b71c912da70e307ff1a9f07c7ca277a727306126,python/ray/tune/examples/mlflow_example.py,,easy_objective,#Any#,18

Before Change

    for i in range(20):
        result = dict(
            timesteps_total=i,
            mean_loss=(config["height"] - 14)**2 - abs(config["width"] - 3))
        tune.report(**result)
        time.sleep(0.02)

After Change

def easy_objective(config):
    // Hyperparameters
    width, height = config["width"], config["height"]

    for step in range(config.get("steps", 100)):
        // Iterative training function - can be any arbitrary training procedure

Instances