code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      config = base_clip.get_config(run_local)
  
      config.experiment_name = "clip_clip"
  
      del config.model.encoder_name
      del config.model.encoder.config_name
      del config.model.encoder
  
      config.model.image_encoder_name = "clip"
      config.model.image_encoder = ml_collections.ConfigDict()
      config.model.image_encoder.config_name = "vit_b32"
  
      config.model.text_encoder_name = "clip"
      config.model.text_encoder = ml_collections.ConfigDict()
      config.model.text_encoder.config_name = "vit_b32"
  
      # The following configurations are meant to be used by DMVR datasets but also
      # as input to other parts of the config.
  
      config.dataset_configs.min_resize = base_clip.get_clip_image_size(
          config.model.image_encoder.config_name
      )
      config.dataset_configs.crop_size = base_clip.get_clip_image_size(
          config.model.image_encoder.config_name
      )
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(run_local) and returns: config