


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase      =   logging.get_logger(__name__)

UpperCAmelCase      =   """▁"""

UpperCAmelCase      =   {"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

UpperCAmelCase      =   {
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

UpperCAmelCase      =   {"""vinai/bartpho-syllable""": 1024}







class lowerCAmelCase_						(			__lowerCamelCase	):

 '''simple docstring'''

 __snake_case												=  VOCAB_FILES_NAMES
 __snake_case												=  PRETRAINED_VOCAB_FILES_MAP
 __snake_case												=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __snake_case												=  ["""input_ids""", """attention_mask"""]



 def __init__(     self		,				_UpperCAmelCase		,				_UpperCAmelCase		,				_UpperCAmelCase="<s>"		,				_UpperCAmelCase="</s>"		,				_UpperCAmelCase="</s>"		,				_UpperCAmelCase="<s>"		,				_UpperCAmelCase="<unk>"		,				_UpperCAmelCase="<pad>"		,				_UpperCAmelCase="<mask>"		,				_UpperCAmelCase = None		,				**_UpperCAmelCase		,				):
       # Mask token behave like a normal word, i.e. include the space before it
       snake_case_	=				AddedToken(__lowercase		,				lstrip=__lowercase		,				rstrip=__lowercase ) if isinstance(__lowercase		,				__lowercase ) else mask_token

       snake_case_	=				{} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=__lowercase		,				eos_token=__lowercase		,				unk_token=__lowercase		,				sep_token=__lowercase		,				cls_token=__lowercase		,				pad_token=__lowercase		,				mask_token=__lowercase		,				sp_model_kwargs=self.sp_model_kwargs		,				**__lowercase		,				)

       snake_case_	=				vocab_file
       snake_case_	=				monolingual_vocab_file
       snake_case_	=				spm.SentencePieceProcessor(**self.sp_model_kwargs )
       self.sp_model.Load(str(__lowercase ) )

       # Load the reduced vocab

       # Keep order of special tokens for backward compatibility
       snake_case_	=				{}
       snake_case_	=				0
       for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
             if str(__lowercase ) not in self.fairseq_tokens_to_ids:
                   snake_case_	=				cnt
                   cnt += 1
       with open(__lowercase		,				'''r'''		,				encoding='''utf-8''' ) as f:
             for line in f.readlines():
                   snake_case_	=				line.strip().split()[0]
                   snake_case_	=				len(self.fairseq_tokens_to_ids )
       if str(__lowercase ) not in self.fairseq_tokens_to_ids:
             snake_case_	=				len(self.fairseq_tokens_to_ids )

       snake_case_	=				{v: k for k, v in self.fairseq_tokens_to_ids.items()}



 def __getstate__(     self ):
       snake_case_	=				self.__dict__.copy()
       snake_case_	=				None
       snake_case_	=				self.sp_model.serialized_model_proto()
       return state



 def __setstate__(     self		,				_UpperCAmelCase ):
       snake_case_	=				d

       # for backward compatibility
       if not hasattr(self		,				'''sp_model_kwargs''' ):
             snake_case_	=				{}

       snake_case_	=				spm.SentencePieceProcessor(**self.sp_model_kwargs )
       self.sp_model.LoadFromSerializedProto(self.sp_model_proto )



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase = None ):

       if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       snake_case_	=				[self.cls_token_id]
       snake_case_	=				[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase = None		,				_UpperCAmelCase = False ):

       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=__lowercase		,				token_ids_a=__lowercase		,				already_has_special_tokens=__lowercase )

       if token_ids_a is None:
             return [1] + ([0] * len(__lowercase )) + [1]
       return [1] + ([0] * len(__lowercase )) + [1, 1] + ([0] * len(__lowercase )) + [1]



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase = None ):
       snake_case_	=				[self.sep_token_id]
       snake_case_	=				[self.cls_token_id]

       if token_ids_a is None:
             return len(cls + token_ids_a + sep ) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]



