
import random


class 		__magic_name__   :





		def __init__(							self    :	Optional[Any]						,  lowerCamelCase__    :	float						,  lowerCamelCase__    :	float				):
				lowerCAmelCase		:					List[str]  	=     x
				lowerCAmelCase		:					Union[str, Any]  	=     y





		def       _A							(							self    :	List[Any]				):
				return (self.x**2 + self.y**2) <= 1





		@classmethod
		def       _A							(							cls    :	int				):
				return cls(x=random.random()						,  y=random.random()				)



def     UpperCAmelCase__							(       __magic_name__						:     Union[str, Any]  ):


		'''simple docstring'''

		if number_of_simulations < 1:
				raise ValueError('''At least one simulation is necessary to estimate PI.'''  )

		lowerCAmelCase		:					Optional[Any]  	=     0
		for _ in range(_UpperCAmelCase  ):
				lowerCAmelCase		:					Dict  	=     Point.random_unit_square()

				if random_point.is_in_unit_circle():
						number_in_unit_circle += 1

		return 4 * number_in_unit_circle / number_of_simulations


if __name__ == "__main__":
		# import doctest

		# doctest.testmod()
		from math import pi

		__SCREAMING_SNAKE_CASE			:   List[str]         =     '''Please enter the desired number of Monte Carlo simulations: '''
		__SCREAMING_SNAKE_CASE			:   List[Any]         =     estimate_pi(int(input(prompt).strip()))
		print(f"""An estimate of PI is {my_pi} with an error of {abs(my_pi - pi)}""")


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__SCREAMING_SNAKE_CASE			:   str         =     {
    'configuration_deta': ['DETA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DetaConfig'],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE			:   Optional[int]         =     ['DetaImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__SCREAMING_SNAKE_CASE			:   str         =     [
		    'DETA_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'DetaForObjectDetection',
		    'DetaModel',
		    'DetaPreTrainedModel',
		]


if TYPE_CHECKING:
		from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_deta import DetaImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_deta import (
				    DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
				    DetaForObjectDetection,
				    DetaModel,
				    DetaPreTrainedModel,
				)

else:
		import sys

		__SCREAMING_SNAKE_CASE			:   Dict         =     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
