




"""simple docstring"""


from typing import Dict

from .base import GenericTensor, Pipeline






class       lowercase(  __a				):







 '''simple docstring'''





 def 				UpperCamelCase_     (       self:	int,   a_:	Any=None,   a_:	Optional[int]=None,   a_:	Dict=None,   **a_:	Dict	):




   '''simple docstring'''



   if tokenize_kwargs is None:
     _snake_case							:	Union[str, Any]			=						{}

   if truncation is not None:
     if "truncation" in tokenize_kwargs:
       raise ValueError(
           """truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)"""	)
     _snake_case							:	List[str]			=						truncation

   _snake_case							:	Dict			=						tokenize_kwargs

   _snake_case							:	Any			=						{}
   if return_tensors is not None:
     _snake_case							:	Any			=						return_tensors

   return preprocess_params, {}, postprocess_params


 def 				UpperCamelCase_     (       self:	Dict,   a_:	Any,   **a_:	Optional[Any]	):




   '''simple docstring'''



   _snake_case							:	Tuple			=						self.framework
   _snake_case							:	Optional[Any]			=						self.tokenizer(a_,   return_tensors=a_,   **a_	)
   return model_inputs


 def 				UpperCamelCase_     (       self:	Optional[int],   a_:	str	):




   '''simple docstring'''



   _snake_case							:	Optional[Any]			=						self.model(**a_	)
   return model_outputs


 def 				UpperCamelCase_     (       self:	List[Any],   a_:	Optional[int],   a_:	str=False	):




   '''simple docstring'''



   if return_tensors:
     return model_outputs[0]
   if self.framework == "pt":
     return model_outputs[0].tolist()
   elif self.framework == "tf":
     return model_outputs[0].numpy().tolist()


 def __call__(       self:	Tuple,   *a_:	Union[str, Any],   **a_:	Any	):




   '''simple docstring'''



   return super().__call__(*a_,   **a_	)








"""simple docstring"""


def       UpperCAmelCase__ (snake_case__							:      int					):
  """simple docstring"""

  if not isinstance(snake_case__	,     snake_case__					) or number < 0:
    raise ValueError("""Input must be a non-negative integer"""					)

  _snake_case							:	Dict			=						0
  while number:
    # This way we arrive at next set bit (next 1) instead of looping
    # through each bit and checking for 1s hence the
    # loop won't run 32 times it will only run the number of `1` times
    number &= number - 1
    count += 1
  return count


if __name__ == "__main__":
     import doctest

     doctest.testmod()


