



from math import factorial, pi



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_ = 30  ):

			if not isinstance(SCREAMING_SNAKE_CASE_						,  (int, float)  ):
						raise ValueError("maclaurin_sin() requires either an int or float for theta"  )

			if not isinstance(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ) or accuracy <= 0:
						raise ValueError("maclaurin_sin() requires a positive int for accuracy"  )

			lowercase__					  =				float(SCREAMING_SNAKE_CASE_  )
			lowercase__					  =				theta // (2 * pi)
			theta -= 2 * div * pi
			return sum(
			    (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1  ) for r in range(SCREAMING_SNAKE_CASE_  )  )



def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_ = 30  ):

			if not isinstance(SCREAMING_SNAKE_CASE_						,  (int, float)  ):
						raise ValueError("maclaurin_cos() requires either an int or float for theta"  )

			if not isinstance(SCREAMING_SNAKE_CASE_						,  SCREAMING_SNAKE_CASE_  ) or accuracy <= 0:
						raise ValueError("maclaurin_cos() requires a positive int for accuracy"  )

			lowercase__					  =				float(SCREAMING_SNAKE_CASE_  )
			lowercase__					  =				theta // (2 * pi)
			theta -= 2 * div * pi
			return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r  ) for r in range(SCREAMING_SNAKE_CASE_  )  )


if __name__ == "__main__":
							import doctest

							doctest.testmod()

							print(maclaurin_sin(10))
							print(maclaurin_sin(-10))
							print(maclaurin_sin(10, 15))
							print(maclaurin_sin(-10, 15))

							print(maclaurin_cos(5))
							print(maclaurin_cos(-5))
							print(maclaurin_cos(10, 15))
							print(maclaurin_cos(-10, 15))









from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments



def __lowerCAmelCase (     ):
			lowercase__					  =				HfArgumentParser(SCREAMING_SNAKE_CASE_  )
			lowercase__					  =				parser.parse_args_into_dataclasses()[0]
			lowercase__					  =				TensorFlowBenchmark(args=SCREAMING_SNAKE_CASE_  )
			try:
						lowercase__					  =				parser.parse_args_into_dataclasses()[0]
			except ValueError as e:
						lowercase__					  =				"Arg --no_{0} is no longer used, please use --no-{0} instead."
						lowercase__					  =				" ".join(str(SCREAMING_SNAKE_CASE_  ).split(" "  )[:-1]  )
						lowercase__					  =				""
						lowercase__					  =				eval(str(SCREAMING_SNAKE_CASE_  ).split(" "  )[-1]  )
						lowercase__					  =				[]
						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(SCREAMING_SNAKE_CASE_  )
						if len(SCREAMING_SNAKE_CASE_  ) > 0:
									lowercase__					  =				full_error_msg + begin_error_msg + str(SCREAMING_SNAKE_CASE_  )
						raise ValueError(SCREAMING_SNAKE_CASE_  )
			benchmark.run()


if __name__ == "__main__":
							main()




