class_docstr: Policy that performs a fixed sequence of actions.
  
  Args:
      env_spec (garage.envs.env_spec.EnvSpec): Environment specification.
      scripted_actions (list[np.ndarray] or np.ndarray): Sequence of actions
          to perform.
      agent_infos (list[dict[str, np.ndarray]] or None): Sequence of
          agent_infos to produce.
class_docstr_tok: ["Policy","that","performs","a","fixed","sequence","of","actions",".","Args",":","env_spec","(","garage.envs.env_spec.EnvSpec",")",":","Environment","specification",".","scripted_actions","(","list","[","np.ndarray","]","or","np.ndarray",")",":","Sequence","of","actions","to","perform",".","agent_infos","(","list","[","dict","[","str",",","np.ndarray","]","]","or","None",")",":","Sequence","of","agent_infos","to","produce","."]
docstr: Get next action.
  
  Args:
      observations (np.ndarray): Ignored.
  
  Raises:
      ValueError: If observations has length greater than 1.
  
  Returns:
      tuple[np.ndarray, dict[str, np.ndarray]]: The action and agent_info
          for this time step.
docstr_tok: ["Get","next","action",".","Args",":","observations","(","np.ndarray",")",":","Ignored",".","Raises",":","ValueError",":","If","observations","has","length","greater","than","1",".","Returns",":","tuple","[","np.ndarray",",","dict","[","str",",","np.ndarray","]","]",":","The","action","and","agent_info","for","this","time","step","."]
code: def get_actions(self, observations):
      """Get next action.
  
      Args:
          observations (np.ndarray): Ignored.
  
      Raises:
          ValueError: If observations has length greater than 1.
  
      Returns:
          tuple[np.ndarray, dict[str, np.ndarray]]: The action and agent_info
              for this time step.
  
      """
      if len(observations) != 1:
          raise ValueError(
              "FixedPolicy does not support more than one "
              "observation at a time."
          )
      action, agent_info = self.get_action(observations[0])
      return np.array([action]), {
          k: np.array([v]) for (k, v) in agent_info.items()
      }
  
file_path: garage/src/garage/np/policies/fixed_policy.py
imports: import numpy
  from garage.np.policies.policy import Policy
label_desc: Use image node_id 6 for calling the FixedPolicy obj's underlying member method code with example usage: obj.get_actions(observations) and returns: np,  unknown