class_docstr: :class:`HybridCLIPConfig` is the configuration class to store the configuration of a
  :class:`~HybridCLIPModel`. It is used to instantiate HybridCLIPModel model according to the specified arguments,
  defining the text model and vision model configs.
  
  Configuration objects inherit from :class:`~transformers.PretrainedConfig` and can be used to control the model
  outputs. Read the documentation from :class:`~transformers.PretrainedConfig` for more information.
  
  Args:
      text_config_dict (:obj:`dict`):
          Dictionary of configuration options that defines text model config.
      vision_config_dict (:obj:`dict`):
          Dictionary of configuration options that defines vison model config.
      projection_dim (:obj:`int`, `optional`, defaults to 512):
          Dimentionality of text and vision projection layers.
      kwargs (`optional`):
          Dictionary of keyword arguments.
  
  Examples::
  
      >>> from transformers import BertConfig, CLIPConfig, HybridCLIPConfig, FlaxHybridCLIP
  
      >>> # Initializing a BERT and CLIP configuration
      >>> config_text = BertConfig()
      >>> config_vision = CLIPConfig()
  
      >>> config = HybridCLIPConfig.from_text_vision_configs(config_text, config_vision, projection_dim=512)
  
      >>> # Initializing a BERT and CLIPVision model
      >>> model = EncoderDecoderModel(config=config)
  
      >>> # Accessing the model configuration
      >>> config_text = model.config.text_config
      >>> config_vision  = model.config.vision_config
  
      >>> # Saving the model, including its configuration
      >>> model.save_pretrained('my-model')
  
      >>> # loading model and config from pretrained folder
      >>> encoder_decoder_config = HybridCLIPConfig.from_pretrained('my-model')
      >>> model = FlaxHybridCLIP.from_pretrained('my-model', config=encoder_decoder_config)
docstr: Serializes this instance to a Python dictionary. Override the default
  :meth:`~transformers.PretrainedConfig.to_dict`.
  
  Returns:
      :obj:`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
docstr_tok: ["Serializes","this","instance","to","a","Python","dictionary",".","Override","the","default",":","meth",":","`","~transformers.PretrainedConfig.to_dict","`",".","Returns",":",":","obj",":","`","Dict","[","str",",","any","]","`",":","Dictionary","of","all","the","attributes","that","make","up","this","configuration","instance",","]
code: def to_dict(self):
      """
      Serializes this instance to a Python dictionary. Override the default
      :meth:`~transformers.PretrainedConfig.to_dict`.
  
      Returns:
          :obj:`Dict[str, any]`: Dictionary of all the attributes that make up this configuration instance,
      """
      output = copy.deepcopy(self.__dict__)
      output["text_config"] = self.text_config.to_dict()
      output["vision_config"] = self.vision_config.to_dict()
      output["model_type"] = self.__class__.model_type
      return output
  
imports: import copy
  from transformers.configuration_utils import PretrainedConfig
  from transformers.utils import logging
label_desc: Use image node_id 3 for calling the HybridCLIPConfig obj's underlying member method code with example usage: obj.to_dict() and returns: output