Random-Sampling-SNN

Requirements

pytorch==1.10.0+cu113

spikingjelly==0.0.0.0.12

networkx==3.1

timm==1.0.9

torchtoolbox==0.1.8.2

Training on ImageNet

python -m torch.distributed.launch --nproc_per_node=8 main.py --dataset IMAGENET --batch-size 16 --epochs 120 --T 4 --graph-model WS --skip-ratio 0.05 --data-path YOUR_DATA_PATH

Training on CIFAR-10

python -m torch.distributed.launch --nproc_per_node=1 main.py --dataset CIFAR-10 --graph-model BA --skip-ratio 0.05 --data-path YOUR_DATA_PATH

Training on CIFAR-100

python -m torch.distributed.launch --nproc_per_node=1 main.py --dataset CIFAR-100 --graph-model BA --skip-ratio 0.05 --data-path YOUR_DATA_PATH

Problems you may meet

If you get an output like follows: AttributeError: module 'numpy' has no attribute 'int'. np.int was a deprecated alias for the builtin int. To avoid this error in existing code, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information.

You can fix it by replace np.int by int.