Comments (5)
@syue0225, Did you change any variables? How many UAVs you have? Keep track of the X and Y Matrices, then see what are the shapes of variables and what values they have?
It is better to do it in debug mode.
from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.
The issue is in lines 145, 148, 151, and 154 of the file csi.py. The transpose operation to the second argument of np.multiply should not be there as it will produce an output with the wrong dimensions. I have checked and verified the results.
from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.
when i run it ,it have some problems File "E:/python_code/Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task-main/Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task-main/main.py", line 174, in csi_coef = get_csi(num_UAV, loc_dict, X_Mat[Step, Eps, :], Y_Mat[Step, Eps, :]) File "E:\python_code\Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task-main\Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task-main\csi.py", line 158, in get_csi csi_h[:, source_uav] = np.squeeze(h_S_uav) ValueError: could not broadcast input array from shape (2,2) into shape (2)
could you help me?
are you able to rectify the error, bcz i'm facing the same issure? plz help me
from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.
The issue is in lines 145, 148, 151, and 154 of the file csi.py. The transpose operation to the second argument of np.multiply should not be there as it will produce an output with the wrong dimensions. I have checked and verified the results.
hey can you help me? after removing transpose still getting the same error. does your code working?
from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.
Traceback (most recent call last):
File "E:/Reinforcement_Learning_Team_Q_learnig_MARL_Multi_Agent_UAV_Spectrum_task-main/main.py", line 272, in
next_state_index=next_state_index, task_diff=task_diff, qVal=qVal)
File "<array_function internals>", line 6, in savez
File "D:\Anaconda3\envs\python37\lib\site-packages\numpy\lib\npyio.py", line 618, in savez
_savez(file, args, kwds, False)
File "D:\Anaconda3\envs\python37\lib\site-packages\numpy\lib\npyio.py", line 715, in _savez
zipf = zipfile_factory(file, mode="w", compression=compression)
File "D:\Anaconda3\envs\python37\lib\site-packages\numpy\lib\npyio.py", line 112, in zipfile_factory
return zipfile.ZipFile(file, *args, **kwargs)
File "D:\Anaconda3\envs\python37\lib\zipfile.py", line 1240, in init
self.fp = io.open(file, filemode)
FileNotFoundError: [Errno 2] No such file or directory: '\data\Out_greedy_Size_10_Run_0_Eps_200_Step_30000.npz'
The file doesn't have Out_greedy_Size_10_Run_0_Eps_200_Step_30000.npz,so what's the problem?Can you help me?
from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.
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from reinforcement_learning_team_q_learnig_marl_multi_agent_uav_spectrum_task.