KoichiYasuoka
commited on
Commit
•
3d47df5
1
Parent(s):
6e19526
juman separated
Browse files- juman.py +48 -0
- tokenizer_config.json +1 -1
- ud.py +1 -48
juman.py
ADDED
@@ -0,0 +1,48 @@
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import os
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from transformers import AlbertTokenizerFast
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from transformers.models.bert_japanese.tokenization_bert_japanese import MecabTokenizer
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try:
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from transformers.utils import cached_file
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except:
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from transformers.file_utils import cached_path,hf_bucket_url
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cached_file=lambda x,y:os.path.join(x,y) if os.path.isdir(x) else cached_path(hf_bucket_url(x,y))
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class MecabPreTokenizer(MecabTokenizer):
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def mecab_split(self,i,normalized_string):
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t=str(normalized_string)
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z=[]
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e=0
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for c in self.tokenize(t):
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s=t.find(c,e)
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e=e if s<0 else s+len(c)
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z.append((0,0) if s<0 else (s,e))
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return [normalized_string[s:e] for s,e in z if e>0]
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def pre_tokenize(self,pretok):
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pretok.split(self.mecab_split)
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class JumanAlbertTokenizerFast(AlbertTokenizerFast):
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def __init__(self,**kwargs):
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from tokenizers.pre_tokenizers import PreTokenizer,Metaspace,Sequence
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super().__init__(**kwargs)
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d,r="/var/lib/mecab/dic/juman-utf8","/etc/mecabrc"
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if not (os.path.isdir(d) and os.path.isfile(r)):
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import zipfile
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import tempfile
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self.dicdir=tempfile.TemporaryDirectory()
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d=self.dicdir.name
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with zipfile.ZipFile(cached_file(self.name_or_path,"mecab-jumandic-utf8.zip")) as z:
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z.extractall(d)
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r=os.path.join(d,"mecabrc")
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with open(r,"w",encoding="utf-8") as w:
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print("dicdir =",d,file=w)
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self.custom_pre_tokenizer=Sequence([PreTokenizer.custom(MecabPreTokenizer(mecab_dic=None,mecab_option="-d "+d+" -r "+r)),Metaspace()])
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self._tokenizer.pre_tokenizer=self.custom_pre_tokenizer
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def save_pretrained(self,save_directory,**kwargs):
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import shutil
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from tokenizers.pre_tokenizers import Metaspace
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self._auto_map={"AutoTokenizer":[None,"juman.JumanAlbertTokenizerFast"]}
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self._tokenizer.pre_tokenizer=Metaspace()
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super().save_pretrained(save_directory,**kwargs)
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self._tokenizer.pre_tokenizer=self.custom_pre_tokenizer
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shutil.copy(os.path.abspath(__file__),os.path.join(save_directory,"juman.py"))
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shutil.copy(cached_file(self.name_or_path,"mecab-jumandic-utf8.zip"),os.path.join(save_directory,"mecab-jumandic-utf8.zip"))
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tokenizer_config.json
CHANGED
@@ -1,5 +1,5 @@
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{
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"auto_map": {"AutoTokenizer":[
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"do_lower_case": false,
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{
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"auto_map": {"AutoTokenizer":[null,"juman.JumanAlbertTokenizerFast"]},
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"bos_token": "[CLS]",
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"cls_token": "[CLS]",
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"do_lower_case": false,
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ud.py
CHANGED
@@ -1,11 +1,4 @@
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import
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from transformers import TokenClassificationPipeline,AlbertTokenizerFast,BertJapaneseTokenizer
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from transformers.models.bert_japanese.tokenization_bert_japanese import MecabTokenizer
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try:
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from transformers.utils import cached_file
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except:
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from transformers.file_utils import cached_path,hf_bucket_url
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cached_file=lambda x,y:os.path.join(x,y) if os.path.isdir(x) else cached_path(hf_bucket_url(x,y))
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class UniversalDependenciesPipeline(TokenClassificationPipeline):
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def _forward(self,model_inputs):
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i=y[numpy.nanargmax(z[x[k[-1]],y] if k[-1]<len(x) else z[y,y])]
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h[i]=x[k[-1]] if k[-1]<len(x) else i
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return h
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class MecabPreTokenizer(MecabTokenizer):
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def mecab_split(self,i,normalized_string):
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t=str(normalized_string)
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e=0
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z=[]
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for c in self.tokenize(t):
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s=t.find(c,e)
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e=e if s<0 else s+len(c)
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z.append((0,0) if s<0 else (s,e))
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return [normalized_string[s:e] for s,e in z if e>0]
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def pre_tokenize(self,pretok):
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pretok.split(self.mecab_split)
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class JumanAlbertTokenizerFast(AlbertTokenizerFast):
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def __init__(self,**kwargs):
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from tokenizers.pre_tokenizers import PreTokenizer,Metaspace,Sequence
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super().__init__(**kwargs)
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d,r="/var/lib/mecab/dic/juman-utf8","/etc/mecabrc"
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if not (os.path.isdir(d) and os.path.isfile(r)):
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import zipfile
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import tempfile
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self.dicdir=tempfile.TemporaryDirectory()
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d=self.dicdir.name
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with zipfile.ZipFile(cached_file(self.name_or_path,"mecab-jumandic-utf8.zip")) as z:
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z.extractall(d)
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r=os.path.join(d,"mecabrc")
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with open(r,"w",encoding="utf-8") as w:
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print("dicdir =",d,file=w)
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self.custom_pre_tokenizer=Sequence([PreTokenizer.custom(MecabPreTokenizer(mecab_dic=None,mecab_option="-d "+d+" -r "+r)),Metaspace()])
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self._tokenizer.pre_tokenizer=self.custom_pre_tokenizer
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def save_pretrained(self,save_directory,**kwargs):
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import shutil
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from tokenizers.pre_tokenizers import Metaspace
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self._auto_map={"AutoTokenizer":["ud.BertJapaneseTokenizer","ud.JumanAlbertTokenizerFast"]}
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self._tokenizer.pre_tokenizer=Metaspace()
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super().save_pretrained(save_directory,**kwargs)
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self._tokenizer.pre_tokenizer=self.custom_pre_tokenizer
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shutil.copy(os.path.abspath(__file__),os.path.join(save_directory,"ud.py"))
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shutil.copy(cached_file(self.name_or_path,"mecab-jumandic-utf8.zip"),os.path.join(save_directory,"mecab-jumandic-utf8.zip"))
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from transformers import TokenClassificationPipeline
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class UniversalDependenciesPipeline(TokenClassificationPipeline):
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def _forward(self,model_inputs):
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i=y[numpy.nanargmax(z[x[k[-1]],y] if k[-1]<len(x) else z[y,y])]
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h[i]=x[k[-1]] if k[-1]<len(x) else i
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return h
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