





import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       Tuple:
  # This defines a "chinese character" as anything in the CJK Unicode block:
  #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
  #
  # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
  # despite its name. The modern Korean Hangul alphabet is a different block,
  # as is Japanese Hiragana and Katakana. Those alphabets are used to write
  # space-separated words, so they are not treated specially and handled
  # like the all of the other languages.
  if (
      (cp >= 0x4_E_0_0 and cp <= 0x9_F_F_F)
      or (cp >= 0x3_4_0_0 and cp <= 0x4_D_B_F)  #
      or (cp >= 0x2_0_0_0_0 and cp <= 0x2_A_6_D_F)  #
      or (cp >= 0x2_A_7_0_0 and cp <= 0x2_B_7_3_F)  #
      or (cp >= 0x2_B_7_4_0 and cp <= 0x2_B_8_1_F)  #
      or (cp >= 0x2_B_8_2_0 and cp <= 0x2_C_E_A_F)  #
      or (cp >= 0xF_9_0_0 and cp <= 0xF_A_F_F)
      or (cp >= 0x2_F_8_0_0 and cp <= 0x2_F_A_1_F)  #
  ):  #
    return True

  return False




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       int:
  # word like '180' or '身高' or '神'
  for char in word:
    lowercase__           =  ord(_SCREAMING_SNAKE_CASE		)
    if not _is_chinese_char(_SCREAMING_SNAKE_CASE		):
      return 0
  return 1




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       str:
  lowercase__           =  set()

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




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  if not chinese_word_set:
    return bert_tokens
  lowercase__           =  max([len(_SCREAMING_SNAKE_CASE		) for w in chinese_word_set]		)

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




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  lowercase__           =  []

  for i in range(0		,						len(_SCREAMING_SNAKE_CASE		)		,						100		):
    lowercase__           =  ltp_tokenizer.seg(lines[i : i + 100]		)[0]
    lowercase__           =  [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		)

  lowercase__           =  []
  for i in range(0		,						len(_SCREAMING_SNAKE_CASE		)		,						100		):
    lowercase__           =  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		)

  lowercase__           =  []
  for input_ids, chinese_word in zip(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		):
    lowercase__           =  []
    for id in input_ids:
      lowercase__           =  bert_tokenizer._convert_id_to_token(_SCREAMING_SNAKE_CASE		)
      input_tokens.append(_SCREAMING_SNAKE_CASE		)
    lowercase__           =  add_sub_symbol(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)
    lowercase__           =  []
    # 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] == "##":
        lowercase__           =  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       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		)    ->       List[str]:
  # For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
  # If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
  with open(args.file_name		,						'r'		,						encoding='utf-8'		) as f:
    lowercase__           =  f.readlines()
  lowercase__           =  [line.strip() for line in data if len(_SCREAMING_SNAKE_CASE		) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
  lowercase__           =  LTP(args.ltp		)  # faster in GPU device
  lowercase__           =  BertTokenizer.from_pretrained(args.bert		)

  lowercase__           =  prepare_ref(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)

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


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

      lowercase_          =		parser.parse_args()
      main(args)









from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar

lowercase_          =		TypeVar("""KEY""")
lowercase_          =		TypeVar("""VAL""")
@dataclass(frozen=UpperCAmelCase      ,     slots=UpperCAmelCase				)
class     SCREAMING_SNAKE_CASE       (Generic[KEY, VAL]				):
   _UpperCamelCase   :		KEY
   _UpperCamelCase   :		VAL






class     SCREAMING_SNAKE_CASE       (_Item				):


   def __init__(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     super().__init__(a      ,					a	)


   def __bool__(   self      :    str	)->       bool:





     """simple docstring"""







     return False






lowercase_          =		_DeletedItem()
class     SCREAMING_SNAKE_CASE       (MutableMapping[KEY, VAL]				):


   def __init__(   self      :    Tuple      ,					a      :    int = 8      ,					a      :    float = 0.75	)->       None:





     """simple docstring"""







     lowercase__           =  initial_block_size
     lowercase__           =  [None] * initial_block_size
     assert 0.0 < capacity_factor < 1.0
     lowercase__           =  capacity_factor
     lowercase__           =  0


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    KEY	)->       int:





     """simple docstring"""







     return hash(a	) % len(self._buckets	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[Any]      ,					a      :    int	)->       int:





     """simple docstring"""







     return (ind + 1) % len(self._buckets	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    int      ,					a      :    KEY      ,					a      :    VAL	)->       bool:





     """simple docstring"""







     lowercase__           =  self._buckets[ind]
     if not stored:
       lowercase__           =  _Item(a      ,					a	)
       self._len += 1
       return True
     elif stored.key == key:
       lowercase__           =  _Item(a      ,					a	)
       return True
     else:
       return False


   def 	SCREAMING_SNAKE_CASE_							(   self      :    str	)->       bool:





     """simple docstring"""







     lowercase__           =  len(self._buckets	) * self._capacity_factor
     return len(self	) >= int(a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Tuple	)->       bool:





     """simple docstring"""







     if len(self._buckets	) <= self._initial_block_size:
       return False
     lowercase__           =  len(self._buckets	) * self._capacity_factor / 2
     return len(self	) < limit


   def 	SCREAMING_SNAKE_CASE_							(   self      :    List[str]      ,					a      :    int	)->       None:





     """simple docstring"""







     lowercase__           =  self._buckets
     lowercase__           =  [None] * new_size
     lowercase__           =  0
     for item in old_buckets:
       if item:
         self._add_item(item.key      ,					item.val	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     self._resize(len(self._buckets	) * 2	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       None:





     """simple docstring"""







     self._resize(len(self._buckets	) // 2	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Any      ,					a      :    KEY	)->       Iterator[int]:





     """simple docstring"""







     lowercase__           =  self._get_bucket_index(a	)
     for _ in range(len(self._buckets	)	):
       yield ind
       lowercase__           =  self._get_next_ind(a	)


   def 	SCREAMING_SNAKE_CASE_							(   self      :    Tuple      ,					a      :    KEY      ,					a      :    VAL	)->       None:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       if self._try_set(a      ,					a      ,					a	):
         break


   def __setitem__(   self      :    List[Any]      ,					a      :    KEY      ,					a      :    VAL	)->       None:





     """simple docstring"""







     if self._is_full():
       self._size_up()

     self._add_item(a      ,					a	)


   def __delitem__(   self      :    str      ,					a      :    KEY	)->       None:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       lowercase__           =  self._buckets[ind]
       if item is None:
         raise KeyError(a	)
       if item is _deleted:
         continue
       if item.key == key:
         lowercase__           =  _deleted
         self._len -= 1
         break
     if self._is_sparse():
       self._size_down()


   def __getitem__(   self      :    List[str]      ,					a      :    KEY	)->       VAL:





     """simple docstring"""







     for ind in self._iterate_buckets(a	):
       lowercase__           =  self._buckets[ind]
       if item is None:
         break
       if item is _deleted:
         continue
       if item.key == key:
         return item.val
     raise KeyError(a	)


   def __len__(   self      :    Tuple	)->       int:





     """simple docstring"""







     return self._len


   def __iter__(   self      :    int	)->       Iterator[KEY]:





     """simple docstring"""







     yield from (item.key for item in self._buckets if item)


   def __repr__(   self      :    Union[str, Any]	)->       str:





     """simple docstring"""







     lowercase__           =  ' ,'.join(
         f"""{item.key}: {item.val}""" for item in self._buckets if item	)
     return f"""HashMap({val_string})"""


