examples/neural-archicture-search/run.sh

# ✅ Test:  Acc@1 70.092 Acc@5 89.314
torchrun --nproc_per_node=4 train.py\
    --data-path /home/cs/Documents/datasets/imagenet\
    --model resnet18 --output-dir resnet18 --weights ResNet18_Weights.IMAGENET1K_V1\
    --batch-size 128 --epochs 10 --lr 0.0004 --lr-step-size 2 --lr-gamma 0.5\
    --lr-warmup-method constant --lr-warmup-epochs 1 --lr-warmup-decay 0.\
    --apply-trp --trp-depths 3 3 3 --trp-planes 256 --trp-lambdas 0.4 0.2 0.1 --print-freq 100
# torchrun --nproc_per_node=4 train.py\
#     --data-path /home/cs/Documents/datasets/imagenet\
#     --model resnet18  --resume resnet18/model_3.pth --test-only

# ✅ Test:  Acc@1 73.900 Acc@5 91.536
torchrun --nproc_per_node=4 train.py\
    --data-path /home/cs/Documents/datasets/imagenet\
    --model resnet34 --output-dir resnet34 --weights ResNet34_Weights.IMAGENET1K_V1\
    --batch-size 96 --epochs 10 --lr 0.0004 --lr-step-size 2 --lr-gamma 0.5\
    --lr-warmup-method constant --lr-warmup-epochs 1 --lr-warmup-decay 0.\
    --apply-trp --trp-depths 2 2 2 --trp-planes 256 --trp-lambdas 0.4 0.2 0.1 --print-freq 100
# torchrun --nproc_per_node=4 train.py\
#     --data-path /home/cs/Documents/datasets/imagenet\
#     --model resnet34  --resume resnet34/model_8.pth --test-only


# ✅ Test:  Acc@1 76.896 Acc@5 93.136
torchrun --nproc_per_node=4 train.py\
    --data-path /home/cs/Documents/datasets/imagenet\
    --model resnet50 --output-dir resnet50 --weights ResNet50_Weights.IMAGENET1K_V1\
    --batch-size 64 --epochs 10 --lr 0.0004 --lr-step-size 2 --lr-gamma 0.5\
    --lr-warmup-method constant --lr-warmup-epochs 1 --lr-warmup-decay 0.\
    --apply-trp --trp-depths 1 1 1 --trp-planes 1024 --trp-lambdas 0.4 0.2 0.1 --print-freq 100
# torchrun --nproc_per_node=4 train.py\
#     --data-path /home/cs/Documents/datasets/imagenet\
#     --model resnet50  --resume resnet50/model_9.pth --test-only