






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'''




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







						def __call__(   self   :		Any				,      __UpperCAmelCase   :		List[Any]=None				,      __UpperCAmelCase   :		List[Any]=None				,      __UpperCAmelCase   :		Tuple=None				,      __UpperCAmelCase   :		Optional[Any]=None				,      __UpperCAmelCase   :		Optional[int]=None				,      __UpperCAmelCase   :		List[Any] = True				,      __UpperCAmelCase   :		List[str] = False				,      __UpperCAmelCase   :		Tuple = None				,      __UpperCAmelCase   :		List[str] = None				,      __UpperCAmelCase   :		Optional[int] = 0				,      __UpperCAmelCase   :		Union[str, Any] = None				,      __UpperCAmelCase   :		Optional[int] = None				,      __UpperCAmelCase   :		Any = None				,      __UpperCAmelCase   :		str = False				,      __UpperCAmelCase   :		Optional[Any] = False				,      __UpperCAmelCase   :		Optional[int] = False				,      __UpperCAmelCase   :		Optional[int] = False				,      __UpperCAmelCase   :		int = True				,      __UpperCAmelCase   :		Tuple = None				,      **__UpperCAmelCase   :		Dict				,      )					->List[Any]:




							"""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(_lowerCAmelCase						)
								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(_lowerCAmelCase				,      _lowerCAmelCase						):
									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=_lowerCAmelCase				,      node_labels=_lowerCAmelCase				,      add_special_tokens=_lowerCAmelCase				,      padding=_lowerCAmelCase				,      truncation=_lowerCAmelCase				,      max_length=_lowerCAmelCase				,      stride=_lowerCAmelCase				,      pad_to_multiple_of=_lowerCAmelCase				,      return_token_type_ids=_lowerCAmelCase				,      return_attention_mask=_lowerCAmelCase				,      return_overflowing_tokens=_lowerCAmelCase				,      return_special_tokens_mask=_lowerCAmelCase				,      return_offsets_mapping=_lowerCAmelCase				,      return_length=_lowerCAmelCase				,      verbose=_lowerCAmelCase				,      return_tensors=_lowerCAmelCase				,      **_lowerCAmelCase				,      )

							return encoded_inputs







						def    __lowerCAmelCase      (   self   :		Optional[Any]				,      *__UpperCAmelCase   :		List[str]				,      **__UpperCAmelCase   :		List[Any]						)					->Union[str, Any]:




							"""simple docstring"""


							return self.tokenizer.batch_decode(*_lowerCAmelCase				,      **_lowerCAmelCase						)







						def    __lowerCAmelCase      (   self   :		Tuple				,      *__UpperCAmelCase   :		Dict				,      **__UpperCAmelCase   :		List[str]						)					->int:




							"""simple docstring"""


							return self.tokenizer.decode(*_lowerCAmelCase				,      **_lowerCAmelCase						)







						@property
						def    __lowerCAmelCase      (   self   :		int						)					->List[Any]:




							"""simple docstring"""


							a							=   self.tokenizer.model_input_names
							return tokenizer_input_names










def 		_a					(   a				:float				)							->    float:
 return -num if num < 0 else num
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_min() arg is an empty sequence'''				)
 a							=   x[0]
 for i in x:
  if abs_val(a				) < abs_val(a				):
   a							=   i
 return j
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_max() arg is an empty sequence'''				)
 a							=   x[0]
 for i in x:
  if abs(a				) > abs(a				):
   a							=   i
 return j
def 		_a					(   a				:list[int]				)							->    int:
 if len(a				) == 0:
  raise ValueError('''abs_max_sort() arg is an empty sequence'''				)
 return sorted(a			,							key=a				)[-1]
def 		_a					(   )							->    int:
 assert abs_val(0				) == 0
 assert abs_val(34				) == 34
 assert abs_val(-100_000_000_000				) == 100_000_000_000

 a							=   [-3, -1, 2, -11]
 assert abs_max(a				) == -11
 assert abs_max_sort(a				) == -11
 assert abs_min(a				) == -1


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     test_abs_val()
     print(abs_val(-34))  # --> 34


