


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 			A						(     unittest.TestCase  ):






      def  lowerCamelCase (      self		:  Tuple				)      ->		int:
             """simple docstring"""




             _lowerCamelCase :	Any						=tf.constant([-100, -1.0, -0.1, 0, 0.1, 1.0, 100.0]				)
             _lowerCamelCase :	List[str]						=get_tf_activation('gelu'				)
             _lowerCamelCase :	Optional[int]						=get_tf_activation('gelu_10'				)

             _lowerCamelCase :	Optional[Any]						=gelu(lowercase_				)
             _lowerCamelCase :	int						=geluaa(lowercase_				)

             _lowerCamelCase :	Optional[int]						=tf.where(y_gelu_aa < 10.0    ,     1.0    ,     0.0				)

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






      def  lowerCamelCase (      self		:  List[str]				)      ->		Optional[int]:
             """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(lowercase_				):
                    get_tf_activation('bogus'				)
             with self.assertRaises(lowercase_				):
                    get_tf_activation(lowercase_				)






from __future__ import annotations

from collections.abc import Generator




def 			a_   (					SCREAMING_SNAKE_CASE__      :   int  ):
       '''simple docstring'''





       if not isinstance(SCREAMING_SNAKE_CASE__	,    SCREAMING_SNAKE_CASE__  ) or n < 1:
              raise Exception('Sequence only defined for positive integers'  )

       yield n
       while n != 1:
              if n % 2 == 0:
                     n //= 2
              else:
                     _lowerCamelCase :	Optional[int]						=3 * n + 1
              yield n




def 			a_   (					):
       '''simple docstring'''





       _lowerCamelCase :	Dict						=43
       _lowerCamelCase :	Dict						=tuple(collatz_sequence(SCREAMING_SNAKE_CASE__  )  )
       print(SCREAMING_SNAKE_CASE__  )
       print(F'''Collatz sequence from {n} took {len(SCREAMING_SNAKE_CASE__  )} steps.'''  )


if __name__ == "__main__":
 main()


