8 lines
1.0 KiB
Plaintext
8 lines
1.0 KiB
Plaintext
[2025-10-11 22:09:33,607][__main__][INFO] - Training for 50000 timesteps with NormalQNetwork and NormalReplayBuffer
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[2025-10-11 22:09:33,902][py.warnings][WARNING] - d:\Documents\Nextcloud\Documents\Project WUSTL\Academic\2025_Fall\CSE5100\Homeworks\hw2\hw2\agent.py:55: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).
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max_tensor = torch.max(self.target_net(torch.tensor(next_state).to(self.device)).cpu(), dim=1)
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[2025-10-11 22:09:33,932][py.warnings][WARNING] - d:\Documents\Nextcloud\Documents\Project WUSTL\Academic\2025_Fall\CSE5100\Homeworks\hw2\hw2\agent.py:57: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.detach().clone() or sourceTensor.detach().clone().requires_grad_(True), rather than torch.tensor(sourceTensor).
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tensor_arr = np.where(done, torch.tensor(reward).to(self.device), torch.tensor(reward).to(self.device) + max_tensor * gamma_tensor)
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