
"""simple docstring"""






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

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_pegasus import PegasusTokenizer
else:
 __SCREAMING_SNAKE_CASE							=     None


__SCREAMING_SNAKE_CASE							=     logging.get_logger(__name__)


__SCREAMING_SNAKE_CASE							=     '▁'

__SCREAMING_SNAKE_CASE							=     {'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}

__SCREAMING_SNAKE_CASE							=     {
    'vocab_file': {'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/spiece.model'},
    'tokenizer_file': {
        'google/pegasus-xsum': 'https://huggingface.co/google/pegasus-xsum/resolve/main/tokenizer.json'
    },
}

__SCREAMING_SNAKE_CASE							=     {
    'google/pegasus-xsum': 512,
}





class 				a__					(						A__       ):
     UpperCAmelCase__         =      VOCAB_FILES_NAMES
     UpperCAmelCase__         =      PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__         =      PegasusTokenizer
     UpperCAmelCase__         =      ['''input_ids''', '''attention_mask''']



     def __init__(							self :Any      ,  _lowerCamelCase :Union[str, Any]=None      ,  _lowerCamelCase :Optional[int]=None      ,  _lowerCamelCase :Optional[Any]="<pad>"      ,  _lowerCamelCase :Dict="</s>"      ,  _lowerCamelCase :List[str]="<unk>"      ,  _lowerCamelCase :Any="<mask_2>"      ,  _lowerCamelCase :Optional[Any]="<mask_1>"      ,  _lowerCamelCase :str=None      ,  _lowerCamelCase :List[Any]=103      ,  **_lowerCamelCase :List[str]      ,  ):







      '''simple docstring'''



      UpperCamelCase_     :					str   	=offset

      if additional_special_tokens is not None:
       if not isinstance(_lowerCamelCase      ,  _lowerCamelCase   ):
        raise TypeError(
            f'''additional_special_tokens should be of type {type(_lowerCamelCase   )}, but is'''
            f''' {type(_lowerCamelCase   )}'''   )

       UpperCamelCase_     :					List[Any]   	=(
           ([mask_token_sent] + additional_special_tokens)
           if mask_token_sent not in additional_special_tokens and mask_token_sent is not None
           else additional_special_tokens
       )
       # fill additional tokens with ..., <unk_token_102> in case not all additional tokens are already taken
       additional_special_tokens_extended += [
           f'''<unk_{i}>''' for i in range(len(_lowerCamelCase   )      ,  self.offset - 1   )
       ]

       if len(set(_lowerCamelCase   )   ) != len(_lowerCamelCase   ):
        raise ValueError(
            'Please make sure that the provided additional_special_tokens do not contain an incorrectly'
            f''' shifted list of <unk_x> tokens. Found {additional_special_tokens_extended}.'''   )
       UpperCamelCase_     :					Any   	=additional_special_tokens_extended
      else:
       UpperCamelCase_     :					List[str]   	=[mask_token_sent] if mask_token_sent is not None else []
       additional_special_tokens += [f'''<unk_{i}>''' for i in range(2      ,  self.offset   )]

      super().__init__(
          _lowerCamelCase      ,  tokenizer_file=_lowerCamelCase      ,  pad_token=_lowerCamelCase      ,  eos_token=_lowerCamelCase      ,  unk_token=_lowerCamelCase      ,  mask_token=_lowerCamelCase      ,  mask_token_sent=_lowerCamelCase      ,  offset=_lowerCamelCase      ,  additional_special_tokens=_lowerCamelCase      ,  **_lowerCamelCase      ,  )
      UpperCamelCase_     :					Dict   	=vocab_file
      UpperCamelCase_     :					List[Any]   	=False if not self.vocab_file else True



     def  lowerCamelCase_						(							self :List[Any]      ,  _lowerCamelCase :Optional[int]   ):







      '''simple docstring'''



      UpperCamelCase_     :					List[Any]   	=set(self.all_special_ids   )  # call it once instead of inside list comp
      all_special_ids.remove(self.unk_token_id   )  # <unk> is only sometimes special

      if all_special_ids != set(range(len(self.additional_special_tokens   ) + 3   )   ):
       raise ValueError(
           'There should be 3 special tokens: mask_token, pad_token, and eos_token +'
           f''' {len(self.additional_special_tokens   )} additional_special_tokens, but got {all_special_ids}'''   )

      return [1 if x in all_special_ids else 0 for x in seq]



     def  lowerCamelCase_						(							self :Dict      ,  _lowerCamelCase :List      ,  _lowerCamelCase :Optional[List] = None      ,  _lowerCamelCase :bool = False   ):







