Kernel Spike

Introduction

This project is for exploring using the kernel function as a alternative for exponantial function in computing the spike convolution, which is used to approximate the spike outputs. The algorithm is implemented in Pytorch and the configuration is in YAML, managed by Hydra.

TODO

• Implement the kernel-weight metho
• Implement the kernel-attention method
• Implement the ... undergoing method

Usage

To run the code, you need to install the dependencies first:

pip install -r requirements.txt

Then, you can run the code with the following command for training the model:

python train.py

To test the model, you can run the following command:

python test.py

The configuration is in config folder, you can change the configuration by modifying the file or using command line arguments. For example, to change the learning rate, you can run the following command:

python train.py trainer.lr=0.01

or directly change the lr in config/trainer.yaml file. For more information about the configuration, please refer to the Hydra documentation.