Use this seed to start new deep learning / ML projects.
- Built in setup.py
- Built in requirements
- Examples with MNIST
- Badges
- Bibtex
The goal of this seed is to structure ML paper-code the same so that work can easily be extended and replicated.
What it does
First, install dependencies
# clone project
git clone https://github.com/YourGithubName/deep-learning-project-template
# install project
cd deep-learning-project-template
pip install -e .
pip install -r requirements.txt
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
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)
@article{YourName,
title={Your Title},
author={Your team},
journal={Location},
year={Year}
}