


"""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

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


__magic_name__	:   Dict          =							{
    'configuration_tvlt': ['TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TvltConfig'],
    'feature_extraction_tvlt': ['TvltFeatureExtractor'],
    'processing_tvlt': ['TvltProcessor'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__magic_name__	:   Tuple          =							[
					    'TVLT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TvltModel',
					    'TvltForPreTraining',
					    'TvltForAudioVisualClassification',
					    'TvltPreTrainedModel',
					]

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__magic_name__	:   Optional[Any]          =							['TvltImageProcessor']


if TYPE_CHECKING:
					from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
					from .processing_tvlt import TvltProcessor
					from .feature_extraction_tvlt import TvltFeatureExtractor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tvlt import (
										    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TvltForAudioVisualClassification,
										    TvltForPreTraining,
										    TvltModel,
										    TvltPreTrainedModel,
										)

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_tvlt import TvltImageProcessor


else:
					import sys

					__magic_name__	:   List[str]          =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








"""simple docstring"""




import numpy as np





def 			a_   (  lowercase__   :List[str]    ):
			__lowerCamelCase        =			np.exp(lowercase__    )

			# Add up the all the exponentials
			__lowerCamelCase        =			np.sum(lowercase__    )

			# Divide every exponent by the sum of all exponents
			__lowerCamelCase        =			exponent_vector / sum_of_exponents

			return softmax_vector


if __name__ == "__main__":
					print(softmax((0,)))




