'''simple docstring'''


from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean

def   A_      (       SCREAMING_SNAKE_CASE_						)			->Optional[int]:

  # A local function to see if a dot lands in the circle.
  def is_in_circle(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						) -> bool:
    lowercase_     =       sqrt((x**2) + (y**2)						)
    # Our circle has a radius of 1, so a distance
    # greater than 1 would land outside the circle.
    return distance_from_centre <= 1

  # The proportion of guesses that landed in the circle
  lowercase_     =       mean(
      int(is_in_circle(uniform(-1.0 ,	1.0						) ,	uniform(-1.0 ,	1.0						)						)						)
      for _ in range(SCREAMING_SNAKE_CASE_						)						)
  # The ratio of the area for circle to square is pi/4.
  lowercase_     =       proportion * 4
  print(f"""The estimated value of pi is {pi_estimate}"""						)
  print(f"""The numpy value of pi is {pi}"""						)
  print(f"""The total error is {abs(pi - pi_estimate						)}"""						)

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ = 0.0 ,	SCREAMING_SNAKE_CASE_ = 1.0 ,	)			->float:
  return mean(
      function_to_integrate(uniform(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)						) for _ in range(SCREAMING_SNAKE_CASE_						)						) * (max_value - min_value)

def   A_      (       SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ = 0.0 ,	SCREAMING_SNAKE_CASE_ = 1.0						)			->None:

  def identity_function(SCREAMING_SNAKE_CASE_						) -> float:
    return x

  lowercase_     =       area_under_curve_estimator(
      SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
  lowercase_     =       (max_value * max_value - min_value * min_value) / 2

  print("""******************"""						)
  print(f"""Estimating area under y=x where x varies from {min_value} to {max_value}"""						)
  print(f"""Estimated value is {estimated_value}"""						)
  print(f"""Expected value is {expected_value}"""						)
  print(f"""Total error is {abs(estimated_value - expected_value						)}"""						)
  print("""******************"""						)

def   A_      (       SCREAMING_SNAKE_CASE_						)			->None:

  def function_to_integrate(SCREAMING_SNAKE_CASE_						) -> float:
    return sqrt(4.0 - x * x						)

  lowercase_     =       area_under_curve_estimator(
      SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_ ,	0.0 ,	2.0						)

  print("""******************"""						)
  print("""Estimating pi using area_under_curve_estimator"""						)
  print(f"""Estimated value is {estimated_value}"""						)
  print(f"""Expected value is {pi}"""						)
  print(f"""Total error is {abs(estimated_value - pi						)}"""						)
  print("""******************"""						)


if __name__ == "__main__":
       import doctest

       doctest.testmod()


'''simple docstring'''


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


__snake_case						  =		logging.get_logger(__name__)

__snake_case						  =		{
    """uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}





class       _a    (		__a      ):


  """simple docstring"""

  A_    							=						'''mra'''




  def __init__(		self      :       Any   ,				lowercase_      :       List[str]=50_265   ,				lowercase_      :       Tuple=768   ,				lowercase_      :       Optional[Any]=12   ,				lowercase_      :       str=12   ,				lowercase_      :       Optional[int]=3_072   ,				lowercase_      :       Union[str, Any]="gelu"   ,				lowercase_      :       str=0.1   ,				lowercase_      :       Tuple=0.1   ,				lowercase_      :       str=512   ,				lowercase_      :       Optional[int]=1   ,				lowercase_      :       Tuple=0.0_2   ,				lowercase_      :       List[Any]=1e-5   ,				lowercase_      :       Optional[Any]="absolute"   ,				lowercase_      :       int=4   ,				lowercase_      :       int="full"   ,				lowercase_      :       Tuple=0   ,				lowercase_      :       str=0   ,				lowercase_      :       List[str]=1   ,				lowercase_      :       Tuple=0   ,				lowercase_      :       Optional[Any]=2   ,				**lowercase_      :       List[str]   ,				):







    '''simple docstring'''


    super().__init__(pad_token_id=lowercase_   ,				bos_token_id=lowercase_   ,				eos_token_id=lowercase_   ,				**lowercase_      )

    lowercase_     =       vocab_size
    lowercase_     =       max_position_embeddings
    lowercase_     =       hidden_size
    lowercase_     =       num_hidden_layers
    lowercase_     =       num_attention_heads
    lowercase_     =       intermediate_size
    lowercase_     =       hidden_act
    lowercase_     =       hidden_dropout_prob
    lowercase_     =       attention_probs_dropout_prob
    lowercase_     =       initializer_range
    lowercase_     =       type_vocab_size
    lowercase_     =       layer_norm_eps
    lowercase_     =       position_embedding_type
    lowercase_     =       block_per_row
    lowercase_     =       approx_mode
    lowercase_     =       initial_prior_first_n_blocks
    lowercase_     =       initial_prior_diagonal_n_blocks

