
'''simple docstring'''

from typing import TYPE_CHECKING

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


UpperCamelCase_     			= {
    """configuration_deformable_detr""": ["""DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DeformableDetrConfig"""],
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase_     			= ["""DeformableDetrFeatureExtractor"""]
     UpperCamelCase_     			= ["""DeformableDetrImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     UpperCamelCase_     			= [
         """DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """DeformableDetrForObjectDetection""",
         """DeformableDetrModel""",
         """DeformableDetrPreTrainedModel""",
     ]


if TYPE_CHECKING:
     from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
          from .image_processing_deformable_detr import DeformableDetrImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_deformable_detr import (
              DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DeformableDetrForObjectDetection,
              DeformableDetrModel,
              DeformableDetrPreTrainedModel,
          )

else:
     import sys

     UpperCamelCase_     			= _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




'''simple docstring'''

import random


class   a_  :




       def __init__(     self   ,   snake_case_   ,   snake_case_  ):
         _lowerCAmelCase       :  List[str]   				=					x
         _lowerCAmelCase       :  List[str]   				=					y




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







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



def 	_UpperCAmelCase				(  _lowerCamelCase						:       int		)    ->						float:
  if number_of_simulations < 1:
    raise ValueError("""At least one simulation is necessary to estimate PI."""		)

  _lowerCAmelCase       :  Tuple   				=					0
  for _ in range(_lowerCamelCase		):
    _lowerCAmelCase       :  Union[str, Any]   				=					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

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


