






# 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


UpperCamelCase								=		{
    "configuration_efficientnet": [
        "EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientNetConfig",
        "EfficientNetOnnxConfig",
    ]
}

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

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCamelCase								=		[
							    "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

							UpperCamelCase								=		_LazyModule(__name__, globals()["__file__"], _import_structure)









"""simple docstring"""







def     UpperCAmelCase_					(				__a   :			list						):




			'''simple docstring'''



			if len(__a						) <= 1:
						return lst

			_lowerCamelCase					:					str	       =    1

			while i < len(__a						):
						if lst[i - 1] <= lst[i]:
									i += 1
						else:
									_lowerCamelCase       ,							_lowerCamelCase					:					Optional[Any]	       =    lst[i], lst[i - 1]
									i -= 1
									if i == 0:
												_lowerCamelCase					:					Dict	       =    1

			return lst


if __name__ == "__main__":
	a_							=    input("""Enter numbers separated by a comma:\n""").strip()
	a_							=    [int(item) for item in user_input.split(""",""")]
	print(gnome_sort(unsorted))





