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}
}
14 Sep 13, 2022
86 Dec 31, 2022
12 Oct 21, 2022
281 Dec 31, 2022
42 Dec 05, 2022
29 Nov 18, 2022
140 Dec 30, 2022
123 Oct 07, 2022
9 Nov 28, 2022
883 Jan 07, 2023
24 Oct 22, 2022
23 Jan 25, 2022
6 Dec 29, 2021
2 Aug 28, 2022
27 Nov 22, 2022
223 Jan 04, 2023
840 Jan 03, 2023
8 Jan 22, 2022
278 Dec 25, 2022
27 Dec 10, 2022