The problem about the fine-tuning of meta strategy

[zhenzhenzhizhi]

Hello, the author, I want to ask a question about the training of the thesis of distractor. The second step of the meta strategy is to fine tune the teacher tracker. According to your tutorial, I put the “*. pth” file from the/log folder to a new folder, and then put the "nest. pth "file in another folder. Then use the command you give to train:
python main.py --model simple-pos-act-lstm --tracker none --env UnrealTrackMulti-FlexibleRoomAdv-DiscreteColor-v1 --env-base UnrealTrackMulti-FlexibleRoomAdv-DiscreteColor-v1 --rnn-out 128 --seed 4 --seed-test 2 --train-mode 0 --norm-reward --aux attack-reward --lr 0.0005 --gpu-id 1 --old ./old_oppent --load-model-dir ./new_model/new-201.pth
But it didn't produce any results. I don't know what's wrong.

[zhenzhenzhizhi]

@zfw1226

[zfw1226]

Can you report the logs of your terminal after exiting (ctrl +c) the process?

Note that this issue is about the active_tracking_rl repo, it would be better to report this issue in that repo.

[zhenzhenzhizhi]

Can you report the logs of your terminal after exiting (ctrl +c) the process?

Note that this issue is about the active_tracking_rl repo, it would be better to report this issue in that repo.

Sorry, I will report this problem in the repo in active tracking.