Source code for garage.tf.policies.uniform_control_policy
"""Uniform control policy."""
from garage.tf.policies.policy import Policy
[docs]class UniformControlPolicy(Policy):
"""Policy that output random action uniformly.
Args:
env_spec (garage.envs.env_spec.EnvSpec): Environment specification.
"""
def __init__(
self,
env_spec,
):
super().__init__(env_spec=env_spec)
@property
def vectorized(self):
"""Vectorized or not.
Returns:
Bool: True if primitive supports vectorized operations.
"""
return True
[docs] def get_action(self, observation):
"""Get single action from this policy for the input observation.
Args:
observation (numpy.ndarray): Observation from environment.
Returns:
numpy.ndarray: Action
dict: Predicted action and agent information. It returns an empty
dict since there is no parameterization.
"""
return self.action_space.sample(), dict()
[docs] def get_actions(self, observations):
"""Get multiple actions from this policy for the input observations.
Args:
observations (numpy.ndarray): Observations from environment.
Returns:
numpy.ndarray: Actions
dict: Predicted action and agent information. It returns an empty
dict since there is no parameterization.
"""
return self.action_space.sample_n(len(observations)), dict()