run_sample.sh

pip install -e .
# pip uninstall -y timm
# pip install mpi4py timm diffusers
MODEL_PATH=output_mdt_xl2/mdt_xl2_v1_ckpt.pt
export OPENAI_LOGDIR=output_mdt_xl2_eval
NUM_GPUS=8

echo 'CFG Class-conditional sampling:'
MODEL_FLAGS="--image_size 256 --model MDT_XL_2 --decode_layer 2"
DIFFUSION_FLAGS="--num_sampling_steps 250 --num_samples 50000  --cfg_cond True"
echo $MODEL_FLAGS
echo $DIFFUSION_FLAGS
echo $MODEL_PATH
python -m torch.distributed.launch --nproc_per_node=$NUM_GPUS scripts/image_sample.py --model_path $MODEL_PATH $MODEL_FLAGS $DIFFUSION_FLAGS
echo $MODEL_FLAGS
echo $DIFFUSION_FLAGS
echo $MODEL_PATH
python evaluations/evaluator.py ../dataeval/VIRTUAL_imagenet256_labeled.npz $OPENAI_LOGDIR/samples_50000x256x256x3.npz

echo 'Class-conditional sampling:'
MODEL_FLAGS="--image_size 256 --model MDT_XL_2 --decode_layer 2"
DIFFUSION_FLAGS="--num_sampling_steps 250 --num_samples 50000"
echo $MODEL_FLAGS
echo $DIFFUSION_FLAGS
echo $MODEL_PATH
python -m torch.distributed.launch --nproc_per_node=$NUM_GPUS scripts/image_sample.py --model_path $MODEL_PATH $MODEL_FLAGS $DIFFUSION_FLAGS
echo $MODEL_FLAGS
echo $DIFFUSION_FLAGS
echo $MODEL_PATH
python evaluations/evaluator.py ../dataeval/VIRTUAL_imagenet256_labeled.npz $OPENAI_LOGDIR/samples_50000x256x256x3.npz