ray.rllib.policy.policy.Policy.set_state#

Policy.set_state(state: Dict[str, numpy.array | jnp.ndarray | tf.Tensor | torch.Tensor | dict | tuple]) None[source]#

Restores the entire current state of this Policy from state.

Parameters:

state – The new state to set this policy to. Can be obtained by calling self.get_state().