Open LinghaoChan opened 2 years ago
I just got 91.31 % top1 Accuracy on dataset 'CIFAR-10' (symmetric noise 0.2). Did you reproduce the author's experimental results in the original paper?
How much RAM is needed to run the codes of this article? (I use COLAB to run this code, but RAM crashes)
This is a good work. However, the training efficiency is somehow low~
In the training stage, the GPU utilization is about 50-60%. In the "pare-wise selection" stage, the GPU utilization is approximate 0.
At first, I think it is because the program executes the CPU operations in the "pare-wise selection" stage. I set up some checkpoints in the "pare-wise selection" stage, and find that most of the time was spent on "Weighted k-nn correction" (code link).
Looking forward to your suggestions for training efficiently~~~