class_docstr: A dummy off-policy algorithm.
class_docstr_tok: ["A","dummy","off-policy","algorithm","."]
docstr: Obtain samplers and start actual training for each epoch.
  
  Args:
      trainer (Trainer): Trainer is passed to give algorithm
          the access to trainer.step_epochs(), which provides services
          such as snapshotting and sampler control.
docstr_tok: ["Obtain","samplers","and","start","actual","training","for","each","epoch",".","Args",":","trainer","(","Trainer",")",":","Trainer","is","passed","to","give","algorithm","the","access","to","trainer.step_epochs","(",")",",","which","provides","services","such","as","snapshotting","and","sampler","control","."]
code: def train(self, trainer):
      """Obtain samplers and start actual training for each epoch.
  
      Args:
          trainer (Trainer): Trainer is passed to give algorithm
              the access to trainer.step_epochs(), which provides services
              such as snapshotting and sampler control.
  
      """
  
imports: from garage.np.algos import RLAlgorithm
label_desc: Use image node_id 2 for calling the DummyOffPolicyAlgo obj's underlying member method code with example usage: obj.train(trainer) without return types