



"""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       __lowerCamelCase	(   unittest.TestCase    ):







   def 							A__						(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(lowerCamelCase				)
      _lowerCAmelCase					     =		geluaa(lowerCamelCase				)

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

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







   def 							A__						(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(lowerCamelCase				):
         get_tf_activation("""bogus"""				)
      with self.assertRaises(lowerCamelCase				):
         get_tf_activation(lowerCamelCase				)




"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


SCREAMING_SNAKE_CASE				:     Union[str, Any]          =	{
    '''configuration_align''': [
        '''ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''AlignConfig''',
        '''AlignTextConfig''',
        '''AlignVisionConfig''',
    ],
    '''processing_align''': ['''AlignProcessor'''],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE				:     Any          =	[
      '''ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''AlignModel''',
      '''AlignPreTrainedModel''',
      '''AlignTextModel''',
      '''AlignVisionModel''',
  ]

if TYPE_CHECKING:
  from .configuration_align import (
      ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
      AlignConfig,
      AlignTextConfig,
      AlignVisionConfig,
  )
  from .processing_align import AlignProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_align import (
        ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
        AlignModel,
        AlignPreTrainedModel,
        AlignTextModel,
        AlignVisionModel,
    )

else:
  import sys

  SCREAMING_SNAKE_CASE				:     Any          =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)