 @property
 def 						UpperCamelCase__					(     self ):
       return len(self.fairseq_ids_to_tokens )



 def 						UpperCamelCase__					(     self ):
       snake_case_	=				{self.convert_ids_to_tokens(__lowercase ): i for i in range(self.vocab_size )}
       vocab.update(self.added_tokens_encoder )
       return vocab



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       return self.sp_model.encode(__lowercase		,				out_type=__lowercase )



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       if token in self.fairseq_tokens_to_ids:
             return self.fairseq_tokens_to_ids[token]
       else:
             return self.unk_token_id



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       return self.fairseq_ids_to_tokens[index]



 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase ):
       snake_case_	=				''''''.join(__lowercase ).replace(__lowercase		,				''' ''' ).strip()
       return out_string





 def 						UpperCamelCase__					(     self		,				_UpperCAmelCase		,				_UpperCAmelCase = None ):
       if not os.path.isdir(__lowercase ):
             logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
             return
       snake_case_	=				os.path.join(
           __lowercase		,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )
       snake_case_	=				os.path.join(
           __lowercase		,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''monolingual_vocab_file''']		,				)

       if os.path.abspath(self.vocab_file ) != os.path.abspath(__lowercase ) and os.path.isfile(self.vocab_file ):
             copyfile(self.vocab_file		,				__lowercase )
       elif not os.path.isfile(self.vocab_file ):
             with open(__lowercase		,				'''wb''' ) as fi:
                   snake_case_	=				self.sp_model.serialized_model_proto()
                   fi.write(__lowercase )

       if os.path.abspath(self.monolingual_vocab_file ) != os.path.abspath(
           __lowercase ) and os.path.isfile(self.monolingual_vocab_file ):
             copyfile(self.monolingual_vocab_file		,				__lowercase )
       elif not os.path.isfile(self.monolingual_vocab_file ):
             with open(__lowercase		,				'''w'''		,				encoding='''utf-8''' ) as fp:
                   for token in self.fairseq_tokens_to_ids:
                         if token not in self.all_special_tokens:
                               fp.write(F'''{str(__lowercase )} \n''' )

       return out_vocab_file, out_monolingual_vocab_file



import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE )->  Tuple:




      """simple docstring"""

      if (
          (cp >= 0X4E00 and cp <= 0X9FFF)
          or (cp >= 0X3400 and cp <= 0X4DBF)  #
          or (cp >= 0X2_0000 and cp <= 0X2_A6DF)  #
          or (cp >= 0X2_A700 and cp <= 0X2_B73F)  #
          or (cp >= 0X2_B740 and cp <= 0X2_B81F)  #
          or (cp >= 0X2_B820 and cp <= 0X2_CEAF)  #
          or (cp >= 0XF900 and cp <= 0XFAFF)
          or (cp >= 0X2_F800 and cp <= 0X2_FA1F)  #
      ):  #
            return True

      return False






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE )->  List[Any]:




      """simple docstring"""

      for char in word:
            snake_case_	=				ord(SCREAMING_SNAKE_CASE )
            if not _is_chinese_char(SCREAMING_SNAKE_CASE ):
                  return 0
      return 1






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE )->  str:




      """simple docstring"""

      snake_case_	=				set()

      for token in tokens:
            snake_case_	=				len(SCREAMING_SNAKE_CASE ) > 1 and is_chinese(SCREAMING_SNAKE_CASE )
            if chinese_word:
                  word_set.add(SCREAMING_SNAKE_CASE )
      snake_case_	=				list(SCREAMING_SNAKE_CASE )
      return word_list






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )->  List[str]:




      """simple docstring"""

      if not chinese_word_set:
            return bert_tokens
      snake_case_	=				max([len(SCREAMING_SNAKE_CASE ) for w in chinese_word_set] )

      snake_case_	=				bert_tokens
      snake_case_	,   snake_case_	=				0, len(SCREAMING_SNAKE_CASE )
      while start < end:
            snake_case_	=				True
            if is_chinese(bert_word[start] ):
                  snake_case_	=				min(end - start , SCREAMING_SNAKE_CASE )
                  for i in range(SCREAMING_SNAKE_CASE , 1 , -1 ):
                        snake_case_	=				''''''.join(bert_word[start : start + i] )
                        if whole_word in chinese_word_set:
                              for j in range(start + 1 , start + i ):
                                    snake_case_	=				'''##''' + bert_word[j]
                              snake_case_	=				start + i
                              snake_case_	=				False
                              break
            if single_word:
                  start += 1
      return bert_word






