from ...configuration_utils import PretrainedConfig
from ...utils import logging


a     :			Tuple					    =						logging.get_logger(__name__)

a     :			str					    =						{
    """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json""",
}

class 				_lowercase						(    a__ ):






    '''simple docstring'''
    SCREAMING_SNAKE_CASE:							str        =						'mpnet'




    def __init__(						self					,	lowerCamelCase__=30_527					,	lowerCamelCase__=768					,	lowerCamelCase__=12					,	lowerCamelCase__=12					,	lowerCamelCase__=3_072					,	lowerCamelCase__="gelu"					,	lowerCamelCase__=0.1					,	lowerCamelCase__=0.1					,	lowerCamelCase__=512					,	lowerCamelCase__=0.0_2					,	lowerCamelCase__=1E-12					,	lowerCamelCase__=32					,	lowerCamelCase__=1					,	lowerCamelCase__=0					,	lowerCamelCase__=2					,	**lowerCamelCase__					,	):
       super().__init__(pad_token_id=__A					,	bos_token_id=__A					,	eos_token_id=__A					,	**__A   )

       lowerCAmelCase_:       Tuple         =  vocab_size
       lowerCAmelCase_:       List[Any]         =  hidden_size
       lowerCAmelCase_:       Optional[int]         =  num_hidden_layers
       lowerCAmelCase_:       List[Any]         =  num_attention_heads
       lowerCAmelCase_:       int         =  hidden_act
       lowerCAmelCase_:       str         =  intermediate_size
       lowerCAmelCase_:       Optional[int]         =  hidden_dropout_prob
       lowerCAmelCase_:       Union[str, Any]         =  attention_probs_dropout_prob
       lowerCAmelCase_:       int         =  max_position_embeddings
       lowerCAmelCase_:       str         =  initializer_range
       lowerCAmelCase_:       List[str]         =  layer_norm_eps
       lowerCAmelCase_:       List[str]         =  relative_attention_num_buckets
import random

class 				_lowercase						:






    '''simple docstring'''




    def __init__(						self					,	lowerCamelCase__					,	lowerCamelCase__   ):
       lowerCAmelCase_:       int         =  x
       lowerCAmelCase_:       List[str]         =  y




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




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





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

   lowerCAmelCase_:       List[Any]         =  0
   for _ in range(lowercase				):
      lowerCAmelCase_:       Tuple         =  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     :			Union[str, Any]					    =						"""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)}''')