
'''simple docstring'''
# 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					:    Any           = {
    'configuration_vivit': ['VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VivitConfig'],
}
try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Union[str, Any]           = ['VivitImageProcessor']


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Optional[Any]           = [
						    '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					:    List[str]           = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase







def 		A_(     A						:		str):
							if not sentence:
														return ""
							UpperCamelCase   			=     dict(zip(A		,     A))
							return lower_to_upper.get(sentence[0]		,     sentence[0]) + sentence[1:]


if __name__ == "__main__":
						from doctest import testmod

						testmod()




