code: def get_config(run_local: str = "") -> ml_collections.ConfigDict:
      """Returns the experiment configuration."""
      config = base.get_config(run_local)
  
      config.experiment_name = "clip"
  
      config.model_name = "image_text"
  
      config.model.encoder_name = "clip"
      config.model.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 = get_clip_image_size(
          config.model.encoder.config_name
      )
      config.dataset_configs.crop_size = get_clip_image_size(
          config.model.encoder.config_name
      )
      config.dataset_configs.normalization_mean = (
          0.48145466,
          0.4578275,
          0.40821073,
      )
      config.dataset_configs.normalization_std = (
          0.26862954,
          0.26130258,
          0.27577711,
      )
      config.dataset_configs.tokenizer.tokenizer_type = "clip"
  
      config.dataset_configs.tokenizer_type = "dmvr"
      config.dataset_configs.vocab_size = 49_408
  
      return config
  
label_desc: Use image node_id 2 for calling a global function with example usage: get_config(run_local) and returns: config