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spikformer

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ICLR 2023, Spikformer: When Spiking Neural Network Meets Transformer

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# Spikformer: When Spiking Neural Network Meets Transformer, [ICLR 2023](https://openreview.net/forum?id=frE4fUwz_h).
# Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket, [Arxiv](https://arxiv.org/abs/2401.02020).
The Spikformer V2 code will be released after it organized.
## Reference
If you find this repo useful, please consider citing:
```
@inproceedings{
zhou2023spikformer,
title={Spikformer: When Spiking Neural Network Meets Transformer },
author={Zhaokun Zhou and Yuesheng Zhu and Chao He and Yaowei Wang and Shuicheng YAN and Yonghong Tian and Li Yuan},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=frE4fUwz_h}
}
```
Our codes are based on the official imagenet example by PyTorch, pytorch-image-models by Ross Wightman and SpikingJelly by Wei Fang.

### Requirements
timm==0.5.4

cupy==10.3.1

pytorch==1.10.0+cu111

spikingjelly==0.0.0.0.12

pyyaml

data prepare: ImageNet with the following folder structure, you can extract imagenet by this [script](https://gist.github.com/BIGBALLON/8a71d225eff18d88e469e6ea9b39cef4).
```
│imagenet/
├──train/
│  ├── n01440764
│  │   ├── n01440764_10026.JPEG
│  │   ├── n01440764_10027.JPEG
│  │   ├── ......
│  ├── ......
├──val/
│  ├── n01440764
│  │   ├── ILSVRC2012_val_00000293.JPEG
│  │   ├── ILSVRC2012_val_00002138.JPEG
│  │   ├── ......
│  ├── ......
```

### Training  on ImageNet
Setting hyper-parameters in imagenet.yml

```
cd imagenet
python -m torch.distributed.launch --nproc_per_node=8 train.py
```

### Testing ImageNet Val data 
```
cd imagenet
python test.py
```

### Training  on cifar10
Setting hyper-parameters in cifar10.yml
```
cd cifar10
python train.py
```
### Training  on cifar10DVS
```
cd cifar10dvs
python train.py
```

spikformer

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