code: 
  
  
  
  import os
  from shutil import copyfile
  from typing import Optional, Tuple
  
  from ...file_utils import is_sentencepiece_available
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  
  
  if is_sentencepiece_available():
  			from .tokenization_deberta_va import DebertaVaTokenizer
  else:
  			lowerCAmelCase__	:  Union[str, Any] 		=None
  
  lowerCAmelCase__	:  Any 		=logging.get_logger(__name__)
  
  lowerCAmelCase__	:  Union[str, Any] 		={'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}
  
  lowerCAmelCase__	:  str 		={
      '''vocab_file''': {
          '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
          '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
          '''microsoft/deberta-v2-xlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
          ),
          '''microsoft/deberta-v2-xxlarge-mnli''': (
              '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
          ),
      }
  }
  
  lowerCAmelCase__	:  Any 		={
      '''microsoft/deberta-v2-xlarge''': 512,
      '''microsoft/deberta-v2-xxlarge''': 512,
      '''microsoft/deberta-v2-xlarge-mnli''': 512,
      '''microsoft/deberta-v2-xxlarge-mnli''': 512,
  }
  
  lowerCAmelCase__	:  Any 		={
      '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
      '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
      '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
      '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
  }
  
  class      UpperCAmelCase_						(     UpperCamelCase_ ):
  
  						'''simple docstring'''
  
  
  
  
  						UpperCamelCase__    :				Optional[int]       						=						VOCAB_FILES_NAMES
  						UpperCamelCase__    :				int       						=						PRETRAINED_VOCAB_FILES_MAP
  						UpperCamelCase__    :				List[str]       						=						PRETRAINED_INIT_CONFIGURATION
  						UpperCamelCase__    :				int       						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  						UpperCamelCase__    :				Union[str, Any]       						=						DebertaVaTokenizer
  
  
  
  
  
  
  						def __init__(					self   ,							_A=None   ,							_A=None   ,							_A=False   ,							_A=False   ,							_A="[CLS]"   ,							_A="[SEP]"   ,							_A="[UNK]"   ,							_A="[SEP]"   ,							_A="[PAD]"   ,							_A="[CLS]"   ,							_A="[MASK]"   ,							**_A   ,							):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													super().__init__(
  													    _A   ,							tokenizer_file=_A   ,							do_lower_case=_A   ,							bos_token=_A   ,							eos_token=_A   ,							unk_token=_A   ,							sep_token=_A   ,							pad_token=_A   ,							cls_token=_A   ,							mask_token=_A   ,							split_by_punct=_A   ,							**_A   ,							)
  
  													__SCREAMING_SNAKE_CASE								=      do_lower_case
  													__SCREAMING_SNAKE_CASE								=      split_by_punct
  													__SCREAMING_SNAKE_CASE								=      vocab_file
  													__SCREAMING_SNAKE_CASE								=      False if not self.vocab_file else True
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A=None	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if token_ids_a is None:
  																				return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  													__SCREAMING_SNAKE_CASE								=      [self.cls_token_id]
  													__SCREAMING_SNAKE_CASE								=      [self.sep_token_id]
  													return cls + token_ids_a + sep + token_ids_a + sep
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A=None   ,							_A=False	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if already_has_special_tokens:
  																				return super().get_special_tokens_mask(
  																				    token_ids_a=_A   ,							token_ids_a=_A   ,							already_has_special_tokens=_A	)
  
  													if token_ids_a is not None:
  																				return [1] + ([0] * len(_A	)) + [1] + ([0] * len(_A	)) + [1]
  													return [1] + ([0] * len(_A	)) + [1]
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A=None	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      [self.sep_token_id]
  													__SCREAMING_SNAKE_CASE								=      [self.cls_token_id]
  													if token_ids_a is None:
  																				return len(cls + token_ids_a + sep	) * [0]
  													return len(cls + token_ids_a + sep	) * [0] + len(token_ids_a + sep	) * [1]
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A = 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(_A	):
  																				logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""	)
  																				return
  													__SCREAMING_SNAKE_CASE								=      os.path.join(
  													    _A   ,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']	)
  
  													if os.path.abspath(self.vocab_file	) != os.path.abspath(_A	):
  																				copyfile(self.vocab_file   ,							_A	)
  
  													return (out_vocab_file,)
  
  
  
  
  
  
  
style_context: 
  
  
  
  from __future__ import annotations
  
  class      UpperCAmelCase_						:
  
  						'''simple docstring'''
  
  
  
  
  						def __init__(					self   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      value
  													__SCREAMING_SNAKE_CASE								=      None
  													__SCREAMING_SNAKE_CASE								=      None
  
  
  
  
  
  
  
  class      UpperCAmelCase_						:
  
  						'''simple docstring'''
  
  
  
  
  						UpperCamelCase__    :				int
  
  
  
  
  
  
  						def __init__(					self	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													__SCREAMING_SNAKE_CASE								=      0
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if node is None:
  																				return
  
  													if path_sum == self.target:
  																				self.paths += 1
  
  													if node.left:
  																				self.depth_first_search(node.left   ,							path_sum + node.left.value	)
  													if node.right:
  																				self.depth_first_search(node.right   ,							path_sum + node.right.value	)
  
  
  
  
  
  
  						def  _A			(					self   ,							_A   ,							_A = None	):
  
  
  
  
  
  
  
  													'''simple docstring'''
  
  													if node is None:
  																				return 0
  													if target is not None:
  																				__SCREAMING_SNAKE_CASE								=      target
  
  													self.depth_first_search(_A   ,							node.value	)
  													self.path_sum(node.left	)
  													self.path_sum(node.right	)
  
  													return self.paths
  
  
  if __name__ == "__main__":
  			import doctest
  
  			doctest.testmod()
  
  
  
  
  
  
  