      '''simple docstring'''



      if already_has_special_tokens:
       return self._special_token_mask(_lowerCamelCase   )
      elif token_ids_a is None:
       return self._special_token_mask(_lowerCamelCase   ) + [1]
      else:
       return self._special_token_mask(token_ids_a + token_ids_a   ) + [1]



     def  lowerCamelCase_						(							self :Optional[Any]      ,  _lowerCamelCase :Dict      ,  _lowerCamelCase :Tuple=None   ):







      '''simple docstring'''



      if token_ids_a is None:
       return token_ids_a + [self.eos_token_id]
      # We don't expect to process pairs, but leave the pair logic for API consistency
      return token_ids_a + token_ids_a + [self.eos_token_id]




     def  lowerCamelCase_						(							self :Optional[int]      ,  _lowerCamelCase :str      ,  _lowerCamelCase :Optional[str] = None   ):







      '''simple docstring'''



      if not self.can_save_slow_tokenizer:
       raise ValueError(
           'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
           'tokenizer.'   )

      if not os.path.isdir(_lowerCamelCase   ):
       logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
       return
      UpperCamelCase_     :					Optional[Any]   	=os.path.join(
          _lowerCamelCase      ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']   )

      if os.path.abspath(self.vocab_file   ) != os.path.abspath(_lowerCamelCase   ):
       copyfile(self.vocab_file      ,  _lowerCamelCase   )

      return (out_vocab_file,)


"""simple docstring"""






import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer




def       A_  (				__lowercase	):
 # 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       A_  (				__lowercase	):
 # word like '180' or '身高' or '神'
 for char in word:
  UpperCamelCase_     :					Union[str, Any]   	=ord(__lowercase	)
  if not _is_chinese_char(__lowercase	):
   return 0
 return 1




def       A_  (				__lowercase	):
 UpperCamelCase_     :					List[str]   	=set()

 for token in tokens:
  UpperCamelCase_     :					Optional[int]   	=len(__lowercase	) > 1 and is_chinese(__lowercase	)
  if chinese_word:
   word_set.add(__lowercase	)
 UpperCamelCase_     :					Tuple   	=list(__lowercase	)
 return word_list




def       A_  (				__lowercase						,	__lowercase	):
 if not chinese_word_set:
  return bert_tokens
 UpperCamelCase_     :					List[str]   	=max([len(__lowercase	) for w in chinese_word_set]	)

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




def       A_  (				__lowercase						,	__lowercase						,	__lowercase	):
 UpperCamelCase_     :					Tuple   	=[]

 for i in range(0						,	len(__lowercase	)						,	1_00	):
  UpperCamelCase_     :					Union[str, Any]   	=ltp_tokenizer.seg(lines[i : i + 1_00]	)[0]
  UpperCamelCase_     :					int   	=[get_chinese_word(__lowercase	) for r in res]
  ltp_res.extend(__lowercase	)
 assert len(__lowercase	) == len(__lowercase	)

 UpperCamelCase_     :					Dict   	=[]
 for i in range(0						,	len(__lowercase	)						,	1_00	):
  UpperCamelCase_     :					int   	=bert_tokenizer(lines[i : i + 1_00]						,	add_special_tokens=__lowercase						,	truncation=__lowercase						,	max_length=5_12	)
  bert_res.extend(res['input_ids']	)
 assert len(__lowercase	) == len(__lowercase	)

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

 assert len(__lowercase	) == len(__lowercase	)

 return ref_ids




def       A_  (				__lowercase	):
 # 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:
  UpperCamelCase_     :					Tuple   	=f.readlines()
 UpperCamelCase_     :					Optional[int]   	=[line.strip() for line in data if len(__lowercase	) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
 UpperCamelCase_     :					Optional[Any]   	=LTP(args.ltp	)  # faster in GPU device
 UpperCamelCase_     :					Dict   	=BertTokenizer.from_pretrained(args.bert	)

 UpperCamelCase_     :					int   	=prepare_ref(__lowercase						,	__lowercase						,	__lowercase	)

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


if __name__ == "__main__":
 __SCREAMING_SNAKE_CASE							=     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')

 __SCREAMING_SNAKE_CASE							=     parser.parse_args()
 main(args)
