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| def estimate_advantages(states, last_state, rewards): | |
| values = critic(states) | |
| last_value = critic(last_state.unsqueeze(0)) | |
| next_values = torch.zeros_like(rewards) | |
| for i in reversed(range(rewards.shape[0])): | |
| last_value = next_values[i] = rewards[i] + 0.99 * last_value | |
| advantages = next_values - values | |
| return advantages |
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