tune_mlflow_logger.py

from ray.tune.integration.mlflow import MLflowLoggerCallback
tune.run(
    train_fn,
    config={
        # define search space here
        "parameter_1": tune.choice([1, 2, 3]),
        "parameter_2": tune.choice([4, 5, 6]),
    },
    callbacks=[MLflowLoggerCallback(
        experiment_name="experiment1",
        save_artifact=True)])