class_docstr: Action taken is uniformly random.
  
  Args:
      env_spec (EnvSpec): Environment spec to explore.
docstr: Get actions from this policy for the input observation.
  
  Args:
      observations(list): Observations from the environment.
  
  Returns:
      np.ndarray: Actions with noise.
      List[dict]: Arbitrary policy state information (agent_info).
docstr_tok: ["Get","actions","from","this","policy","for","the","input","observation",".","Args",":","observations","(","list",")",":","Observations","from","the","environment",".","Returns",":","np.ndarray",":","Actions","with","noise",".","List","[","dict","]",":","Arbitrary","policy","state","information","(","agent_info",")","."]
code: def get_actions(self, observations):
      """Get actions from this policy for the input observation.
  
      Args:
          observations(list): Observations from the environment.
  
      Returns:
          np.ndarray: Actions with noise.
          List[dict]: Arbitrary policy state information (agent_info).
  
      """
      return [
          self._env_spec.action_space.sample() for obs in observations
      ], dict()
  
imports: import gym
  from garage.np.policies.policy import Policy
label_desc: Use image node_id 4 for calling the UniformRandomPolicy obj's underlying member method code with example usage: obj.get_actions(observations) and returns: unknown,  dict