garage.torch.policies.discrete_qf_argmax_policy
¶
A Discrete QFunction-derived policy.
This policy chooses the action that yields to the largest Q-value.
- class DiscreteQFArgmaxPolicy(qf, env_spec, name='DiscreteQFArgmaxPolicy')¶
Bases:
garage.torch.policies.policy.Policy
Policy that derives its actions from a learned Q function.
The action returned is the one that yields the highest Q value for a given state, as determined by the supplied Q function.
- Parameters
- forward(self, observations)¶
Get actions corresponding to a batch of observations.
- Parameters
observations (torch.Tensor) – Batch of observations of shape \((N, O)\). Observations should be flattened even if they are images as the underlying Q network handles unflattening.
- Returns
Batch of actions of shape \((N, A)\)
- Return type
torch.Tensor
- get_action(self, observation)¶
Get a single action given an observation.
- Parameters
observation (np.ndarray) – Observation with shape \((O, )\).
- Returns
Predicted action with shape \((A, )\). dict: Empty since this policy does not produce a distribution.
- Return type
torch.Tensor
- get_actions(self, observations)¶
Get actions given observations.
- Parameters
observations (np.ndarray) – Batch of observations, should have shape \((N, O)\).
- Returns
Predicted actions. Tensor has shape \((N, A)\). dict: Empty since this policy does not produce a distribution.
- Return type
torch.Tensor
- get_param_values(self)¶
Get the parameters to the policy.
This method is included to ensure consistency with TF policies.
- Returns
The parameters (in the form of the state dictionary).
- Return type
- set_param_values(self, state_dict)¶
Set the parameters to the policy.
This method is included to ensure consistency with TF policies.
- Parameters
state_dict (dict) – State dictionary.
- reset(self, do_resets=None)¶
Reset the policy.
This is effective only to recurrent policies.
do_resets is an array of boolean indicating which internal states to be reset. The length of do_resets should be equal to the length of inputs, i.e. batch size.
- Parameters
do_resets (numpy.ndarray) – Bool array indicating which states to be reset.
- property env_spec(self)¶
Policy environment specification.
- Returns
Environment specification.
- Return type
- property observation_space(self)¶
Observation space.
- Returns
The observation space of the environment.
- Return type
akro.Space
- property action_space(self)¶
Action space.
- Returns
The action space of the environment.
- Return type
akro.Space