code: def get_config(runlocal=""):
      """Returns the ViT experiment configuration for SV classification."""
      runlocal = bool(runlocal)
  
      config = ml_collections.ConfigDict()
      config.experiment_name = "sv-vit_offline_eval"
      config.trainer_name = "inference"
  
      # Dataset.
      config.dataset_name = "pileup_window"
      config.data_dtype_str = "float32"
      config.dataset_configs = ml_collections.ConfigDict()
      config.dataset_configs.train_path = ""
      config.dataset_configs.test_path = ""
      config.dataset_configs.eval_path = ""
  
      # Model to be evaluated.
      config.model_name = "xvit_classification"
      config.init_from = ml_collections.ConfigDict()
      config.init_from.xm = (None, None)
      config.batch_size = 8 if runlocal else 512
      config.rng_seed = 42
      config.save_predictions_on_cns = True
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_config(runlocal) and returns: config