The code of the paper MDMLP.
Thanks to TIMM library!
It's used in the same way as timm.
We use fvcore to measure params and flops.
We changed timm/data/dataset_factory.py to be able to train on Flowers102 and Food101.
# For cifar10
python3 train.py /path-to-cifar10 -c ymls/cifar10_sgd.yml --model mdmlp_patch4_lap2_dim64_depth8_32
# For cifar100
python3 train.py /path-to-cifar100 -c ymls/cifar100_sgd.yml --model mdmlp_patch4_lap2_dim64_depth8_32
# For Flowers102
python3 train.py /path-to-flowers102 -c ymls/flowers102_sgd.yml --model mdmlp_patch14_lap7_dim64_depth8_224
# For Food101
python3 train.py /path-to-food101 -c ymls/food101_sgd.yml --model mdmlp_patch14_lap7_dim64_depth8_224
# For MDAttnTool
python3 train.py /path-to-cifar10 -c ymls/cifar10_sgd.yml --model mdmlp_attn_32