
"""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 	_lowercase    (							lowerCAmelCase_					):


     '''simple docstring'''





     _A		    =				'MarkupLMFeatureExtractor'
     _A		    =				('MarkupLMTokenizer', 'MarkupLMTokenizerFast')
     _A		    =				True



     def __call__(   self			,      __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase = True			,      __UpperCamelCase = False			,      __UpperCamelCase = None			,      __UpperCamelCase = None			,      __UpperCamelCase = 0			,      __UpperCamelCase = None			,      __UpperCamelCase = None			,      __UpperCamelCase = None			,      __UpperCamelCase = False			,      __UpperCamelCase = False			,      __UpperCamelCase = False			,      __UpperCamelCase = False			,      __UpperCamelCase = True			,      __UpperCamelCase = None			,      **__UpperCamelCase			,      )->       BatchEncoding:
          # first, create nodes and xpaths
          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`"	)

               UpperCAmelCase__				:			int							=    self.feature_extractor(__UpperCamelCase	)
               UpperCAmelCase__				:			Tuple							=    features["nodes"]
               UpperCAmelCase__				:			Tuple							=    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(__UpperCamelCase			,      __UpperCamelCase	):
                    UpperCAmelCase__				:			str							=    [questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

          UpperCAmelCase__				:			Any							=    self.tokenizer(
              text=questions if questions is not None else nodes			,      text_pair=nodes if questions is not None else None			,      xpaths=__UpperCamelCase			,      node_labels=__UpperCamelCase			,      add_special_tokens=__UpperCamelCase			,      padding=__UpperCamelCase			,      truncation=__UpperCamelCase			,      max_length=__UpperCamelCase			,      stride=__UpperCamelCase			,      pad_to_multiple_of=__UpperCamelCase			,      return_token_type_ids=__UpperCamelCase			,      return_attention_mask=__UpperCamelCase			,      return_overflowing_tokens=__UpperCamelCase			,      return_special_tokens_mask=__UpperCamelCase			,      return_offsets_mapping=__UpperCamelCase			,      return_length=__UpperCamelCase			,      verbose=__UpperCamelCase			,      return_tensors=__UpperCamelCase			,      **__UpperCamelCase			,      )

          return encoded_inputs



     def 			lowerCAmelCase__							(   self			,      *__UpperCamelCase			,      **__UpperCamelCase	)->       Optional[Any]:
          return self.tokenizer.batch_decode(*__UpperCamelCase			,      **__UpperCamelCase	)



     def 			lowerCAmelCase__							(   self			,      *__UpperCamelCase			,      **__UpperCamelCase	)->       Optional[Any]:
          return self.tokenizer.decode(*__UpperCamelCase			,      **__UpperCamelCase	)



     @property
     def 			lowerCAmelCase__							(   self	)->       Dict:
          UpperCAmelCase__				:			int							=    self.tokenizer.model_input_names
          return tokenizer_input_names





"""simple docstring"""




def 				a__			(					lowerCAmelCase						:							str		):






     '''simple docstring'''
     UpperCAmelCase__				:			Optional[Any]							=    str(lowerCAmelCase		).strip()
     if not oct_string:
          raise ValueError("Empty string was passed to the function"		)
     UpperCAmelCase__				:			Tuple							=    oct_string[0] == "-"
     if is_negative:
          UpperCAmelCase__				:			List[Any]							=    oct_string[1:]
     if not oct_string.isdigit() or not all(0 <= int(lowerCAmelCase		) <= 7 for char in oct_string		):
          raise ValueError("Non-octal value was passed to the function"		)
     UpperCAmelCase__				:			Optional[int]							=    0
     for char in oct_string:
          UpperCAmelCase__				:			Tuple							=    8 * decimal_number + int(lowerCAmelCase		)
     if is_negative:
          UpperCAmelCase__				:			int							=    -decimal_number
     return decimal_number


if __name__ == "__main__":
    from doctest import testmod

    testmod()



