
from __future__ import annotations

from collections.abc import Iterator
from typing import Any




class    _SCREAMING_SNAKE_CASE					:
      def __init__(     self						,		lowerCamelCase	):
          snake_case__  =			data
          snake_case__  =			None



      def __str__(     self	):
          return F"""{self.data}"""





class    _SCREAMING_SNAKE_CASE					:
      def __init__(     self	):
          snake_case__  =			None
          snake_case__  =			None
      def __iter__(     self	):
          snake_case__  =			self.front
          while node:
              yield node.data
              snake_case__  =			node.next
      def __len__(     self	):
          return len(tuple(iter(self	)	)	)
      def __str__(     self	):
          return " <- ".join(str(lowerCamelCase	) for item in self	)
      def A_     (     self	):
          return len(self	) == 0
      def A_     (     self						,		lowerCamelCase	):
          snake_case__  =			Node(lowerCamelCase	)
          if self.is_empty():
              snake_case__  =			snake_case__  =			node
          else:
              assert isinstance(self.rear						,		lowerCamelCase	)
              snake_case__  =			node
              snake_case__  =			node
      def A_     (     self	):
          if self.is_empty():
              raise IndexError("dequeue from empty queue"	)
          assert isinstance(self.front						,		lowerCamelCase	)
          snake_case__  =			self.front
          snake_case__  =			self.front.next
          if self.front is None:
              snake_case__  =			None
          return node.data



      def A_     (     self	):
          snake_case__  =			snake_case__  =			None


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

     testmod()





# 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,
)


__magic_name__           =					{
    '''configuration_convnextv2''': [
        '''CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConvNextV2Config''',
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __magic_name__           =					[
         '''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

     __magic_name__           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure)



