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lit_sb3.callbacks.trial_eval

source module lit_sb3.callbacks.trial_eval

TrialEvalCallback for Optuna hyperparameter optimisation.

Classes

source class TrialEvalCallback(eval_env: VecEnv, trial: Any, n_eval_episodes: int = 5, eval_freq: int = 10000, deterministic: bool = True, verbose: int = 0, best_model_save_path: str | Path | None = None, log_path: str | Path | None = None)

Bases : EvalCallback

Callback used for evaluating and reporting an Optuna trial.

Evaluates the model every eval_freq steps and reports the mean reward to the Optuna trial. If the trial should be pruned, training is stopped early.

Parameters

  • eval_env : VecEnv — Environment used for evaluation.

  • trial : Any — Optuna trial instance.

  • n_eval_episodes : int — Number of episodes per evaluation.

  • eval_freq : int — Evaluate every eval_freq steps.

  • deterministic : bool — Use deterministic actions during evaluation.

  • verbose : int — Verbosity level.

  • best_model_save_path : str | Path | None — Where to save the best model.

  • log_path : str | Path | None — Where to save evaluation logs.

Attributes

  • state_key : str — Identifier for the state of the callback.