• Python 3.6
• numpy 1.14
• PyTorch 1.1
• torchvision 0.2

The following demo will show the results of the AISTATS 2023 paper "Order-preserving Complementary-Label Learning" with the Kuzushiji-MNIST dataset. When running the code, the test accuracy of each epoch will be printed for OP-W and OP. The results will have two columns: epoch number and test accuracy.

Before running demo.py, we can choose the type of method. If we run the following code:

python demo.py -me OP 

the method OP will be used or OP-W will be used in default.