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I change the env_name to simple_adversary, then I got the problem below:
Traceback (most recent call last):
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 149, in
runner.run()
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 54, in run
self.evaluate_policy() # Evaluate the policy every 'evaluate_freq' steps
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 70, in evaluate_policy
episode_reward, _ = self.run_episode_mpe(evaluate=True)
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 90, in run_episode_mpe
a_n, a_logprob_n = self.agent_n.choose_action(obs_n, evaluate=evaluate) # Get actions and the corresponding log probabilities of N agents
File "D:\WorkSpace\PycharmWorkSpaces\MARL-code-pytorch-main\MARL-code-pytorch-main\1.MAPPO_MPE\mappo_mpe.py", line 163, in choose_action
obs_n = torch.tensor(obs_n, dtype=torch.float32) # obs_n.shape=(N,obs_dim)
ValueError: expected sequence of length 8 at dim 1 (got 10)
The text was updated successfully, but these errors were encountered:
I change the env_name to simple_adversary, then I got the problem below:
Traceback (most recent call last):
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 149, in
runner.run()
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 54, in run
self.evaluate_policy() # Evaluate the policy every 'evaluate_freq' steps
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 70, in evaluate_policy
episode_reward, _ = self.run_episode_mpe(evaluate=True)
File "D:/WorkSpace/PycharmWorkSpaces/MARL-code-pytorch-main/MARL-code-pytorch-main/1.MAPPO_MPE/MAPPO_MPE_main.py", line 90, in run_episode_mpe
a_n, a_logprob_n = self.agent_n.choose_action(obs_n, evaluate=evaluate) # Get actions and the corresponding log probabilities of N agents
File "D:\WorkSpace\PycharmWorkSpaces\MARL-code-pytorch-main\MARL-code-pytorch-main\1.MAPPO_MPE\mappo_mpe.py", line 163, in choose_action
obs_n = torch.tensor(obs_n, dtype=torch.float32) # obs_n.shape=(N,obs_dim)
ValueError: expected sequence of length 8 at dim 1 (got 10)
The text was updated successfully, but these errors were encountered: