



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase__     			=							{'''configuration_nat''': ['''NAT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NatConfig''']}


try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__     			=							[
      '''NAT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''NatForImageClassification''',
      '''NatModel''',
      '''NatPreTrainedModel''',
      '''NatBackbone''',
  ]

if TYPE_CHECKING:
  from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_nat import (
        NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
        NatBackbone,
        NatForImageClassification,
        NatModel,
        NatPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__     			=							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





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 )  ->     Optional[Any]:
      _lowercase							   =tf.constant([-1_0_0, -1.0, -0.1, 0, 0.1, 1.0, 100.0] )
      _lowercase							   =get_tf_activation('''gelu''' )
      _lowercase							   =get_tf_activation('''gelu_10''' )

      _lowercase							   =gelu(UpperCAmelCase )
      _lowercase							   =geluaa(UpperCAmelCase )

      _lowercase							   =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   __A      (self )  ->     Optional[Any]:
      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 )

