Run MVUE(1:2) for ResNet18

python vision.main.py --model resnet --dataset imagenet --dataset-dir <IMAGENET_DIR> -b 256  --model-config "{'depth':18,''sparseNeuralGrad': True}"

Run MVUE(1:2) for ResNet50

python vision.main.py --model resnet --dataset imagenet --dataset-dir <IMAGENET_DIR> -b 256  --model-config "{'depth':50,''sparseNeuralGrad': True}"


# In order to run the approx-MVUE(2:4) change in vision.models.modules.sparseAct.Conv2d_SparseNeuralGrad to N=2 and M=4


Run sparseAct for ResNet50

python vision.main.py --model resnet --dataset imagenet --dataset-dir <IMAGENET_DIR> -b 256  --model-config "{'depth':50,''sparseAct': True}"


Run weight_transpose with MVUE

export RANK=0
export WORLD_SIZE=8
python dynamic_TNM.src.train_imagenet.py --config config_resnet18_4by8_transpose.yaml



