Actor Modules

Actor modules represent policies in RL. They map observations to actions, either deterministically or stochastically.

TensorDictModules and SafeModules

Actor(*args, **kwargs)	General class for deterministic actors in RL.
MultiStepActorWrapper(*args, **kwargs)	A wrapper around a multi-action actor.
SafeModule(*args, **kwargs)	tensordict.nn.TensorDictModule subclass that accepts a TensorSpec as argument to control the output domain.
SafeSequential(*args, **kwargs)	A safe sequence of TensorDictModules.
TanhModule(*args, **kwargs)	A Tanh module for deterministic policies with bounded action space.

Probabilistic actors

ProbabilisticActor(*args, **kwargs)	General class for probabilistic actors in RL.
SafeProbabilisticModule(*args, **kwargs)	tensordict.nn.ProbabilisticTensorDictModule subclass that accepts a TensorSpec as an argument to control the output domain.
SafeProbabilisticTensorDictSequential(*args, ...)	tensordict.nn.ProbabilisticTensorDictSequential subclass that accepts a TensorSpec as argument to control the output domain.

Q-Value actors

QValueActor(*args, **kwargs)	A Q-Value actor class.
DistributionalQValueActor(*args, **kwargs)	A Distributional DQN actor class.
QValueModule(*args, **kwargs)	Q-Value TensorDictModule for Q-value policies.
DistributionalQValueModule(*args, **kwargs)	Distributional Q-Value hook for Q-value policies.