

from __future__ import annotations



class   __lowercase				:




			"""simple docstring"""







			def __init__( self  :     Dict   ,						lowerCAmelCase__  :     List[Any]=None):
									SCREAMING_SNAKE_CASE_: str  		=       data
									SCREAMING_SNAKE_CASE_: Optional[int]  		=       None




			def __repr__( self  :     Optional[Any]):
									SCREAMING_SNAKE_CASE_: Any  		=       []
									SCREAMING_SNAKE_CASE_: int  		=       self
									while temp:
															string_rep.append(F"{temp.data}")
															SCREAMING_SNAKE_CASE_: Union[str, Any]  		=       temp.next
									return "->".join(lowerCAmelCase__)







def 			A_      (    _UpperCAmelCase    ):
						if not elements_list:
												raise Exception("The Elements List is empty"    )

						SCREAMING_SNAKE_CASE_: Tuple  		=       Node(elements_list[0]    )
						for i in range(1				,	len(_UpperCAmelCase    )    ):
												SCREAMING_SNAKE_CASE_: Tuple  		=       Node(elements_list[i]    )
												SCREAMING_SNAKE_CASE_: Any  		=       current.next
						return head







def 			A_      (    _UpperCAmelCase    ):
						if head_node is not None and isinstance(_UpperCAmelCase				,	_UpperCAmelCase    ):
												print_reverse(head_node.next    )
												print(head_node.data    )







def 			A_      (    ):
						from doctest import testmod

						testmod()

						SCREAMING_SNAKE_CASE_: Optional[Any]  		=       make_linked_list([14, 52, 14, 12, 43]    )
						print("Linked List:"    )
						print(_UpperCAmelCase    )
						print("Elements in Reverse:"    )
						print_reverse(_UpperCAmelCase    )


if __name__ == "__main__":
						main()










# 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)

