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Runtime error
Runtime error
| Setting up Training Environment... | |
| Creating Liquid PPO Agent... | |
| Using cpu device | |
| Wrapping the env with a `Monitor` wrapper | |
| Wrapping the env in a DummyVecEnv. | |
| Starting Training (This may take a while)... | |
| ---------------------------------- | |
| | rollout/ | | | |
| | ep_len_mean | 1e+03 | | |
| | ep_rew_mean | -2.12e+04 | | |
| | time/ | | | |
| | fps | 464 | | |
| | iterations | 1 | | |
| | time_elapsed | 4 | | |
| | total_timesteps | 2048 | | |
| ---------------------------------- | |
| Traceback (most recent call last): | |
| File "/home/ylop/Documents/drone go brr/Drone-go-brrrrr/Drone-go-brrrrr/train.py", line 35, in <module> | |
| train() | |
| ~~~~~^^ | |
| File "/home/ylop/Documents/drone go brr/Drone-go-brrrrr/Drone-go-brrrrr/train.py", line 28, in train | |
| model.learn(total_timesteps=total_timesteps, callback=checkpoint_callback) | |
| ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/stable_baselines3/ppo/ppo.py", line 311, in learn | |
| return super().learn( | |
| ~~~~~~~~~~~~~^ | |
| total_timesteps=total_timesteps, | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| ...<4 lines>... | |
| progress_bar=progress_bar, | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| ) | |
| ^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/stable_baselines3/common/on_policy_algorithm.py", line 337, in learn | |
| self.train() | |
| ~~~~~~~~~~^^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/stable_baselines3/ppo/ppo.py", line 275, in train | |
| loss.backward() | |
| ~~~~~~~~~~~~~^^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/torch/_tensor.py", line 625, in backward | |
| torch.autograd.backward( | |
| ~~~~~~~~~~~~~~~~~~~~~~~^ | |
| self, gradient, retain_graph, create_graph, inputs=inputs | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| ) | |
| ^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/torch/autograd/__init__.py", line 354, in backward | |
| _engine_run_backward( | |
| ~~~~~~~~~~~~~~~~~~~~^ | |
| tensors, | |
| ^^^^^^^^ | |
| ...<5 lines>... | |
| accumulate_grad=True, | |
| ^^^^^^^^^^^^^^^^^^^^^ | |
| ) | |
| ^ | |
| File "/home/ylop/.local/lib/python3.14/site-packages/torch/autograd/graph.py", line 841, in _engine_run_backward | |
| return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass | |
| ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| t_outputs, *args, **kwargs | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| ) # Calls into the C++ engine to run the backward pass | |
| ^ | |
| RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed). Saved intermediate values of the graph are freed when you call .backward() or autograd.grad(). Specify retain_graph=True if you need to backward through the graph a second time or if you need to access saved tensors after calling backward. | |