Deep learning project seed
Use this seed to start new deep learning / ML projects.
- Built in setup.py
- Built in requirements
- Examples with MNIST
- Badges
- Bibtex
Goals
The goal of this seed is to structure ML paper-code the same so that work can easily be extended and replicated.
DELETE EVERYTHING ABOVE FOR YOUR PROJECT
Description
What it does
How to run
Requires Python 3.8+. First, install dependencies
# clone project
git clone https://github.com/Barchid/lava-dl-lightning
cd lava-dl-lightning
# install lava
wget https://github.com/lava-nc/lava/releases/download/v0.2.0/lava-nc-0.2.0.tar.gz
pip install -U pip
pip install lava-nc-0.2.0.tar.gz
# install lava-dl
wget https://github.com/lava-nc/lava-dl/releases/download/v0.1.1/lava-dl-0.1.1.tar.gz
pip install lava-dl-0.1.1.tar.gz
# install pytorch-lightning
pip install pytorch-lightning torchmetrics
Next, navigate to any file and run it.
# module folder
cd project
# run module (example: mnist as your main contribution)
python lit_classifier_main.py
Imports
This project is setup as a package which means you can now easily import any file into any other file like so:
from project.datasets.mnist import mnist
from project.lit_classifier_main import LitClassifier
from pytorch_lightning import Trainer
# model
model = LitClassifier()
# data
train, val, test = mnist()
# train
trainer = Trainer()
trainer.fit(model, train, val)
# test using the best model!
trainer.test(test_dataloaders=test)
Citation
@article{YourName,
title={Your Title},
author={Your team},
journal={Location},
year={Year}
}