'''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 	__SCREAMING_SNAKE_CASE		(			unittest.TestCase			):







  '''simple docstring'''






  def _UpperCamelCase	(					self		):




       '''simple docstring'''

       UpperCAmelCase_				:  List[Any]  = tf.constant([-1_0_0, -1.0, -0.1, 0, 0.1, 1.0, 1_00.0]		)
       UpperCAmelCase_				:  Optional[int]  = get_tf_activation('gelu'		)
       UpperCAmelCase_				:  int  = get_tf_activation('gelu_10'		)

       UpperCAmelCase_				:  List[str]  = gelu(snake_case_		)
       UpperCAmelCase_				:  List[str]  = geluaa(snake_case_		)

       UpperCAmelCase_				:  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 _UpperCamelCase	(					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(snake_case_		):
            get_tf_activation('bogus'		)
       with self.assertRaises(snake_case_		):
            get_tf_activation(snake_case_		)










__SCREAMING_SNAKE_CASE	:							Optional[Any]           =  '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''

__SCREAMING_SNAKE_CASE	:							Optional[int]           =  [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
__SCREAMING_SNAKE_CASE	:							Optional[int]           =  {
    '''{processor_class}''': '''FakeProcessorClass''',
    '''{model_class}''': '''FakeModelClass''',
    '''{object_class}''': '''FakeObjectClass''',
}

