


'''simple docstring'''

import math





def __snake_case (				UpperCAmelCase_						:						int		):

 if 1 < number < 4:
  # 2 and 3 are primes
  return True
 elif number < 2 or number % 2 == 0 or number % 3 == 0:
  # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
  return False

 # All primes number are in format of 6k +/- 1
 for i in range(5 ,    int(math.sqrt(UpperCAmelCase_		) + 1		) ,    6		):
  if number % i == 0 or number % (i + 2) == 0:
   return False
 return True





def __snake_case (				UpperCAmelCase_						:						int = 2000000		):
 return sum(num for num in range(3 ,    UpperCAmelCase_ ,    2		) if is_prime(UpperCAmelCase_		)		) + 2 if n > 2 else 0


if __name__ == "__main__":
     print(f'''{solution() = }''')







'''simple docstring'''

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   snake_case		(   self					):







   """simple docstring"""
   lowerCamelCase_								=  tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 100.0]					)
   lowerCamelCase_								=  get_tf_activation("gelu"					)
   lowerCamelCase_								=  get_tf_activation("gelu_10"					)

   lowerCamelCase_								=  gelu(UpperCamelCase					)
   lowerCamelCase_								=  geluaa(UpperCamelCase					)

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

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







  def   snake_case		(   self					):







   """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(UpperCamelCase					):
    get_tf_activation("bogus"					)
   with self.assertRaises(UpperCamelCase					):
    get_tf_activation(UpperCamelCase					)



