


# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase		   =			{
    'configuration_vivit': ['VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VivitConfig'],
}
try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase		   =			['VivitImageProcessor']


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCamelCase		   =			[
     'VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
     'VivitModel',
     'VivitPreTrainedModel',
     'VivitForVideoClassification',
 ]


if TYPE_CHECKING:
 from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .image_processing_vivit import VivitImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_vivit import (
      VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
      VivitForVideoClassification,
      VivitModel,
      VivitPreTrainedModel,
  )


else:
 import sys

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






import numpy as np




def       a_ (       SCREAMING_SNAKE_CASE__   : np.ndarray						,     SCREAMING_SNAKE_CASE__   : float	):
       '''simple docstring'''





       return np.where(vector > 0						,     SCREAMING_SNAKE_CASE__						,     (alpha * (np.exp(SCREAMING_SNAKE_CASE__	) - 1))	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()


