ray.rllib.policy.Policy.get_state#

Policy.get_state() Dict[str, Union[numpy.array, tensorflow.python.framework.ops.Tensor, torch.Tensor, dict, tuple]][source]#

Returns the entire current state of this Policy.

Note: Not to be confused with an RNN model’s internal state. State includes the Model(s)’ weights, optimizer weights, the exploration component’s state, as well as global variables, such as sampling timesteps.

Returns

Serialized local state.