run.sh

export CUDA_VISIBLE_DEVICES=0

# fine-tune the diffusion model
torchrun --nnode=1 --master_port=25678 train_dit.py --model DiT-XL/2 \
     --data-path /data/datasets/ImageNet/train/ --ckpt pretrained_models/DiT-XL-2-256x256.pt \
     --global-batch-size 8 --tag minimax --ckpt-every 12000 --log-every 1500 --epochs 8 \
     --condense --finetune-ipc -1 --results-dir ../logs/run-0 --spec woof

# run sample generation
python sample.py --model DiT-XL/2 --image-size 256 --ckpt ../logs/run-0/000-DiT-XL-2-minimax/checkpoints/0012000.pt \
    --save-dir ../results/dit-distillation/imagenet-10-1000-minimax --spec woof

# run validation
python train.py -d imagenet --imagenet_dir ../results/dit-distillation/imagenet-10-1000-minimax /data/datasets/ImageNet/ \
    -n resnet_ap --nclass 10 --norm_type instance --ipc 100 --tag test --slct_type random --spec woof