reference/generated/torchrl.trainers.algorithms.configs.modules.DreamerV3DiscreteActorConfig

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torchrl.trainers.algorithms.configs.modules.DreamerV3DiscreteActorConfig

class torchrl.trainers.algorithms.configs.modules.DreamerV3DiscreteActorConfig(_partial_: bool = False, in_features: int = '???', out_features: int = '???', depth: int = 3, num_cells: int = 1024, norm_eps: float = 0.0001, unimix: float = 0.01, in_keys: Any = None, action_key: Any = 'action', logits_key: Any = 'logits', log_prob_key: Any = 'action_log_prob', device: Any = None, _target_: str = 'torchrl.trainers.algorithms.configs.modules._make_dreamer_v3_discrete_actor')

Hydra configuration for DreamerV3DiscreteActor.

Examples

>>> import torch
>>> from hydra.utils import instantiate
>>> from tensordict import TensorDict
>>> from torchrl.trainers.algorithms.configs import DreamerV3DiscreteActorConfig
>>> actor = instantiate(DreamerV3DiscreteActorConfig(in_features=12, out_features=3))
>>> data = TensorDict({"state": torch.randn(4, 8), "belief": torch.randn(4, 4)}, [4])
>>> actor(data)["action"].shape
torch.Size([4, 3])