conda create -p ./venv python=3.7
conda activate ./venv
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch  # install pytorch 1.6.0
pip install deepclustering2-2.0.0-py3-none-any.whl
python setup.py install  
# all packages should be set properly automatically.

cd semi_seg
# our proposed method
python main.py  Data.labeled_data_ratio=0.05  Data.unlabeled_data_ratio=0.95  Trainer.num_batches=300  Trainer.max_epoch=100  Data.name=acdc  Arch.num_classes=4  Optim.lr=0.0000001000 Trainer.name=udaiic Trainer.save_dir=udaiic/10.0_0.1  IICRegParameters.weight=0.1 UDARegCriterion.weight=10.0 
# ps baseline (lower bound)
python main.py  Data.labeled_data_ratio=0.05  Data.unlabeled_data_ratio=0.95  Trainer.num_batches=300  Trainer.max_epoch=100  Data.name=acdc  Arch.num_classes=4  Optim.lr=0.0000001000 Trainer.name=partial Trainer.save_dir=ps  
# fs baseline (upper bound)
python main.py  Data.labeled_data_ratio=1.0  Data.unlabeled_data_ratio=0.0  Trainer.num_batches=300  Trainer.max_epoch=100  Data.name=acdc  Arch.num_classes=4  Optim.lr=0.0000001000 Trainer.name=partial Trainer.save_dir=fs