ray.rllib.core.learner.learner.LearnerHyperparameters

class ray.rllib.core.learner.learner.LearnerHyperparameters(learning_rate: float | List[List[int | float]] = None, grad_clip: float = None, grad_clip_by: str = None, seed: int = None, _per_module_overrides: Dict[str, LearnerHyperparameters] | None = None)

Hyperparameters for a Learner, derived from a subset of AlgorithmConfig values.

Instances of this class should only be created via calling get_learner_hyperparameters() on a frozen AlgorithmConfig object and should always considered read-only.

When creating a new Learner, you should also define a new sub-class of this class and make sure the respective AlgorithmConfig sub-class has a proper implementation of the get_learner_hyperparameters method.

Validation of the values of these hyperparameters should be done by the respective AlgorithmConfig class.

For configuring different learning behaviors for different (single-agent) RLModules within the Learner, RLlib uses the _per_module_overrides property (dict), mapping ModuleID to a overridden version of self, in which the module-specific override settings are applied.

Methods

get_hps_for_module

Returns a LearnerHyperparameter instance, given a module_id.

Attributes

grad_clip
grad_clip_by
learning_rate
seed