



import random

class 						lowerCamelCase_     :






						'''simple docstring'''







						def __init__(						self   :      Optional[Any]						,						__lowerCamelCase   :      float						,						__lowerCamelCase   :      float			)   ->					None:
									A				:       Optional[int]														=    x
									A				:       List[Any]														=    y







						def       SCREAMING_SNAKE_CASE__		(						self   :      Dict			)   ->					bool:
									return (self.x**2 + self.y**2) <= 1







						@classmethod
						def       SCREAMING_SNAKE_CASE__		(						cls   :      Tuple			)   ->					Union[str, Any]:
									return cls(x=random.random()						,						y=random.random()			)







def 						UpperCAmelCase (    _lowerCamelCase     ):
			if number_of_simulations < 1:
						raise ValueError("At least one simulation is necessary to estimate PI."     )

			A				:       List[str]														=    0
			for _ in range(_lowerCamelCase     ):
						A				:       str														=    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     =	"""Please enter the desired number of Monte Carlo simulations: """
							__SCREAMING_SNAKE_CASE     =	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_tokenizers_available, is_torch_available


__SCREAMING_SNAKE_CASE     =	{"""configuration_yoso""": ["""YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YosoConfig"""]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__SCREAMING_SNAKE_CASE     =	[
							    """YOSO_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """YosoForMaskedLM""",
							    """YosoForMultipleChoice""",
							    """YosoForQuestionAnswering""",
							    """YosoForSequenceClassification""",
							    """YosoForTokenClassification""",
							    """YosoLayer""",
							    """YosoModel""",
							    """YosoPreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_yoso import (
														    YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
														    YosoForMaskedLM,
														    YosoForMultipleChoice,
														    YosoForQuestionAnswering,
														    YosoForSequenceClassification,
														    YosoForTokenClassification,
														    YosoLayer,
														    YosoModel,
														    YosoPreTrainedModel,
														)


else:
							import sys

							__SCREAMING_SNAKE_CASE     =	_LazyModule(__name__, globals()["""__file__"""], _import_structure)