






"""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,
)


_SCREAMING_SNAKE_CASE :    Optional[int]    =						{
    '''configuration_convnextv2''': [
        '''CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''ConvNextV2Config''',
    ]
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE :    List[Any]    =						[
      '''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

  _SCREAMING_SNAKE_CASE :    List[str]    =						_LazyModule(__name__, globals()['''__file__'''], _import_structure)












"""simple docstring"""





from __future__ import annotations







def 					lowerCamelCase__	(							_lowerCamelCase	:		list[int]		,    _lowerCamelCase	:		int			)				->    int:
  lowerCamelCase_					,     lowerCamelCase_   					=						0, len(_lowerCamelCase			) - 1
  while start_ind <= end_ind:
    if array[start_ind] == search_item:
      return start_ind
    elif array[end_ind] == search_item:
      return end_ind
    else:
      start_ind += 1
      end_ind -= 1
    # returns -1 if search_item is not found in array
  return -1


if __name__ == "__main__":
  print(double_linear_search(list(range(100)), 40))




