


"""simple docstring"""



def   __lowerCAmelCase						(						lowercase  :  int						,							lowercase  :  int )	->						int:


    """simple docstring"""





    return int((input_a, input_a).count(0 ) != 0 )







def   __lowerCAmelCase						(						)	->						None:


    """simple docstring"""





    assert nand_gate(0						,							0 ) == 1
    assert nand_gate(0						,							1 ) == 1
    assert nand_gate(1						,							0 ) == 1
    assert nand_gate(1						,							1 ) == 0


if __name__ == "__main__":
  print(nand_gate(0, 0))
  print(nand_gate(0, 1))
  print(nand_gate(1, 0))
  print(nand_gate(1, 1))









"""simple docstring"""



from typing import Dict

from .base import GenericTensor, Pipeline







class _lowerCAmelCase				(      snake_case_	):







   def  lowerCamelCase		(	self						,	UpperCamelCase__=None						,	UpperCamelCase__=None						,	UpperCamelCase__=None						,	**UpperCamelCase__						)	->		Union[str, Any]:

       '''simple docstring'''




       if tokenize_kwargs is None:
           snake_case    :      Optional[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    :      Union[str, Any]      					=    tokenize_kwargs

       snake_case    :      List[Any]      					=    {}
       if return_tensors is not None:
           snake_case    :      Tuple      					=    return_tensors

       return preprocess_params, {}, postprocess_params







   def  lowerCamelCase		(	self						,	UpperCamelCase__						,	**UpperCamelCase__						)	->		Dict[str, GenericTensor]:

       '''simple docstring'''




       snake_case    :      List[Any]      					=    self.framework
       snake_case    :      str      					=    self.tokenizer(UpperCamelCase__						,	return_tensors=UpperCamelCase__						,	**UpperCamelCase__						)
       return model_inputs







   def  lowerCamelCase		(	self						,	UpperCamelCase__						)	->		Tuple:

       '''simple docstring'''




       snake_case    :      int      					=    self.model(**UpperCamelCase__						)
       return model_outputs







   def  lowerCamelCase		(	self						,	UpperCamelCase__						,	UpperCamelCase__=False						)	->		Union[str, Any]:

       '''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						,	*UpperCamelCase__						,	**UpperCamelCase__						)	->		Union[str, Any]:

       '''simple docstring'''




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





