<jupyter_start><jupyter_text>Save weights<jupyter_code>folders = ["400_300_chunk_actor_1e-4_critic_1e-4_batch_128",
          "double_400_300_chunk_actor_1e-4_critic_1e-4_batch_128"]
labels = ["DDPG", "Double DDPG"]
train_time = "last"
mean_scores, scores, actor_dicts, critic_dicts = load_folders(folders, train_time=train_time)

torch.save(actor_dicts[0], "checkpoint_actor_DDPG.pth")
torch.save(critic_dicts[0], "checkpoint_critic_DDPG.pth")
torch.save(actor_dicts[1], "checkpoint_actor_Double_DDPG.pth")
torch.save(critic_dicts[1], "checkpoint_critic_Double_DDPG.pth")
(570 - 359) / 570<jupyter_output><empty_output>
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{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '21839', 'license': 'MIT', 'n_tokens_mistral': 285, 'n_tokens_neox': 272, 'n_words': 27, 'path': 'Report_Helper.ipynb', 'repo_name': 'mirceast/continuous-control', 'size': '620'}