


# 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


snake_case							: List[str]      =   {
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: str      =   ["EfficientNetImageProcessor"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						snake_case							: Dict      =   [
						    "EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "EfficientNetForImageClassification",
						    "EfficientNetModel",
						    "EfficientNetPreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_efficientnet import (
						    EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    EfficientNetConfig,
						    EfficientNetOnnxConfig,
						)

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_efficientnet import EfficientNetImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_efficientnet import (
												    EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
												    EfficientNetForImageClassification,
												    EfficientNetModel,
												    EfficientNetPreTrainedModel,
												)

else:
						import sys

						snake_case							: Optional[Any]      =   _LazyModule(__name__, globals()['''__file__'''], _import_structure)








from __future__ import annotations






def 							__lowercase     (				__lowerCAmelCase							:       list[int]     ):  # This function is recursive
							a__    =  len(__lowerCAmelCase     )
							# If the array contains only one element, we return it (it's the stop condition of
							# recursion)
							if array_length <= 1:
														return array
														# Else
							a__    =  array[0]
							a__    =  False
							a__    =  1
							a__    =  []
							while not is_found and i < array_length:
														if array[i] < pivot:
																					a__    =  True
																					a__    =  [element for element in array[i:] if element >= array[i]]
																					a__    =  longest_subsequence(__lowerCAmelCase     )
																					if len(__lowerCAmelCase     ) > len(__lowerCAmelCase     ):
																												a__    =  temp_array
														else:
																					i += 1

							a__    =  [element for element in array[1:] if element >= pivot]
							a__    =  [pivot, *longest_subsequence(__lowerCAmelCase     )]
							if len(__lowerCAmelCase     ) > len(__lowerCAmelCase     ):
														return temp_array
							else:
														return longest_subseq


if __name__ == "__main__":
						import doctest

						doctest.testmod()




