code: 
  
  
  
  
  """simple docstring"""
  
  
  
  from transformers import ProcessorMixin
  
  
  
  
  class 			UpperCAmelCase_						(		A_							):
  				lowercase__		      =   '''AutoFeatureExtractor'''
  				lowercase__		      =   '''AutoTokenizer'''
  
  
  
  
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  
  
  from typing import Optional, Union
  
  from ...file_utils import TensorType
  from ...processing_utils import ProcessorMixin
  from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy
  
  
  
  
  class 			UpperCAmelCase_						(		A_							):
      lowercase__		      =   '''MarkupLMFeatureExtractor'''
      lowercase__		      =   ('''MarkupLMTokenizer''', '''MarkupLMTokenizerFast''')
      lowercase__		      =   True
  
  
  
  
      def __call__(					self		: Dict			,				snake_case_		: Optional[int]=None			,				snake_case_		: Union[str, Any]=None			,				snake_case_		: Tuple=None			,				snake_case_		: str=None			,				snake_case_		: Optional[Any]=None			,				snake_case_		: bool = True			,				snake_case_		: Union[bool, str, PaddingStrategy] = False			,				snake_case_		: Union[bool, str, TruncationStrategy] = None			,				snake_case_		: Optional[int] = None			,				snake_case_		: int = 0			,				snake_case_		: Optional[int] = None			,				snake_case_		: Optional[bool] = None			,				snake_case_		: Optional[bool] = None			,				snake_case_		: bool = False			,				snake_case_		: bool = False			,				snake_case_		: bool = False			,				snake_case_		: bool = False			,				snake_case_		: bool = True			,				snake_case_		: Optional[Union[str, TensorType]] = None			,				**snake_case_		: Dict			,				)   ->							BatchEncoding:
  
  
  
  
       '''simple docstring'''
  
       if self.parse_html:
        if html_strings is None:
         raise ValueError("Make sure to pass HTML strings in case `parse_html` is set to `True`"   )
  
        if nodes is not None or xpaths is not None or node_labels is not None:
         raise ValueError(
             "Please don't pass nodes, xpaths nor node labels in case `parse_html` is set to `True`"   )
  
        A__ =       self.feature_extractor(snake_case_   )
        A__ =       features["nodes"]
        A__ =       features["xpaths"]
       else:
        if html_strings is not None:
         raise ValueError("You have passed HTML strings but `parse_html` is set to `False`."   )
        if nodes is None or xpaths is None:
         raise ValueError("Make sure to pass nodes and xpaths in case `parse_html` is set to `False`"   )
  
          # # second, apply the tokenizer
       if questions is not None and self.parse_html:
        if isinstance(snake_case_			,				snake_case_   ):
         A__ =       [questions]  # add batch dimension (as the feature extractor always adds a batch dimension)
  
       A__ =       self.tokenizer(
           text=questions if questions is not None else nodes			,				text_pair=nodes if questions is not None else None			,				xpaths=snake_case_			,				node_labels=snake_case_			,				add_special_tokens=snake_case_			,				padding=snake_case_			,				truncation=snake_case_			,				max_length=snake_case_			,				stride=snake_case_			,				pad_to_multiple_of=snake_case_			,				return_token_type_ids=snake_case_			,				return_attention_mask=snake_case_			,				return_overflowing_tokens=snake_case_			,				return_special_tokens_mask=snake_case_			,				return_offsets_mapping=snake_case_			,				return_length=snake_case_			,				verbose=snake_case_			,				return_tensors=snake_case_			,				**snake_case_			,				)
  
       return encoded_inputs
  
  
  
  
      def 							__magic_name__							(					self		: Optional[Any]			,				*snake_case_		: Any			,				**snake_case_		: Any   )   ->							int:
  
  
  
  
       '''simple docstring'''
  
       return self.tokenizer.batch_decode(*snake_case_			,				**snake_case_   )
  
  
  
  
      def 							__magic_name__							(					self		: Tuple			,				*snake_case_		: Optional[Any]			,				**snake_case_		: List[Any]   )   ->							Any:
  
  
  
  
       '''simple docstring'''
  
       return self.tokenizer.decode(*snake_case_			,				**snake_case_   )
  
  
  
  
      @property
      def 							__magic_name__							(					self		: List[Any]   )   ->							Optional[int]:
  
  
  
  
       '''simple docstring'''
  
       A__ =       self.tokenizer.model_input_names
       return tokenizer_input_names
  
  
  
  
  
  