

'''simple docstring'''






import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer


def 	_A  (					A__   ):






 """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 	_A  (					A__   ):






 """simple docstring"""



 for char in word:
  __lowercase													=				ord(A__   )
  if not _is_chinese_char(A__   ):
   return 0
 return 1


def 	_A  (					A__   ):






 """simple docstring"""



 __lowercase													=				set()

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


def 	_A  (					A__  ,       A__   ):






 """simple docstring"""



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

 __lowercase													=				bert_tokens
 __lowercase						,			__lowercase													=				0, len(A__   )
 while start < end:
  __lowercase													=				True
  if is_chinese(bert_word[start]   ):
   __lowercase													=				min(end - start  ,       A__   )
   for i in range(A__  ,       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 	_A  (					A__  ,       A__  ,       A__   ):






 """simple docstring"""



 __lowercase													=				[]

 for i in range(0  ,       len(A__   )  ,       100   ):
  __lowercase													=				ltp_tokenizer.seg(lines[i : i + 100]   )[0]
  __lowercase													=				[get_chinese_word(A__   ) for r in res]
  ltp_res.extend(A__   )
 assert len(A__   ) == len(A__   )

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

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

 assert len(A__   ) == len(A__   )

 return ref_ids


def 	_A  (					A__   ):






 """simple docstring"""



 with open(args.file_name  ,       '''r'''  ,       encoding='''utf-8'''   ) as f:
  __lowercase													=				f.readlines()
 __lowercase													=				[line.strip() for line in data if len(A__   ) > 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(A__  ,       A__  ,       A__   )

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


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

 lowerCAmelCase__      		=			parser.parse_args()
 main(args)




'''simple docstring'''






import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs






class     lowercase_			(lowerCamelCase__   ):




  """simple docstring"""




  def __init__(   self     :  Optional[Any]      ,lowercase__     :  int      ,lowercase__     :  List[str]=None      ,lowercase__     :  Any=True      ,lowercase__     :  Union[str, Any]=None      ,**lowercase__     :  Dict    ):
   __lowercase													=				parent
   __lowercase													=				config_class
   __lowercase													=				has_text_modality
   __lowercase													=				kwargs
   __lowercase													=				common_properties






  def       SCREAMING_SNAKE_CASE   (   self     :  Any    ):
   __lowercase													=				self.config_class(**self.inputs_dict    )
   __lowercase													=				(
       ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
       if self.common_properties is None
       else self.common_properties
   )

   # Add common fields for text models
   if self.has_text_modality:
    common_properties.extend(['''vocab_size''']    )

   # Test that config has the common properties as getters
   for prop in common_properties:
    self.parent.assertTrue(hasattr(lowercase__      ,lowercase__    )      ,msg=F"`{prop}` does not exist"    )

   # Test that config has the common properties as setter
   for idx, name in enumerate(lowercase__    ):
    try:
     setattr(lowercase__      ,lowercase__      ,lowercase__    )
     self.parent.assertEqual(
         getattr(lowercase__      ,lowercase__    )      ,lowercase__      ,msg=F"`{name} value {idx} expected, but was {getattr(lowercase__      ,lowercase__    )}"    )
    except NotImplementedError:
     # Some models might not be able to implement setters for common_properties
     # In that case, a NotImplementedError is raised
     pass

        # Test if config class can be called with Config(prop_name=..)
   for idx, name in enumerate(lowercase__    ):
    try:
     __lowercase													=				self.config_class(**{name: idx}    )
     self.parent.assertEqual(
         getattr(lowercase__      ,lowercase__    )      ,lowercase__      ,msg=F"`{name} value {idx} expected, but was {getattr(lowercase__      ,lowercase__    )}"    )
    except NotImplementedError:
     # Some models might not be able to implement setters for common_properties
     # In that case, a NotImplementedError is raised
     pass






  def       SCREAMING_SNAKE_CASE   (   self     :  str    ):
   __lowercase													=				self.config_class(**self.inputs_dict    )
   __lowercase													=				json.loads(config.to_json_string()    )
   for key, value in self.inputs_dict.items():
    self.parent.assertEqual(obj[key]      ,lowercase__    )






  def       SCREAMING_SNAKE_CASE   (   self     :  int    ):
   __lowercase													=				self.config_class(**self.inputs_dict    )

   with tempfile.TemporaryDirectory() as tmpdirname:
    __lowercase													=				os.path.join(lowercase__      ,'''config.json'''    )
    config_first.to_json_file(lowercase__    )
    __lowercase													=				self.config_class.from_json_file(lowercase__    )

   self.parent.assertEqual(config_second.to_dict()      ,config_first.to_dict()    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Optional[Any]    ):
   __lowercase													=				self.config_class(**self.inputs_dict    )

   with tempfile.TemporaryDirectory() as tmpdirname:
    config_first.save_pretrained(lowercase__    )
    __lowercase													=				self.config_class.from_pretrained(lowercase__    )

   self.parent.assertEqual(config_second.to_dict()      ,config_first.to_dict()    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Any    ):
   __lowercase													=				self.config_class(**self.inputs_dict    )

   __lowercase													=				'''test'''
   with tempfile.TemporaryDirectory() as tmpdirname:
    __lowercase													=				os.path.join(lowercase__      ,lowercase__    )
    config_first.save_pretrained(lowercase__    )
    __lowercase													=				self.config_class.from_pretrained(lowercase__      ,subfolder=lowercase__    )

   self.parent.assertEqual(config_second.to_dict()      ,config_first.to_dict()    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Optional[Any]    ):
   __lowercase													=				self.config_class(**self.inputs_dict      ,num_labels=5    )
   self.parent.assertEqual(len(config.idalabel    )      ,5    )
   self.parent.assertEqual(len(config.labelaid    )      ,5    )

   __lowercase													=				3
   self.parent.assertEqual(len(config.idalabel    )      ,3    )
   self.parent.assertEqual(len(config.labelaid    )      ,3    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Tuple    ):
   if self.config_class.is_composition:
    return
   __lowercase													=				self.config_class()
   self.parent.assertIsNotNone(lowercase__    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Any    ):
   __lowercase													=				copy.deepcopy(lowercase__    )
   __lowercase													=				self.config_class(**lowercase__    )
   __lowercase													=				[]
   for key, value in config_common_kwargs.items():
    if key == "torch_dtype":
     if not is_torch_available():
      continue
     else:
      import torch

      if config.torch_dtype != torch.floataa:
       wrong_values.append(('''torch_dtype''', config.torch_dtype, torch.floataa)    )
    elif getattr(lowercase__      ,lowercase__    ) != value:
     wrong_values.append((key, getattr(lowercase__      ,lowercase__    ), value)    )

   if len(lowercase__    ) > 0:
    __lowercase													=				'''\n'''.join([F"- {v[0]}: got {v[1]} instead of {v[2]}" for v in wrong_values]    )
    raise ValueError(F"The following keys were not properly set in the config:\n{errors}"    )






  def       SCREAMING_SNAKE_CASE   (   self     :  Optional[int]    ):
   self.create_and_test_config_common_properties()
   self.create_and_test_config_to_json_string()
   self.create_and_test_config_to_json_file()
   self.create_and_test_config_from_and_save_pretrained()
   self.create_and_test_config_from_and_save_pretrained_subfolder()
   self.create_and_test_config_with_num_labels()
   self.check_config_can_be_init_without_params()
   self.check_config_arguments_init()

