class_docstr: Dummy Recurrent Policy.
  
  Args:
      env_spec (garage.envs.env_spec.EnvSpec): Environment specification.
docstr: Get single action from this policy for the input observation.
  
  Args:
      observation (numpy.ndarray): Observation from environment.
  
  Returns:
      numpy.ndarray: Predicted action.
      dict: Distribution parameters. Empty because no distribution is
          used.
docstr_tok: ["Get","single","action","from","this","policy","for","the","input","observation",".","Args",":","observation","(","numpy.ndarray",")",":","Observation","from","environment",".","Returns",":","numpy.ndarray",":","Predicted","action",".","dict",":","Distribution","parameters",".","Empty","because","no","distribution","is","used","."]
code: 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: Predicted action.
          dict: Distribution parameters. Empty because no distribution is
              used.
  
      """
      return self.action_space.sample(), dict()
  
imports: import numpy
  from garage.np.policies import Policy
label_desc: Use image node_id 2 for calling the DummyRecurrentPolicy obj's underlying member method code with example usage: obj.get_action(observation) and returns: self,  dict