lit_sb3.buffers.maskable.rollout

source module lit_sb3.buffers.maskable.rollout

Classes

• MaskableRolloutBufferSamples

• MaskableRolloutBuffer — Rollout buffer that also stores the invalid action masks associated with each observation.

source class MaskableRolloutBufferSamples()

Bases : NamedTuple

source class MaskableRolloutBuffer(buffer_size: int, observation_space: spaces.Space, action_space: spaces.Space, device: torch.device | str = 'auto', gae_lambda: float = 1, gamma: float = 0.99, n_envs: int = 1)

Bases : RolloutBuffer

Rollout buffer that also stores the invalid action masks associated with each observation.

Parameters

• buffer_size : int — Max number of element in the buffer

• observation_space : spaces.Space — Observation space

• action_space : spaces.Space — Action space

• device : torch.device | str — PyTorch device

• gae_lambda : float — Factor for trade-off of bias vs variance for Generalized Advantage Estimator Equivalent to classic advantage when set to 1.

• gamma : float — Discount factor

• n_envs : int — Number of parallel environments

Methods

• reset

• add — Add transition to buffer.

• get

source method MaskableRolloutBuffer.reset() → None

Raises

• TypeError

source method MaskableRolloutBuffer.add(*args, action_masks: np.ndarray | None = None, **kwargs) → None

Add transition to buffer.

Parameters

• *args — Positional arguments forwarded to parent add.

• action_masks : np.ndarray | None — Masks applied to constrain the choice of possible actions.

• **kwargs — Keyword arguments forwarded to parent add.

source method MaskableRolloutBuffer.get(batch_size: int | None = None) → Generator[MaskableRolloutBufferSamples, None, None]