**inputs)`,highlighted:`<span class="hljs-meta">&gt;&gt;&gt; </span>bertjapanese = AutoModel.from_pretrained(<span class="hljs-string">&quot;cl-tohoku/bert-base-japanese-char&quot;</span>)
<span class="hljs-meta">&gt;&gt;&gt; </span>tokenizer = AutoTokenizer.from_pretrained(<span class="hljs-string">&quot;cl-tohoku/bert-base-japanese-char&quot;</span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-comment">## Input Japanese Text</span>
<span class="hljs-meta">&gt;&gt;&gt; </span>line = <span class="hljs-string">&quot;\u543E\u8F29\u306F\u732B\u3067\u3042\u308B\u3002&quot;</span>

<span class="hljs-meta">&gt;&gt;&gt; </span>inputs = tokenizer(line, return_tensors=<span class="hljs-string">&quot;pt&quot;</span>)

<span class="hljs-meta">&gt;&gt;&gt; </span><span class="hljs-built_in">print</span>(tokenizer.decode(inputs[<span class="hljs-string">&quot;input_ids&quot;</span>][<span class="hljs-number">0</span>]))
[CLS] \u543E \u8F29 \u306F \u732B \u3067 \u3042 \u308B \u3002 [SEP]

<span class="hljs-meta">&gt;&gt;&gt; </span>outputs = bertjapanese(**inputs)`}}),Z=new qs({}),ee=new Ne({props:{name:"class transformers.BertJapaneseTokenizer",anchor:"transformers.BertJapaneseTokenizer",parameters:[{name:"vocab_file",val:""},{name:"spm_file",val:" = None"},{name:"do_lower_case",val:" = False"},{name:"do_word_tokenize",val:" = True"},{name:"do_subword_tokenize",val:" = True"},{name:"word_tokenizer_type",val:" = 'basic'"},{name:"subword_tokenizer_type",val:" = 'wordpiece'"},{name:"never_split",val:" = None"},{name:"unk_token",val:" = '[UNK]'"},{name:"sep_token",val:" = '[SEP]'"},{name:"pad_token",val:" = '[PAD]'"},{name:"cls_token",val:" = '[CLS]'"},{name:"mask_token",val:" = '[MASK]'"},{name:"mecab_kwargs",val:" = None"},{name:"sudachi_kwargs",val:" = None"},{name:"jumanpp_kwargs",val:" = None"},{name:"**kwargs",val:""}],parametersDescription:[{anchor:"transformers.BertJapaneseTokenizer.vocab_file",description:`<strong>vocab_file</strong> (<code>str</code>) &#x2014;
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Dictionary passed to the <code>SudachiTokenizer</code> constructor.`,name:"sudachi_kwargs"},{anchor:"transformers.BertJapaneseTokenizer.jumanpp_kwargs",description:`<strong>jumanpp_kwargs</strong> (<code>dict</code>, <em>optional</em>) &#x2014;
Dictionary passed to the <code>JumanppTokenizer</code> constructor.`,name:"jumanpp_kwargs"}],source:"https://github.com/huggingface/transformers/blob/v4.29.0/src/transformers/models/bert_japanese/tokenization_bert_japanese.py#L107"}}),se=new Ne({props:{name:"build_inputs_with_special_tokens",anchor:"transformers.BertJapaneseTokenizer.build_inputs_with_special_tokens",parameters:[{name:"token_ids_0",val:": typing.List[int]"},{name:"token_ids_1",val:": typing.Optional[typing.List[int]] = None"}],parametersDescription:[{anchor:"transformers.BertJapaneseTokenizer.build_inputs_with_special_tokens.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
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Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/v4.29.0/src/transformers/models/bert_japanese/tokenization_bert_japanese.py#L308",returnDescription:`
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`,returnType:`
<p><code>List[int]</code></p>
`}}),ne=new Ne({props:{name:"convert_tokens_to_string",anchor:"transformers.BertJapaneseTokenizer.convert_tokens_to_string",parameters:[{name:"tokens",val:""}],source:"https://github.com/huggingface/transformers/blob/v4.29.0/src/transformers/models/bert_japanese/tokenization_bert_japanese.py#L300"}}),ae=new Ne({props:{name:"create_token_type_ids_from_sequences",anchor:"transformers.BertJapaneseTokenizer.create_token_type_ids_from_sequences",parameters:[{name:"token_ids_0",val:": typing.List[int]"},{name:"token_ids_1",val:": typing.Optional[typing.List[int]] = None"}],parametersDescription:[{anchor:"transformers.BertJapaneseTokenizer.create_token_type_ids_from_sequences.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs.`,name:"token_ids_0"},{anchor:"transformers.BertJapaneseTokenizer.create_token_type_ids_from_sequences.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
Optional second list of IDs for sequence pairs.`,name:"token_ids_1"}],source:"https://github.com/huggingface/transformers/blob/v4.29.0/src/transformers/models/bert_japanese/tokenization_bert_japanese.py#L363",returnDescription:`
<p>List of <a href="../glossary#token-type-ids">token type IDs</a> according to the given sequence(s).</p>
`,returnType:`
<p><code>List[int]</code></p>
`}}),O=new go({props:{anchor:"transformers.BertJapaneseTokenizer.create_token_type_ids_from_sequences.example",$$slots:{default:[bo]},$$scope:{ctx:Oe}}}),re=new Ne({props:{name:"get_special_tokens_mask",anchor:"transformers.BertJapaneseTokenizer.get_special_tokens_mask",parameters:[{name:"token_ids_0",val:": typing.List[int]"},{name:"token_ids_1",val:": typing.Optional[typing.List[int]] = None"},{name:"already_has_special_tokens",val:": bool = False"}],parametersDescription:[{anchor:"transformers.BertJapaneseTokenizer.get_special_tokens_mask.token_ids_0",description:`<strong>token_ids_0</strong> (<code>List[int]</code>) &#x2014;
List of IDs.`,name:"token_ids_0"},{anchor:"transformers.BertJapaneseTokenizer.get_special_tokens_mask.token_ids_1",description:`<strong>token_ids_1</strong> (<code>List[int]</code>, <em>optional</em>) &#x2014;
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Whether or not the token list is already formatted with special tokens for the model.`,name:"already_has_special_tokens"}],source:"https://github.com/huggingface/transformers/blob/v4.29.0/src/transformers/models/bert_japanese/tokenization_bert_japanese.py#L334",returnDescription:`
<p>A list of integers in the range [0, 1]: 1 for a special token, 0 for a sequence token.</p>
`,returnType:`
<p><code>List[int]</code></p>
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