code: 
  '''simple docstring'''
  
  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:
       UpperCamelCase_     			=       None
  
  UpperCamelCase_     			=       logging.get_logger(__name__)
  
  UpperCamelCase_     			=       {"""vocab_file""": """spm.model""", """tokenizer_file""": """tokenizer.json"""}
  
  UpperCamelCase_     			=       {
      """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"""
          ),
      }
  }
  
  UpperCamelCase_     			=       {
      """microsoft/deberta-v2-xlarge""": 5_12,
      """microsoft/deberta-v2-xxlarge""": 5_12,
      """microsoft/deberta-v2-xlarge-mnli""": 5_12,
      """microsoft/deberta-v2-xxlarge-mnli""": 5_12,
  }
  
  UpperCamelCase_     			=       {
      """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   a_  (_a    ):
         __lowerCAmelCase    :				Tuple    =      VOCAB_FILES_NAMES
         __lowerCAmelCase    :				Optional[Any]    =      PRETRAINED_VOCAB_FILES_MAP
         __lowerCAmelCase    :				Any    =      PRETRAINED_INIT_CONFIGURATION
         __lowerCAmelCase    :				int    =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
         __lowerCAmelCase    :				Union[str, Any]    =      DebertaVaTokenizer
  
  
  
  
         def __init__(     self   ,   snake_case_=None   ,   snake_case_=None   ,   snake_case_=False   ,   snake_case_=False   ,   snake_case_="[CLS]"   ,   snake_case_="[SEP]"   ,   snake_case_="[UNK]"   ,   snake_case_="[SEP]"   ,   snake_case_="[PAD]"   ,   snake_case_="[CLS]"   ,   snake_case_="[MASK]"   ,   **snake_case_   ,   ):
           super().__init__(
               snake_case_   ,   tokenizer_file=snake_case_   ,   do_lower_case=snake_case_   ,   bos_token=snake_case_   ,   eos_token=snake_case_   ,   unk_token=snake_case_   ,   sep_token=snake_case_   ,   pad_token=snake_case_   ,   cls_token=snake_case_   ,   mask_token=snake_case_   ,   split_by_punct=snake_case_   ,   **snake_case_   ,   )
  
           _lowerCAmelCase       :  str   				=					do_lower_case
           _lowerCAmelCase       :  str   				=					split_by_punct
           _lowerCAmelCase       :  Union[str, Any]   				=					vocab_file
           _lowerCAmelCase       :  Any   				=					False if not self.vocab_file else True
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_=None  ):
  
           if token_ids_a is None:
             return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           _lowerCAmelCase       :  int   				=					[self.cls_token_id]
           _lowerCAmelCase       :  int   				=					[self.sep_token_id]
           return cls + token_ids_a + sep + token_ids_a + sep
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_=None   ,   snake_case_=False  ):
  
           if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=snake_case_   ,   token_ids_a=snake_case_   ,   already_has_special_tokens=snake_case_  )
  
           if token_ids_a is not None:
             return [1] + ([0] * len(snake_case_  )) + [1] + ([0] * len(snake_case_  )) + [1]
           return [1] + ([0] * len(snake_case_  )) + [1]
  
  
  
  
         def 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_=None  ):
           _lowerCAmelCase       :  Optional[int]   				=					[self.sep_token_id]
           _lowerCAmelCase       :  Tuple   				=					[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 							__UpperCamelCase       (     self   ,   snake_case_   ,   snake_case_ = None  ):
           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(snake_case_  ):
             logger.error(f'Vocabulary path ({save_directory}) should be a directory'  )
             return
           _lowerCAmelCase       :  str   				=					os.path.join(
               snake_case_   ,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]  )
  
           if os.path.abspath(self.vocab_file  ) != os.path.abspath(snake_case_  ):
             copyfile(self.vocab_file   ,   snake_case_  )
  
           return (out_vocab_file,)
  
  
  
style_context: 
  '''simple docstring'''
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  UpperCamelCase_     			=       {
      """configuration_deformable_detr""": ["""DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DeformableDetrConfig"""],
  }
  
  try:
       if not is_vision_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       UpperCamelCase_     			=       ["""DeformableDetrFeatureExtractor"""]
       UpperCamelCase_     			=       ["""DeformableDetrImageProcessor"""]
  
  try:
       if not is_torch_available():
            raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
       pass
  else:
       UpperCamelCase_     			=       [
           """DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """DeformableDetrForObjectDetection""",
           """DeformableDetrModel""",
           """DeformableDetrPreTrainedModel""",
       ]
  
  
  if TYPE_CHECKING:
       from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig
  
       try:
            if not is_vision_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
            from .image_processing_deformable_detr import DeformableDetrImageProcessor
  
       try:
            if not is_torch_available():
                 raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
            pass
       else:
            from .modeling_deformable_detr import (
                DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
                DeformableDetrForObjectDetection,
                DeformableDetrModel,
                DeformableDetrPreTrainedModel,
            )
  
  else:
       import sys
  
       UpperCamelCase_     			=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
  
  
  