Lava-DL, but with PyTorch-Lightning flavour

Last update: Oct 31, 2022

Related tags

Deep Learning lava-dl-lightning

Overview

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}
}

Lava-DL, but with PyTorch-Lightning flavour

Related tags

Overview

Deep learning project seed

Goals

DELETE EVERYTHING ABOVE FOR YOUR PROJECT

Your Project Name

Description

How to run

Imports

Citation

Owner

Sami BARCHID

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

A mini-course offered to Undergrad chemistry students

Fast Axiomatic Attribution for Neural Networks (NeurIPS*2021)

The official implementation of Variable-Length Piano Infilling (VLI).

Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

MaskTrackRCNN for video instance segmentation based on mmdetection

Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions

This is 2nd term discrete maths project done by UCU students that uses backtracking to solve various problems.

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.

Plotting points that lie on the intersection of the given curves using gradient descent.

MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

VGG16 model-based classification project about brain tumor detection.

Pseudo-rng-app - whos needs science to make a random number when you have pseudoscience?

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, and Trevor Darrell. CVPR 2015 and PAMI 2016.

Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"

Keras implementation of AdaBound

Colab notebook and additional materials for Python-driven analysis of redlining data in Philadelphia

Lava-DL, but with PyTorch-Lightning flavour

Related tags

Overview

Deep learning project seed

Goals

DELETE EVERYTHING ABOVE FOR YOUR PROJECT

Your Project Name

Description

How to run

Imports

Citation

Owner

Sami BARCHID

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

A mini-course offered to Undergrad chemistry students

Fast Axiomatic Attribution for Neural Networks (NeurIPS*2021)

The official implementation of Variable-Length Piano Infilling (VLI).

Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"

MaskTrackRCNN for video instance segmentation based on mmdetection

Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch

Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions

This is 2nd term discrete maths project done by UCU students that uses backtracking to solve various problems.

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.

Plotting points that lie on the intersection of the given curves using gradient descent.

MetaTTE: a Meta-Learning Based Travel Time Estimation Model for Multi-city Scenarios

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

VGG16 model-based classification project about brain tumor detection.

Pseudo-rng-app - whos needs science to make a random number when you have pseudoscience?

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.

Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective

Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"

Keras implementation of AdaBound

Colab notebook and additional materials for Python-driven analysis of redlining data in Philadelphia

Fully Convolutional Networks for Semantic Segmentation by Jonathan Long, Evan Shelhamer, and Trevor Darrell. CVPR 2015 and PAMI 2016.