Why training ends at epoch 50?

[yuxudong20]

Hello, I have tried to reproduce ATAC's results in the paper. However, when I run the official codes, the experiment automatically ends at epoch 50. I cannot find where the problem is? Could you give me some help?
For example, I have run 'python scripts/main.py -e hopper-medium-expert-v2 --gpu_id 0 --seed 15'. Are there any other hyperparameters that need to be given?
@chinganc

[chinganc]

Hi @yuxudong20, there was pytorch bug created in our refactoring which causes errors when using gpu. It's fixed now. Can you please give it a try? Thanks.

[yuxudong20]

Hi, @chinganc, thanks a lot. It seems that current codes can run 3000 epochs. However, the learning curves suddenly fall down, as in the following figure. Is this correct?

[yuxudong20]

And the amplification shows that it falls down at epoch 50.

[chinganc]

This is normal: Currently, it by default uses 50 epochs to do warmstart, which is just BC for the policy, and then ATAC starts. The drop you see there is the first epoch of ATAC.