




'''simple docstring'''


from __future__ import annotations

from collections.abc import Iterator
from typing import Any

class 			A    :







							def __init__(  self       :  Optional[Any]							,			lowerCAmelCase_       :  Any					)			->							None:


														"""simple docstring"""


														_a	     =				data
														_a	     =				None







							def __str__(  self       :  Optional[int]					)			->							str:


														"""simple docstring"""


														return F'{self.data}'



class 			A    :







							def __init__(  self       :  List[Any]					)			->							None:


														"""simple docstring"""


														_a	     =				None
														_a	     =				None







							def __iter__(  self       :  Dict					)			->							Iterator[Any]:


														"""simple docstring"""


														_a	     =				self.front
														while node:
																					yield node.data
																					_a	     =				node.next







							def __len__(  self       :  Tuple					)			->							int:


														"""simple docstring"""


														return len(tuple(iter(self					)					)					)







							def __str__(  self       :  List[str]					)			->							str:


														"""simple docstring"""


														return " <- ".join(str(lowerCAmelCase_					) for item in self					)







							def    __lowerCAmelCase			(  self       :  int					)			->							bool:


														"""simple docstring"""


														return len(self					) == 0







							def    __lowerCAmelCase			(  self       :  List[str]							,			lowerCAmelCase_       :  Any					)			->							None:


														"""simple docstring"""


														_a	     =				Node(lowerCAmelCase_					)
														if self.is_empty():
																					_a	     =				_a	     =				node
														else:
																					assert isinstance(self.rear							,			lowerCAmelCase_					)
																					_a	     =				node
																					_a	     =				node







							def    __lowerCAmelCase			(  self       :  Any					)			->							Any:


														"""simple docstring"""


														if self.is_empty():
																					raise IndexError('''dequeue from empty queue'''					)
														assert isinstance(self.front							,			lowerCAmelCase_					)
														_a	     =				self.front
														_a	     =				self.front.next
														if self.front is None:
																					_a	     =				None
														return node.data







							def    __lowerCAmelCase			(  self       :  Optional[Any]					)			->							None:


														"""simple docstring"""


														_a	     =				_a	     =				None


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

				testmod()







'''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,
)


_snake_case      :      Tuple   							=		{
    'configuration_convnextv2': [
        'CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ConvNextV2Config',
    ]
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				_snake_case      :      Tuple   							=		[
				    'CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'ConvNextV2ForImageClassification',
				    'ConvNextV2Model',
				    'ConvNextV2PreTrainedModel',
				    'ConvNextV2Backbone',
				]


if TYPE_CHECKING:
				from .configuration_convnextva import (
				    CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    ConvNextVaConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_convnextva import (
								    CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ConvNextVaBackbone,
								    ConvNextVaForImageClassification,
								    ConvNextVaModel,
								    ConvNextVaPreTrainedModel,
								)

else:
				import sys

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

