



import unittest

import numpy as np

from transformers import is_tf_available
from transformers.testing_utils import require_tf


if is_tf_available():
    import tensorflow as tf

    from transformers.activations_tf import get_tf_activation



@require_tf
class 		_snake_case      (			unittest.TestCase				):





 """simple docstring"""



 def lowercase_		(						self					)	->							List[str]:




   """simple docstring"""







   _A           =    tf.constant([-1_0_0, -1.0, -0.1, 0, 0.1, 1.0, 100.0]					)
   _A           =    get_tf_activation('''gelu'''					)
   _A           =    get_tf_activation('''gelu_10'''					)

   _A           =    gelu(a					)
   _A           =    geluaa(a					)

   _A           =    tf.where(y_gelu_aa < 10.0	,    1.0	,    0.0					)

   self.assertEqual(tf.math.reduce_max(a					).numpy().item()	,    10.0					)
   self.assertTrue(np.allclose(y_gelu * clipped_mask	,    y_gelu_aa * clipped_mask					)					)



 def lowercase_		(						self					)	->							Union[str, Any]:




   """simple docstring"""







   get_tf_activation('''gelu'''					)
   get_tf_activation('''gelu_10'''					)
   get_tf_activation('''gelu_fast'''					)
   get_tf_activation('''gelu_new'''					)
   get_tf_activation('''glu'''					)
   get_tf_activation('''mish'''					)
   get_tf_activation('''quick_gelu'''					)
   get_tf_activation('''relu'''					)
   get_tf_activation('''sigmoid'''					)
   get_tf_activation('''silu'''					)
   get_tf_activation('''swish'''					)
   get_tf_activation('''tanh'''					)
   with self.assertRaises(a					):
     get_tf_activation('''bogus'''					)
   with self.assertRaises(a					):
     get_tf_activation(a					)




def     UpperCAmelCase__ (							__snake_case						,				__snake_case = 1_000							)   -> str:
  if (not isinstance(__snake_case						,				__snake_case							)) or (digit_position <= 0):
    raise ValueError('''Digit position must be a positive integer'''							)
  elif (not isinstance(__snake_case						,				__snake_case							)) or (precision < 0):
    raise ValueError('''Precision must be a nonnegative integer'''							)

  # compute an approximation of (16 ** (n - 1)) * pi whose fractional part is mostly
  # accurate
  _A           =    (
      4 * _subsum(__snake_case						,				1						,				__snake_case							)
      - 2 * _subsum(__snake_case						,				4						,				__snake_case							)
      - _subsum(__snake_case						,				5						,				__snake_case							)
      - _subsum(__snake_case						,				6						,				__snake_case							)
  )

  # return the first hex digit of the fractional part of the result
  return hex(int((sum_result % 1) * 16							)							)[2:]




def     UpperCAmelCase__ (							__snake_case						,				__snake_case						,				__snake_case							)   -> float:
  _A           =    0.0
  for sum_index in range(digit_pos_to_extract + precision							):
    _A           =    8 * sum_index + denominator_addend
    if sum_index < digit_pos_to_extract:
      # if the exponential term is an integer and we mod it by the denominator
      # before dividing, only the integer part of the sum will change;
      # the fractional part will not
      _A           =    pow(
          16						,				digit_pos_to_extract - 1 - sum_index						,				__snake_case							)
    else:
      _A           =    pow(16						,				digit_pos_to_extract - 1 - sum_index							)
    total += exponential_term / denominator
  return total


if __name__ == "__main__":
    import doctest

    doctest.testmod()