code: def training_function(config):
      # Hyperparameters
      alpha, beta = config["alpha"], config["beta"]
      for step in range(10):
          # Iterative training function - can be any arbitrary training procedure.
          intermediate_score = objective(step, alpha, beta)
          # Feed the score back back to Tune.
          train.report(dict(mean_loss=intermediate_score))
  
label_desc: Use image node_id 2 for calling a global function with example usage: training_function(config) without return types