code: 
  
  
  import copy
  
  from transformers.configuration_utils import PretrainedConfig
  from transformers.utils import logging
  
  
  lowerCAmelCase__   	=				logging.get_logger(__name__)
  
  
  
  
  
  
  
  class   lowerCAmelCase__ (       a):
  
  
  
  
       '''simple docstring'''
       __SCREAMING_SNAKE_CASE						    =				"hybrid-clip"
       __SCREAMING_SNAKE_CASE						    =				True
  
  
       def __init__(		self				,		__lowerCamelCase=5_1_2				,		**__lowerCamelCase)    ->       str:
              super().__init__(**__lowerCamelCase)
  
              if "text_config" not in kwargs:
                     raise ValueError("`text_config` can not be `None`.")
  
              if "vision_config" not in kwargs:
                     raise ValueError("`vision_config` can not be `None`.")
  
              _A   : Optional[int]       					=				kwargs.pop("text_config")
              _A   : Union[str, Any]       					=				kwargs.pop("vision_config")
  
              _A   : Dict       					=				text_config.pop("model_type")
              _A   : Optional[int]       					=				vision_config.pop("model_type")
  
              from transformers import AutoConfig
  
              _A   : List[Any]       					=				AutoConfig.for_model(__lowerCamelCase				,		**__lowerCamelCase)
  
              if vision_model_type == "clip":
                     _A   : Any       					=				AutoConfig.for_model(__lowerCamelCase				,		**__lowerCamelCase).vision_config
              elif vision_model_type == "clip_vision_model":
                     from transformers import CLIPVisionConfig
  
                     _A   : Tuple       					=				CLIPVisionConfig(**__lowerCamelCase)
              else:
                     _A   : List[str]       					=				AutoConfig.for_model(__lowerCamelCase				,		**__lowerCamelCase)
  
              _A   : int       					=				projection_dim
              _A   : str       					=				1.0
  
  
       @classmethod
       def 				_lowerCamelCase				(		cls				,		__lowerCamelCase				,		__lowerCamelCase				,		**__lowerCamelCase)    ->       Union[str, Any]:
              return cls(text_config=text_config.to_dict()				,		vision_config=vision_config.to_dict()				,		**__lowerCamelCase)
  
  
       def 				_lowerCamelCase				(		self)    ->       int:
              _A   : Dict       					=				copy.deepcopy(self.__dict__)
              _A   : Union[str, Any]       					=				self.text_config.to_dict()
              _A   : Dict       					=				self.vision_config.to_dict()
              _A   : List[Any]       					=				self.__class__.model_type
              return output
  
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
  
  
  lowerCAmelCase__   	=				{'configuration_detr': ['DETR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DetrConfig', 'DetrOnnxConfig']}
  
  try:
      if not is_vision_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      lowerCAmelCase__   	=				['DetrFeatureExtractor']
      lowerCAmelCase__   	=				['DetrImageProcessor']
  
  try:
      if not is_torch_available():
          raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
      pass
  else:
      lowerCAmelCase__   	=				[
          'DETR_PRETRAINED_MODEL_ARCHIVE_LIST',
          'DetrForObjectDetection',
          'DetrForSegmentation',
          'DetrModel',
          'DetrPreTrainedModel',
      ]
  
  
  if TYPE_CHECKING:
      from .configuration_detr import DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DetrConfig, DetrOnnxConfig
  
      try:
          if not is_vision_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .feature_extraction_detr import DetrFeatureExtractor
          from .image_processing_detr import DetrImageProcessor
  
      try:
          if not is_torch_available():
              raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
          pass
      else:
          from .modeling_detr import (
              DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
              DetrForObjectDetection,
              DetrForSegmentation,
              DetrModel,
              DetrPreTrainedModel,
          )
  
  else:
      import sys
  
      lowerCAmelCase__   	=				_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
  