4d4da8d719d38094e9e73adb2ad7ccb60461a0f6,slm_lab/agent/algorithm/dqn.py,DQNBase,sample,#DQNBase#,110

Before Change

        return q_targets

    def sample(self):
        batches = [body.memory.sample(self.batch_size)
                   for body in self.agent.flat_nonan_body_a]
        batch = util.concat_dict(batches)
        util.to_torch_batch(batch)
        return batch

    def train(self):
        t = util.s_get(self, "aeb_space.clock").get("total_t")
        if (t > self.training_min_timestep and t % self.training_frequency == 0):

After Change

        return q_targets

    def sample(self):
        return super(DQNBase, self).sample()

    def train(self):
        return super(DQNBase, self).train()

Instances