



"""simple docstring"""







from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments



def      __UpperCAmelCase      (    )							->      str:
		lowercase__   :    Tuple				=			HfArgumentParser(__lowerCamelCase	)
		lowercase__   :    Optional[Any]				=			parser.parse_args_into_dataclasses()[0]
		lowercase__   :    int				=			TensorFlowBenchmark(args=__lowerCamelCase	)
		try:
				lowercase__   :    Optional[int]				=			parser.parse_args_into_dataclasses()[0]
		except ValueError as e:
				lowercase__   :    Optional[Any]				=			'''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
				lowercase__   :    List[str]				=			''' '''.join(str(__lowerCamelCase	).split(''' '''	)[:-1]	)
				lowercase__   :    Tuple				=			''''''
				lowercase__   :    List[Any]				=			eval(str(__lowerCamelCase	).split(''' '''	)[-1]	)
				lowercase__   :    Any				=			[]
				for arg in depreciated_args:
						# arg[2:] removes '--'
						if arg[2:] in TensorFlowBenchmark.deprecated_args:
								# arg[5:] removes '--no_'
								full_error_msg += arg_error_msg.format(arg[5:]	)
						else:
								wrong_args.append(__lowerCamelCase	)
				if len(__lowerCamelCase	) > 0:
						lowercase__   :    Optional[int]				=			full_error_msg + begin_error_msg + str(__lowerCamelCase	)
				raise ValueError(__lowerCamelCase	)
		benchmark.run()


if __name__ == "__main__":
							main()




'''simple docstring'''
def 					a__       (					lowerCAmelCase__						)    ->	int:
    if a < 0:
        raise ValueError('''Input value must be a positive integer'''						)
    elif isinstance(lowerCAmelCase__  ,					lowerCAmelCase__						):
        raise TypeError('''Input value must be a \'int\' type'''						)
    return bin(lowerCAmelCase__						).count('''1'''						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
