






import os

from ...utils import logging
from .utils import DataProcessor, InputExample


A_			:Optional[int]	    =		logging.get_logger(__name__)




class 							__A	(     a					):





				"""simple docstring"""







				def __init__(					self				,    lowerCamelCase__				,    lowerCamelCase__=None       ):




									"""simple docstring"""

									__UpperCamelCase :   int									=language
									__UpperCamelCase :   Tuple									=train_language


				def  __lowercase				(					self				,    lowerCamelCase__       ):




									"""simple docstring"""

									__UpperCamelCase :   Dict									=self.language if self.train_language is None else self.train_language
									__UpperCamelCase :   Optional[int]									=self._read_tsv(os.path.join(lowerCamelCase__				,    f'XNLI-MT-1.0/multinli/multinli.train.{lg}.tsv'       )       )
									__UpperCamelCase :   Optional[Any]									=[]
									for i, line in enumerate(lowerCamelCase__       ):
														if i == 0:
																			continue
														__UpperCamelCase :   List[str]									=f'train-{i}'
														__UpperCamelCase :   List[Any]									=line[0]
														__UpperCamelCase :   List[Any]									=line[1]
														__UpperCamelCase :   Dict									='contradiction' if line[2] == 'contradictory' else line[2]
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training input {text_a} is not a string'       )
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training input {text_b} is not a string'       )
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training label {label} is not a string'       )
														examples.append(InputExample(guid=lowerCamelCase__				,    text_a=lowerCamelCase__				,    text_b=lowerCamelCase__				,    label=lowerCamelCase__       )       )
									return examples


				def  __lowercase				(					self				,    lowerCamelCase__       ):




									"""simple docstring"""

									__UpperCamelCase :   Union[str, Any]									=self._read_tsv(os.path.join(lowerCamelCase__				,    'XNLI-1.0/xnli.test.tsv'       )       )
									__UpperCamelCase :   List[Any]									=[]
									for i, line in enumerate(lowerCamelCase__       ):
														if i == 0:
																			continue
														__UpperCamelCase :   Optional[Any]									=line[0]
														if language != self.language:
																			continue
														__UpperCamelCase :   str									=f'test-{i}'
														__UpperCamelCase :   int									=line[6]
														__UpperCamelCase :   Union[str, Any]									=line[7]
														__UpperCamelCase :   Union[str, Any]									=line[1]
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training input {text_a} is not a string'       )
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training input {text_b} is not a string'       )
														if not isinstance(lowerCamelCase__				,    lowerCamelCase__       ):
																			raise ValueError(f'Training label {label} is not a string'       )
														examples.append(InputExample(guid=lowerCamelCase__				,    text_a=lowerCamelCase__				,    text_b=lowerCamelCase__				,    label=lowerCamelCase__       )       )
									return examples







				def  __lowercase				(					self       ):




									"""simple docstring"""

									return ["contradiction", "entailment", "neutral"]
A_			:Tuple	    =		{
    '''xnli''': XnliProcessor,
}

A_			:Any	    =		{
    '''xnli''': '''classification''',
}

A_			:Tuple	    =		{
    '''xnli''': 3,
}









import random




class 							__A	:





				"""simple docstring"""







				def __init__(					self				,    lowerCamelCase__				,    lowerCamelCase__       ):




									"""simple docstring"""

									__UpperCamelCase :   Optional[Any]									=x
									__UpperCamelCase :   int									=y


				def  __lowercase				(					self       ):




									"""simple docstring"""

									return (self.x**2 + self.y**2) <= 1







				@classmethod
				def  __lowercase				(					cls       ):




									"""simple docstring"""

									return cls(x=random.random()				,    y=random.random()       )






def 				A	(			a_   )	->		float:
					if number_of_simulations < 1:
										raise ValueError('At least one simulation is necessary to estimate PI.'   )

					__UpperCamelCase :   List[str]									=0
					for _ in range(a_   ):
										__UpperCamelCase :   Optional[int]									=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

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

