Pytorch Lightning code guideline for conferences

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

Paper Conference Conference Conference

CI testing

Description

What it does

How to run

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    

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}
}
Owner
Pytorch Lightning
Pytorch Lightning
KUIELAB-MDX-Net got the 2nd place on the Leaderboard A and the 3rd place on the Leaderboard B in the MDX-Challenge ISMIR 2021

KUIELAB-MDX-Net got the 2nd place on the Leaderboard A and the 3rd place on the Leaderboard B in the MDX-Challenge ISMIR 2021

IELab@ Korea University 74 Dec 28, 2022
Official PyTorch implementation of SyntaSpeech (IJCAI 2022)

SyntaSpeech: Syntax-Aware Generative Adversarial Text-to-Speech | | | | 中文文档 This repository is the official PyTorch implementation of our IJCAI-2022

Zhenhui YE 116 Nov 24, 2022
This repository contains the segmentation user interface from the OpenSurfaces project, extracted as a lightweight tool

OpenSurfaces Segmentation UI This repository contains the segmentation user interface from the OpenSurfaces project, extracted as a lightweight tool.

Sean Bell 66 Jul 11, 2022
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)

Unsupervised Depth Completion with Calibrated Backprojection Layers PyTorch implementation of Unsupervised Depth Completion with Calibrated Backprojec

80 Dec 13, 2022
A task Provided by A respective Artenal Ai and Ml based Company to complete it

A task Provided by A respective Alternal Ai and Ml based Company to complete it .

Parth Madan 1 Jan 25, 2022
EvoJAX is a scalable, general purpose, hardware-accelerated neuroevolution toolkit

EvoJAX: Hardware-Accelerated Neuroevolution EvoJAX is a scalable, general purpose, hardware-accelerated neuroevolution toolkit. Built on top of the JA

Google 598 Jan 07, 2023
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

Wei Jin 85 Oct 13, 2022
Official PyTorch implementation of the paper "TEMOS: Generating diverse human motions from textual descriptions"

TEMOS: TExt to MOtionS Generating diverse human motions from textual descriptions Description Official PyTorch implementation of the paper "TEMOS: Gen

Mathis Petrovich 187 Dec 27, 2022
A python library for highly configurable transformers - easing model architecture search and experimentation.

A python library for highly configurable transformers - easing model architecture search and experimentation.

Anthony Fuller 51 Nov 20, 2022
Repository for the paper "Online Domain Adaptation for Occupancy Mapping", RSS 2020

RSS 2020 - Online Domain Adaptation for Occupancy Mapping Repository for the paper "Online Domain Adaptation for Occupancy Mapping", Robotics: Science

Anthony 26 Sep 22, 2022
MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings

offline-MBPO This repository contains the code of a version of model-based RL algorithm MBPO, which is modified to perform in offline RL settings Pape

LxzGordon 1 Oct 24, 2021
[ICCV 2021] Official Tensorflow Implementation for "Single Image Defocus Deblurring Using Kernel-Sharing Parallel Atrous Convolutions"

KPAC: Kernel-Sharing Parallel Atrous Convolutional block This repository contains the official Tensorflow implementation of the following paper: Singl

Hyeongseok Son 50 Dec 29, 2022
HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records

HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro

Hanyang Liu 4 Aug 08, 2022
Neural implicit reconstruction experiments for the Vector Neuron paper

Neural Implicit Reconstruction with Vector Neurons This repository contains code for the neural implicit reconstruction experiments in the paper Vecto

Congyue Deng 35 Jan 02, 2023
Hi Guys, here I am providing examples, which will help you in Lerarning Python

LearningPython Hi guys, here I am trying to include as many practice examples of Python Language, as i Myself learn, and hope these will help you in t

4 Feb 03, 2022
An image classification app boilerplate to serve your deep learning models asap!

Image 🖼 Classification App Boilerplate Have you been puzzled by tons of videos, blogs and other resources on the internet and don't know where and ho

Smaranjit Ghose 27 Oct 06, 2022
Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet)

Hierarchical Cross-modal Talking Face Generation with Dynamic Pixel-wise Loss (ATVGnet) By Lele Chen , Ross K Maddox, Zhiyao Duan, Chenliang Xu. Unive

Lele Chen 218 Dec 27, 2022
Fastshap: A fast, approximate shap kernel

fastshap: A fast, approximate shap kernel fastshap was designed to be: Fast Calculating shap values can take an extremely long time. fastshap utilizes

Samuel Wilson 22 Sep 24, 2022
A tutorial on training a DarkNet YOLOv4 model for the CrowdHuman dataset

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c

JK Jung 118 Nov 10, 2022
Hypernetwork-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels

Hypernet-Ensemble Learning of Segmentation Probability for Medical Image Segmentation with Ambiguous Labels The implementation of Hypernet-Ensemble Le

Sungmin Hong 6 Jul 18, 2022