# Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license

from ultralytics.utils import SETTINGS

try:
    assert SETTINGS["raytune"] is True  # verify integration is enabled
    import ray
    from ray import tune
    from ray.air import session

except (ImportError, AssertionError):
    tune = None


def on_fit_epoch_end(trainer):
    """
    Report training metrics to Ray Tune at epoch end when a Ray session is active.

    Captures metrics from the trainer object and sends them to Ray Tune with the current epoch number,
    enabling hyperparameter tuning optimization. Only executes when within an active Ray Tune session.

    Args:
        trainer (ultralytics.engine.trainer.BaseTrainer): The Ultralytics trainer object containing metrics and epochs.

    Examples:
        >>> # Called automatically by the Ultralytics training loop
        >>> on_fit_epoch_end(trainer)

    References:
        Ray Tune docs: https://docs.ray.io/en/latest/tune/index.html
    """
    if ray.train._internal.session.get_session():  # check if Ray Tune session is active
        metrics = trainer.metrics
        session.report({**metrics, **{"epoch": trainer.epoch + 1}})


callbacks = (
    {
        "on_fit_epoch_end": on_fit_epoch_end,
    }
    if tune
    else {}
)
