



'''simple docstring'''





from typing import Dict, List, Optional

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


_lowerCAmelCase      						=	logging.get_logger(__name__)


_lowerCAmelCase      						=	{
    '''nielsr/canine-s''': 2048,
}

# Unicode defines 1,114,112 total “codepoints”
_lowerCAmelCase      						=	111_4112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
_lowerCAmelCase      						=	0

_lowerCAmelCase      						=	0xe_000
_lowerCAmelCase      						=	0xe_001
_lowerCAmelCase      						=	0xe_002
_lowerCAmelCase      						=	0xe_003
_lowerCAmelCase      						=	0xe_004

# Maps special codepoints to human-readable names.
_lowerCAmelCase      						=	{
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: '''[CLS]''',
    SEP: '''[SEP]''',
    BOS: '''[BOS]''',
    MASK: '''[MASK]''',
    PAD: '''[PAD]''',
    RESERVED: '''[RESERVED]''',
}

# Maps special codepoint human-readable names to their codepoint values.
_lowerCAmelCase      						=	{name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}






class        lowerCAmelCase_(				SCREAMING_SNAKE_CASE__     ):
  '''simple docstring'''




  __lowercase							:      Optional[int]				=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




  def __init__(    self  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=chr(__lowerCamelCase      )  ,__UpperCAmelCase=False  ,__UpperCAmelCase=2048  ,**__UpperCAmelCase  ,)    ->		Dict:
      lowerCAmelCase__ :  Optional[int]							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else bos_token
      lowerCAmelCase__ :  str							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else eos_token
      lowerCAmelCase__ :  Tuple							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else sep_token
      lowerCAmelCase__ :  int							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else cls_token
      lowerCAmelCase__ :  Union[str, Any]							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      lowerCAmelCase__ :  Any							      =					AddedToken(__lowerCamelCase  ,lstrip=__lowerCamelCase  ,rstrip=__lowerCamelCase      ) if isinstance(__lowerCamelCase  ,__lowerCamelCase      ) else mask_token

      super().__init__(
          bos_token=__lowerCamelCase  ,eos_token=__lowerCamelCase  ,sep_token=__lowerCamelCase  ,cls_token=__lowerCamelCase  ,pad_token=__lowerCamelCase  ,mask_token=__lowerCamelCase  ,add_prefix_space=__lowerCamelCase  ,model_max_length=__lowerCamelCase  ,**__lowerCamelCase  ,)

      # Creates a mapping for looking up the IDs of special symbols.
      lowerCAmelCase__ :  Dict[str, int]							      =					{}
      for codepoint, name in SPECIAL_CODEPOINTS.items():
          lowerCAmelCase__ :  Union[str, Any]							      =					codepoint

      # Creates a mapping for looking up the string forms of special symbol IDs.
      lowerCAmelCase__ :  Dict[int, str]							      =					{
          codepoint: name for name, codepoint in self._special_codepoints.items()
      }

      lowerCAmelCase__ :  Tuple							      =					UNICODE_VOCAB_SIZE
      lowerCAmelCase__ :  int							      =					len(self._special_codepoints      )




  @property
  def 							UpperCAmelCase_	(    self      )    ->		Tuple:
      return self._unicode_vocab_size




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		List[str]:
      return list(__lowerCamelCase      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		List[str]:




      try:
          return ord(__lowerCamelCase      )
      except TypeError:
          raise ValueError(F"""invalid token: '{token}'"""      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Dict:




      try:
          if index in SPECIAL_CODEPOINTS:
              return SPECIAL_CODEPOINTS[index]
          return chr(__lowerCamelCase      )
      except TypeError:
          raise ValueError(F"""invalid id: {index}"""      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase      )    ->		Union[str, Any]:
      return "".join(__lowerCamelCase      )




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		Dict:
      lowerCAmelCase__ :  Union[str, Any]							      =					[self.sep_token_id]
      lowerCAmelCase__ :  List[Any]							      =					[self.cls_token_id]

      lowerCAmelCase__ :  Dict							      =					cls + token_ids_a + sep
      if token_ids_a is not None:
          result += token_ids_a + sep
      return result




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None  ,__UpperCAmelCase = False      )    ->		int:




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

      lowerCAmelCase__ :  Optional[Any]							      =					[1] + ([0] * len(__lowerCamelCase      )) + [1]
      if token_ids_a is not None:
          result += ([0] * len(__lowerCamelCase      )) + [1]
      return result




  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		Any:
      lowerCAmelCase__ :  str							      =					[self.sep_token_id]
      lowerCAmelCase__ :  str							      =					[self.cls_token_id]

      lowerCAmelCase__ :  str							      =					len(cls + token_ids_a + sep      ) * [0]
      if token_ids_a is not None:
          result += len(token_ids_a + sep      ) * [1]
      return result






  def 							UpperCAmelCase_	(    self  ,__UpperCAmelCase  ,__UpperCAmelCase = None      )    ->		Tuple:
      return ()









"""simple docstring"""



import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer







def 		__lowercase     (   snake_case_  :  int						)   ->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 		__lowercase     (   snake_case_  :  str						)   ->Dict:



    '''simple docstring'''







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







def 		__lowercase     (   snake_case_  :  List[str]						)   ->List[Any]:



    '''simple docstring'''







    __A    :						str						 =     set()

    for token in tokens:
        __A    :						List[Any]						 =     len(snake_case_						) > 1 and is_chinese(snake_case_						)
        if chinese_word:
            word_set.add(snake_case_						)
    __A    :						Any						 =     list(snake_case_						)
    return word_list







def 		__lowercase     (   snake_case_  :  List[str]				,snake_case_  :  set()						)   ->Any:



    '''simple docstring'''







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

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







def 		__lowercase     (   snake_case_  :  List[str]				,snake_case_  :  LTP				,snake_case_  :  BertTokenizer						)   ->Dict:



    '''simple docstring'''







    __A    :						Optional[Any]						 =     []

    for i in range(0				,len(snake_case_						)				,100						):
        __A    :						int						 =     ltp_tokenizer.seg(lines[i : i + 100]						)[0]
        __A    :						List[Any]						 =     [get_chinese_word(snake_case_						) for r in res]
        ltp_res.extend(snake_case_						)
    assert len(snake_case_						) == len(snake_case_						)

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

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

    assert len(snake_case_						) == len(snake_case_						)

    return ref_ids







def 		__lowercase     (   snake_case_  :  int						)   ->List[Any]:



    '''simple docstring'''







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

    __A    :						Optional[Any]						 =     prepare_ref(snake_case_				,snake_case_				,snake_case_						)

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


if __name__ == "__main__":
       a_ =			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""")

       a_ =			parser.parse_args()
       main(args)




