
def      __UpperCAmelCase    (  snake_case_							:		int				):



	'''simple docstring'''



	UpperCAmelCase:					Dict 						=     1
	UpperCAmelCase:					int 						=     0
	UpperCAmelCase:					Optional[int] 						=     1
	UpperCAmelCase:					str 						=     1
	UpperCAmelCase:					int 						=     3
	UpperCAmelCase:					Dict 						=     3
	UpperCAmelCase:					List[Any] 						=     limit
	UpperCAmelCase:					Dict 						=     0

	UpperCAmelCase:					Optional[Any] 						=     ""
	while counter != decimal + 1:
		if 4 * q + r - t < n * t:
			result += str(snake_case_				)
			if counter == 0:
				result += "."

			if decimal == counter:
				break

			counter += 1
			UpperCAmelCase:					Any 						=     1_0 * (r - n * t)
			UpperCAmelCase:					Tuple 						=     ((1_0 * (3 * q + r)) // t) - 1_0 * n
			q *= 1_0
			UpperCAmelCase:					List[str] 						=     nr
		else:
			UpperCAmelCase:					Dict 						=     (2 * q + r) * l
			UpperCAmelCase:					Optional[int] 						=     (q * (7 * k) + 2 + (r * l)) // (t * l)
			q *= k
			t *= l
			l += 2
			k += 1
			UpperCAmelCase:					int 						=     nn
			UpperCAmelCase:					Union[str, Any] 						=     nr
	return result



def      __UpperCAmelCase    (  ):



	'''simple docstring'''



	print(F'{calculate_pi(5_0				) = }'				)
	import doctest

	doctest.testmod()


if __name__ == "__main__":
	main()


import torch
from torch import autograd





class 		__lowerCamelCase     (   autograd.Function		):



							@staticmethod
							def     A__ (     __snake_case	,				__snake_case	,				__snake_case	,				__snake_case							)						->     Dict:






								"""simple docstring"""



								UpperCAmelCase:					Optional[Any] 						=     inputs.numel()
								UpperCAmelCase:					Tuple 						=     int(0.0_05 * nb_elems							) + 1
								if sigmoid:
									UpperCAmelCase:					int 						=     (torch.sigmoid(__snake_case							) > threshold).type(inputs.type()							)
								else:
									UpperCAmelCase:					List[Any] 						=     (inputs > threshold).type(inputs.type()							)
								if mask.sum() < nb_min:
									# We limit the pruning so that at least 0.5% (half a percent) of the weights are remaining
									UpperCAmelCase:					List[Any] 						=     inputs.flatten().kthvalue(max(nb_elems - nb_min	,				1							)							).values
									UpperCAmelCase:					Optional[int] 						=     (inputs > k_threshold).type(inputs.type()							)
								return mask




							@staticmethod
							def     A__ (     __snake_case	,				__snake_case							)						->     Any:






								"""simple docstring"""



								return gradOutput, None, None





class 		__lowerCamelCase     (   autograd.Function		):



							@staticmethod
							def     A__ (     __snake_case	,				__snake_case	,				__snake_case							)						->     Any:






								"""simple docstring"""



								UpperCAmelCase:					Tuple 						=     inputs.clone()
								UpperCAmelCase						,   UpperCAmelCase:					List[Any] 						=     inputs.flatten().sort(descending=__snake_case							)
								UpperCAmelCase:					Optional[Any] 						=     int(threshold * inputs.numel()							)

								# flat_out and mask access the same memory.
								UpperCAmelCase:					Optional[int] 						=     mask.flatten()
								UpperCAmelCase:					Union[str, Any] 						=     0
								UpperCAmelCase:					int 						=     1
								return mask




							@staticmethod
							def     A__ (     __snake_case	,				__snake_case							)						->     Optional[Any]:






								"""simple docstring"""



								return gradOutput, None





class 		__lowerCamelCase     (   lowercase		):



							@staticmethod
							def     A__ (     __snake_case	,				__snake_case							)						->     str:






								"""simple docstring"""



								UpperCAmelCase:					Union[str, Any] 						=     inputs.clone()
								UpperCAmelCase						,   UpperCAmelCase:					Any 						=     inputs.abs().flatten().sort(descending=__snake_case							)
								UpperCAmelCase:					str 						=     int(threshold * inputs.numel()							)

								# flat_out and mask access the same memory.
								UpperCAmelCase:					Optional[int] 						=     mask.flatten()
								UpperCAmelCase:					Union[str, Any] 						=     0
								UpperCAmelCase:					List[str] 						=     1
								return mask
