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
Your Project Name
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}
}
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