e70bdb2d089ae283781c45b8d97963823a984baa,ch10/00_pong_pg.py,,,#,51

Before Change

    batch_states, batch_actions, batch_scales = [], [], []
    m_baseline, m_batch_scales, m_loss_entropy, m_loss_policy, m_loss_total = [], [], [], [], []
    m_grad_max, m_grad_mean = [], []
    sum_reward = 0.0

    with common.RewardTracker(writer, stop_reward=18) as tracker:
        for step_idx, exp in enumerate(exp_source):

After Change

            writer.add_scalar("loss_policy", loss_policy_v.data.cpu().numpy()[0], step_idx)
            writer.add_scalar("loss_total", loss_v.data.cpu().numpy()[0], step_idx)

            writer.add_scalar("grad_l2", np.sqrt(np.mean(np.square(grads))), step_idx)
            writer.add_scalar("grad_max", np.max(np.abs(grads)), step_idx)
            writer.add_scalar("grad_var", np.var(grads), step_idx)

            batch_states.clear()

Instances