garage.torch.policies.deterministic_mlp_policy
¶
This modules creates a deterministic policy network.
A neural network can be used as policy method in different RL algorithms. It accepts an observation of the environment and predicts an action.
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class
DeterministicMLPPolicy
(env_spec, name='DeterministicMLPPolicy', **kwargs)¶ Bases:
garage.torch.policies.policy.Policy
Implements a deterministic policy network.
The policy network selects action based on the state of the environment. It uses a PyTorch neural network module to fit the function of pi(s).
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forward
(self, observations)¶ Compute actions from the observations.
- Parameters
observations (torch.Tensor) – Batch of observations on default torch device.
- Returns
Batch of actions.
- Return type
torch.Tensor
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get_action
(self, observation)¶ Get a single action given an observation.
- Parameters
observation (np.ndarray) – Observation from the environment.
- Returns
np.ndarray: Predicted action.
- dict:
np.ndarray[float]: Mean of the distribution
- np.ndarray[float]: Log of standard deviation of the
distribution
- Return type
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get_actions
(self, observations)¶ Get actions given observations.
- Parameters
observations (np.ndarray) – Observations from the environment.
- Returns
np.ndarray: Predicted actions.
- dict:
np.ndarray[float]: Mean of the distribution
- np.ndarray[float]: Log of standard deviation of the
distribution
- Return type
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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
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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.
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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.
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property
env_spec
(self)¶ Policy environment specification.
- Returns
Environment specification.
- Return type
garage.EnvSpec
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property
observation_space
(self)¶ Observation space.
- Returns
The observation space of the environment.
- Return type
akro.Space
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property
action_space
(self)¶ Action space.
- Returns
The action space of the environment.
- Return type
akro.Space
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