"""simple docstring"""







import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


SCREAMING_SNAKE_CASE									=						logging.get_logger(__name__)



class  _lowerCamelCase			(__lowerCamelCase     ):







				def __init__( self    :       Optional[int]			,					*lowerCamelCase_    :       Dict			,					**lowerCamelCase_    :       Tuple						):

					"""simple docstring"""






					warnings.warn(
					    'The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
					    ' use DPTImageProcessor instead.'			,					lowerCamelCase_			,					)
					super().__init__(*lowerCamelCase_			,					**lowerCamelCase_						)




"""simple docstring"""







from decimal import Decimal, getcontext
from math import ceil, factorial


def      __lowerCAmelCase(		__UpperCAmelCase			):






	"""simple docstring"""





	if not isinstance(__UpperCAmelCase     ,__UpperCAmelCase			):
		raise TypeError('Undefined for non-integers'			)
	elif precision < 1:
		raise ValueError('Undefined for non-natural numbers'			)

	_lowercase :    Optional[Any]							=							precision
	_lowercase :    Dict							=							ceil(precision / 14			)
	_lowercase :    int							=							426_880 * Decimal(10_005			).sqrt()
	_lowercase :    Optional[Any]							=							1
	_lowercase :    Union[str, Any]							=							13_591_409
	_lowercase :    Optional[int]							=							Decimal(__UpperCAmelCase			)
	for k in range(1     ,__UpperCAmelCase			):
		_lowercase :    List[str]							=							factorial(6 * k			) // (factorial(3 * k			) * factorial(__UpperCAmelCase			) ** 3)
		linear_term += 545_140_134
		exponential_term *= -262_537_412_640_768_000
		partial_sum += Decimal(multinomial_term * linear_term			) / exponential_term
	return str(constant_term / partial_sum			)[:-1]


if __name__ == "__main__":
						SCREAMING_SNAKE_CASE									=						50
						print(f"""The first {n} digits of pi is: {pi(n)}""")



