



import math
def 				UpperCAmelCase__		(					_SCREAMING_SNAKE_CASE :						str					)->int:
      _lowerCAmelCase			      =	0
      if n % 2 == 0:
            count += 1
            while n % 2 == 0:
                  _lowerCAmelCase			      =	int(n / 2					)
    # the n input value must be odd so that
    # we can skip one element (ie i += 2)

      _lowerCAmelCase			      =	3

      while i <= int(math.sqrt(__lowercase					)					):
            if n % i == 0:
                  count += 1
                  while n % i == 0:
                        _lowerCAmelCase			      =	int(n / i					)
            _lowerCAmelCase			      =	i + 2

      # this condition checks the prime
      # number n is greater than 2

      if n > 2:
            count += 1
      return count


if __name__ == "__main__":
    UpperCAmelCase_          =				5_1_2_4_2_1_8_3
    print(F"""The number of distinct prime factors is/are {exact_prime_factor_count(n)}""")
    print(F"""The value of log(log(n)) is {math.log(math.log(n)):.4f}""")



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 			lowerCAmelCase__(     unittest.TestCase    ):






    '''simple docstring'''





    def        _lowerCamelCase			(						self					: Optional[int]						):





       '''simple docstring'''
       UpperCAmelCase_				:   str							= tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 100.0]						)
       UpperCAmelCase_				:   List[Any]							= get_tf_activation('''gelu'''						)
       UpperCAmelCase_				:   Any							= get_tf_activation('''gelu_10'''						)

       UpperCAmelCase_				:   int							= gelu(__snake_case						)
       UpperCAmelCase_				:   Union[str, Any]							= geluaa(__snake_case						)

       UpperCAmelCase_				:   Union[str, Any]							= tf.where(y_gelu_aa < 10.0							, 1.0							, 0.0						)

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





    def        _lowerCamelCase			(						self					: Dict						):





       '''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(__snake_case						):
          get_tf_activation('''bogus'''						)
       with self.assertRaises(__snake_case						):
          get_tf_activation(__snake_case						)