



import random



class       _lowercase				:





	"""simple docstring"""




	def __init__(self						,			lowerCamelCase_						,			lowerCamelCase_						):
						"""simple docstring"""

						a   	=  x
						a   	=  y




	def 	UpperCamelCase_			(self						):
						"""simple docstring"""

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




	@classmethod
	def 	UpperCamelCase_			(cls						):
						"""simple docstring"""

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






def        a( A			:       int			)						->			float:
					"""simple docstring"""





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

					a   	=  0
					for _ in range(A			):
										a   	=  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

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





from .pipeline_kandinskya_a import KandinskyVaaPipeline
from .pipeline_kandinsky2_2_controlnet import KandinskyVaaControlnetPipeline
from .pipeline_kandinsky2_2_controlnet_img2img import KandinskyVaaControlnetImgaImgPipeline
from .pipeline_kandinsky2_2_img2img import KandinskyVaaImgaImgPipeline
from .pipeline_kandinsky2_2_inpainting import KandinskyVaaInpaintPipeline
from .pipeline_kandinsky2_2_prior import KandinskyVaaPriorPipeline
from .pipeline_kandinsky2_2_prior_emb2emb import KandinskyVaaPriorEmbaEmbPipeline