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )->  Any:




      """simple docstring"""

      snake_case_	=				[]

      for i in range(0 , len(SCREAMING_SNAKE_CASE ) , 100 ):
            snake_case_	=				ltp_tokenizer.pipeline(lines[i : i + 100] , tasks=['''cws'''] ).cws
            snake_case_	=				[get_chinese_word(SCREAMING_SNAKE_CASE ) for r in res]
            ltp_res.extend(SCREAMING_SNAKE_CASE )
      assert len(SCREAMING_SNAKE_CASE ) == len(SCREAMING_SNAKE_CASE )

      snake_case_	=				[]
      for i in range(0 , len(SCREAMING_SNAKE_CASE ) , 100 ):
            snake_case_	=				bert_tokenizer(lines[i : i + 100] , add_special_tokens=SCREAMING_SNAKE_CASE , truncation=SCREAMING_SNAKE_CASE , max_length=512 )
            bert_res.extend(res['''input_ids'''] )
      assert len(SCREAMING_SNAKE_CASE ) == len(SCREAMING_SNAKE_CASE )

      snake_case_	=				[]
      for input_ids, chinese_word in zip(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
            snake_case_	=				[]
            for id in input_ids:
                  snake_case_	=				bert_tokenizer._convert_id_to_token(SCREAMING_SNAKE_CASE )
                  input_tokens.append(SCREAMING_SNAKE_CASE )
            snake_case_	=				add_sub_symbol(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
            snake_case_	=				[]
            # We only save pos of chinese subwords start with ##, which mean is part of a whole word.
            for i, token in enumerate(SCREAMING_SNAKE_CASE ):
                  if token[:2] == "##":
                        snake_case_	=				token[2:]
                        # save chinese tokens' pos
                        if len(SCREAMING_SNAKE_CASE ) == 1 and _is_chinese_char(ord(SCREAMING_SNAKE_CASE ) ):
                              ref_id.append(SCREAMING_SNAKE_CASE )
            ref_ids.append(SCREAMING_SNAKE_CASE )

      assert len(SCREAMING_SNAKE_CASE ) == len(SCREAMING_SNAKE_CASE )

      return ref_ids






def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE )->  Tuple:




      """simple docstring"""

      with open(args.file_name , '''r''' , encoding='''utf-8''' ) as f:
            snake_case_	=				f.readlines()
      snake_case_	=				[line.strip() for line in data if len(SCREAMING_SNAKE_CASE ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
      snake_case_	=				LTP(args.ltp )  # faster in GPU device
      snake_case_	=				BertTokenizer.from_pretrained(args.bert )

      snake_case_	=				prepare_ref(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )

      with open(args.save_path , '''w''' , encoding='''utf-8''' ) as f:
            snake_case_	=				[json.dumps(SCREAMING_SNAKE_CASE ) + '''\n''' for ref in ref_ids]
            f.writelines(SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
   UpperCAmelCase      =   argparse.ArgumentParser(description="""prepare_chinese_ref""")
   parser.add_argument(
       """--file_name""",
       required=False,
       type=str,
       default="""./resources/chinese-demo.txt""",
       help="""file need process, same as training data in lm""",
   )
   parser.add_argument(
       """--ltp""",
       required=False,
       type=str,
       default="""./resources/ltp""",
       help="""resources for LTP tokenizer, usually a path""",
   )
   parser.add_argument(
       """--bert""",
       required=False,
       type=str,
       default="""./resources/robert""",
       help="""resources for Bert tokenizer""",
   )
   parser.add_argument(
       """--save_path""",
       required=False,
       type=str,
       default="""./resources/ref.txt""",
       help="""path to save res""",
   )

   UpperCAmelCase      =   parser.parse_args()
   main(args)