We just upload the sub-directory for the artifact evaluation. Feel free to go inside the sub-directory of artifact for more information!
We also provide the environment dependencies inside requirements.txt, generated by pipreqs.
To install the dependency: pip install -r requirements.txt
This repo intends to provide the source codes in PyTorch for fine-tuning and profiling the SNN models.
1a). Profiling the SNN models to examine the original ratio of silent neurons.
python3 model_profile.py -profile --n_mask 0
1b). Profiling the SNN models to examine the ratio of silent neurons by masking out all neurons that only spike for 1 time.
python3 model_profile.py -profile --n_mask 1
2). Finetuning the SNN models to recover the accuracy from masking out the neurons that only spike for 1 time.
python3 fine_tune.py --n_masks 1
Package version:
Python 3.9.7.
CUDA 11.1.
PyTorch 2.3.1 py3.9_cuda11.8_cudnn8.7.0_0
spikingjelly 0.0.0.0.12
More details to come soon.