


def 	__lowerCAmelCase   (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 0 , SCREAMING_SNAKE_CASE = 0 )->  Any:




      """simple docstring"""

      snake_case_	=				right or len(__a ) - 1
      if left > right:
            return -1
      elif list_data[left] == key:
            return left
      elif list_data[right] == key:
            return right
      else:
            return search(__a , __a , left + 1 , right - 1 )


if __name__ == "__main__":
   import doctest

   doctest.testmod()



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)