class_docstr: A dummy off-policy algorithm.
class_docstr_tok: ["A","dummy","off-policy","algorithm","."]
docstr: Perform one step of policy optimization given one batch of samples.
  
  Args:
      itr (int): Iteration number.
      paths (list[dict]): A list of collected paths.
docstr_tok: ["Perform","one","step","of","policy","optimization","given","one","batch","of","samples",".","Args",":","itr","(","int",")",":","Iteration","number",".","paths","(","list","[","dict","]",")",":","A","list","of","collected","paths","."]
code: def train_once(self, itr, paths):
      """Perform one step of policy optimization given one batch of samples.
  
      Args:
          itr (int): Iteration number.
          paths (list[dict]): A list of collected paths.
  
      """
  
imports: from garage.np.algos import RLAlgorithm
label_desc: Use image node_id 3 for calling the DummyOffPolicyAlgo obj's underlying member method code with example usage: obj.train_once(itr, paths) without return types