code: 
  
  
  
  
  """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       = {
      "configuration_convnextv2": [
          "CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP",
          "ConvNextV2Config",
      ]
  }
  
  try:
        if not is_torch_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        SCREAMING_SNAKE_CASE       = [
            "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       = _LazyModule(__name__, globals()["__file__"], _import_structure)
  
  
  
  
  
  
style_context: 
  
  
  
  
  """simple docstring"""
  
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  SCREAMING_SNAKE_CASE       = {
      "configuration_deta": ["DETA_PRETRAINED_CONFIG_ARCHIVE_MAP", "DetaConfig"],
  }
  
  try:
        if not is_vision_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        SCREAMING_SNAKE_CASE       = ["DetaImageProcessor"]
  
  try:
        if not is_torch_available():
              raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
        pass
  else:
        SCREAMING_SNAKE_CASE       = [
            "DETA_PRETRAINED_MODEL_ARCHIVE_LIST",
            "DetaForObjectDetection",
            "DetaModel",
            "DetaPreTrainedModel",
        ]
  
  
  if TYPE_CHECKING:
        from .configuration_deta import DETA_PRETRAINED_CONFIG_ARCHIVE_MAP, DetaConfig
  
        try:
              if not is_vision_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .image_processing_deta import DetaImageProcessor
  
        try:
              if not is_torch_available():
                    raise OptionalDependencyNotAvailable()
        except OptionalDependencyNotAvailable:
              pass
        else:
              from .modeling_deta import (
                  DETA_PRETRAINED_MODEL_ARCHIVE_LIST,
                  DetaForObjectDetection,
                  DetaModel,
                  DetaPreTrainedModel,
              )
  
  else:
        import sys
  
        SCREAMING_SNAKE_CASE       = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
  
  
  
  
  
  