The required packages are as follows:
- python 3.5
- torch 1.2
- torchvision 0.4
- CUDA 10.0
- scikit-learn 0.22
Please download datasets to ./data and rename the file. Or you may modify the data path in main.py.
Please download
the CSI pretrained model provided
by CSI and save it as ./checkpoint/cifar10_labeled.model. You can also train your
own model with CSI's code for other settings.
Also, you need to pretrain a CVAE model with CIFAR10 training data according to CMG stage 1, and save the checkpoint
as ./checkpoint/cvae_10class.pkl.
To perform CMG tuning on CSI models and get the final result on CIFAR10 (OOD Detection on different datasets), run this command:
python -m main \
--device {the available GPU in your cluser, e.g., cuda:0} \
--params-dict-name './checkpoint/cifar10_labled.model' \
--params-dict-name2 './checkpoint/cvae_10class.pkl'