[Tune] [Air] Ray Tune + MLflow integration with setup_mlflow does not record runs about ray HOT 4 OPEN

def train_function_mlflow(config):
    mlflow_config = config.pop('mlflow', None)
    
    setup_mlflow(config)
    mlflow.set_tracking_uri(uri=mlflow_config['tracking_uri'])
    mlflow.set_experiment(experiment_name=mlflow_config['experiment_name'])
    mlflow.log_params(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
        intermediate_score = evaluation_fn(step, width, height)
        # Log the metrics to mlflow
        mlflow.log_metrics(dict(mean_loss=intermediate_score), step=step)
        # Feed the score back to Tune.
        train.report({"iterations": step, "mean_loss": intermediate_score})
        time.sleep(0.1)


def tune_with_setup(mlflow_tracking_uri, experiment_name, finish_fast=False):
    # Set the experiment, or create a new one if does not exist yet.
    mlflow.set_tracking_uri(mlflow_tracking_uri)
    mlflow.set_experiment(experiment_name=experiment_name)
    tuner = tune.Tuner(
        train_function_mlflow,
        run_config=train.RunConfig(
            name="mlflow",
        ),
        tune_config=tune.TuneConfig(
            num_samples=5,
        ),
        param_space={
            "width": tune.randint(10, 100),
            "height": tune.randint(0, 100),
            "steps": 5 if finish_fast else 25,
            "mlflow": {
                "experiment_name": experiment_name,
                "tracking_uri": mlflow_tracking_uri,
            },
        },
    )
    tuner.fit()