class_docstr: An exploration strategy based on the Ornstein-Uhlenbeck process.
  
  The process is governed by the following stochastic differential equation.
  
  .. math::
     dx_t = -\theta(\mu - x_t)dt + \sigma \sqrt{dt} \mathcal{N}(\mathbb{0}, \mathbb{1})  # noqa: E501
  
  Args:
      env_spec (EnvSpec): Environment to explore.
      policy (garage.Policy): Policy to wrap.
      mu (float): :math:`\mu` parameter of this OU process. This is the drift
          component.
      sigma (float): :math:`\sigma > 0` parameter of this OU process. This is
          the coefficient for the Wiener process component. Must be greater
          than zero.
      theta (float): :math:`\theta > 0` parameter of this OU process. Must be
          greater than zero.
      dt (float): Time-step quantum :math:`dt > 0` of this OU process. Must
          be greater than zero.
      x0 (float): Initial state :math:`x_0` of this OU process.
docstr: Return actions with noise.
  
  Args:
      observations (np.ndarray): Observation from the environment.
  
  Returns:
      np.ndarray: Actions with noise.
      List[dict]: Arbitrary policy state information (agent_info).
code: def get_actions(self, observations):
      """Return actions with noise.
  
      Args:
          observations (np.ndarray): Observation from the environment.
  
      Returns:
          np.ndarray: Actions with noise.
          List[dict]: Arbitrary policy state information (agent_info).
  
      """
      actions, agent_infos = self.policy.get_actions(observations)
      ou_state = self._simulate()
      return (
          np.clip(
              actions + ou_state,
              self._action_space.low,
              self._action_space.high,
          ),
          agent_infos,
      )
  
file_path: garage/src/garage/np/exploration_policies/add_ornstein_uhlenbeck_noise.py
imports: import numpy
  from garage.np.exploration_policies.exploration_policy import ExplorationPolicy
label_desc: Use image node_id 5 for calling the AddOrnsteinUhlenbeckNoise obj's underlying member method code with example usage: obj.get_actions(observations) and returns: np,  agent_infos