code: def discount_rewards(r):
      
      discounted_r = np.zeros_like(r)
      running_add = 0
      for t in reversed(range(0, r.size)):
          # Reset the sum, since this was a game boundary (pong specific!).
          if r[t] != 0:
              running_add = 0
          running_add = running_add * gamma + r[t]
          discounted_r[t] = running_add
      return discounted_r
docs: take 1D float array of rewards and compute discounted reward