Python Efficient-training Resources

SALT: Stackelberg Adversarial Regularization Code for Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach, EMNLP 2021. R

Multi-Task Pre-Training for Plug-and-Play Task-Oriented Dialogue System Authors: Yixuan Su, Lei Shu, Elman Mansimov, Arshit Gupta, Deng Cai, Yi-An Lai

Discord Token Checker Simple yet efficient tool used to check and sort tokens in terms of there validation.When the program is done,go to the "output"

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles This project is for the paper: Detecting Errors and Estimating

IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-quality pre-trained models from torchvision, MMLabs, and soon Pytorch Image Models. It orchestrates the end-to-end deep learning workflow allowing to train networks with easy-to-use robust high-performance libraries such as Pytorch-Lightning and Fastai

EasyBuild is a software build and installation framework that allows you to manage (scientific) software on High Performance Computing (HPC) systems in an efficient way.

MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training.

Efficient matrix representations for working with tabular data

CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted

This is a library for training and applying sparse fine-tunings with torch and transformers. Please refer to our paper Composable Sparse Fine-Tuning f

ESRGAN (Enhanced SRGAN) [ 🚀 BasicSR] [Real-ESRGAN] ✨ New Updates. We have extended ESRGAN to Real-ESRGAN, which is a more practical algorithm for rea

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks This repository contains a TensorFlow implementation of "

A new codebase for popular Scene Graph Generation methods (2020). Visualization & Scene Graph Extraction on custom images/datasets are provided. It's also a PyTorch implementation of paper “Unbiased Scene Graph Generation from Biased Training CVPR 2020”

Improved Training of Wasserstein GANs Code for reproducing experiments in "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, Tensor

DeCLIP Supervision Exists Everywhere: A Data Efficient Contrastive Language-Image Pre-training Paradigm. Our paper is available in arxiv Updates ** Ou

Code for DetCon This repository contains code for the ICCV 2021 paper "Efficient Visual Pretraining with Contrastive Detection" by Olivier J. Hénaff,

What's New Sep 2021: We host a challenge in AAAI workshop: The 2nd Self-supervised Learning for Audio and Speech Processing! See SUPERB official site

Explaining in Style: Official TensorFlow Colab Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang, Yossi Gandelsman,

Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark (ICCV 2021) Kun Wang, Zhenyu Zhang, Zhiqiang Yan, X

Implementation of ICCV 2021 paper: PnP-DETR: Towards Efficient Visual Analysis with Transformers arxiv This repository is based on detr Recently, DETR

MosaicML Composer MosaicML Composer contains a library of methods, and ways to compose them together for more efficient ML training. We aim to ease th

Calibrate your listeners! Robust communication-based training for pragmatic speakers Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman Findings of

Unified-EPT Code for the ICCV 2021 Workshop paper: A Unified Efficient Pyramid Transformer for Semantic Segmentation. Installation Linux, CUDA=10.0,

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

Relation Prediction as an Auxiliary Training Objective for Knowledge Base Completion This repo provides the code for the paper Relation Prediction as

UniSpeech The family of UniSpeech: UniSpeech (ICML 2021): Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR UniSpeech-

Pre-training BERT Masked Language Models (MLM) This repository contains the method to pre-train a BERT model using custom vocabulary. It was used to p

AdaMML: Adaptive Multi-Modal Learning for Efficient Video Recognition [ArXiv] [Project Page] This repository is the official implementation of AdaMML:

Data Efficient Decision Making

Project Azua 0. Overview Many modern AI algorithms are known to be data-hungry, whereas human decision-making is much more efficient. The human can re

Unofficial PyTorch implementation of DeepMind's Perceiver IO with PyTorch Lightning scripts for distributed training

Sync Toolbox - Python package with reference implementations for efficient, robust, and accurate music synchronization based on dynamic time warping (DTW)

SCoRe: Pre-Training for Context Representation in Conversational Semantic Parsing This repository contains code for the ICLR 2021 paper "SCoRE: Pre-Tr

Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin

Why efficient Python? Because using Python more efficiently will make your code more readable and run more efficiently.

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)

multitask-learning-transformers A simple recipe for training and inferencing Transformer architecture for Multi-Task Learning on custom datasets. You

🧬 Training the car to do self-parking using a genetic algorithm

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

face.evoLVe: High-Performance Face Recognition Library based on PaddlePaddle & PyTorch Evolve to be more comprehensive, effective and efficient for fa

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas

NEATEST: Evolving Neural Networks Through Augmenting Topologies with Evolution Strategy Training

The first comprehensive Robustness investigation benchmark on large-scale dataset ImageNet regarding ARchitecture design and Training techniques towards diverse noises.

SimSwap-train Reimplement of SimSwap training code Instructions 1.Environment Preparation （1）Refer to the README document of SIMSWAP to configure the

PINTO_model_zoo Please read the contents of the LICENSE file located directly under each folder before using the model. My model conversion scripts ar

Convolutional networks using PyTorch This is a complete training example for Deep Convolutional Networks on various datasets (ImageNet, Cifar10, Cifar

pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm

An efficient 3D semantic segmentation framework for Urban-scale point clouds like SensatUrban, Campus3D, etc.

About subwAI subwAI - a project for training an AI to play the endless runner Subway Surfers using a supervised machine learning approach by imitation

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

GAN stability This repository contains the experiments in the supplementary material for the paper Which Training Methods for GANs do actually Converg

Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation, available for both PyTorch and Tensorflow.

Tevatron Tevatron is a simple and efficient toolkit for training and running dense retrievers with deep language models. The toolkit has a modularized

pytorch-fcn PyTorch implementation of Fully Convolutional Networks. Requirements pytorch = 0.2.0 torchvision = 0.1.8 fcn = 6.1.5 Pillow scipy tqdm

TextAttack 🐙 Generating adversarial examples for NLP models [TextAttack Documentation on ReadTheDocs] About • Setup • Usage • Design About TextAttack

A2T: Towards Improving Adversarial Training of NLP Models This is the source code for the EMNLP 2021 (Findings) paper "Towards Improving Adversarial T

EARL This repository provides a simple implementation of the work "Efficient Sparse Attacks on Videos using Reinforcement Learning" Example: Demo: Her

Rockpool Rockpool is a Python package for developing signal processing applications with spiking neural networks. Rockpool allows you to build network

Introduction SCRFD is an efficient high accuracy face detection approach which initially described in Arxiv. Performance Precision, flops and infer ti

TorchX TorchX: A PyTorch Extension Library for More Efficient Deep Learning. @misc{torchx, author = {Ansheng You and Changxu Wang}, title = {T

Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

SEW (Squeezed and Efficient Wav2vec) The repo contains the code of the paper "Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speec

The training code for the 4th place model at MDX 2021 leaderboard A.

FFRecord The FFRecord format is a simple format for storing a sequence of binary records developed by HFAiLab, which supports random access and Linux

InsGen - Data-Efficient Instance Generation from Instance Discrimination Data-Efficient Instance Generation from Instance Discrimination Ceyuan Yang,

ROSITA News & Updates (24/08/2021) Release the demo to perform fine-grained semantic alignments using the pretrained ROSITA model. (15/08/2021) Releas

Selene is a Python library and command line interface for training deep neural networks from biological sequence data such as genomes.

RoSTER The source code used for Distantly-Supervised Named Entity Recognition with Noise-Robust Learning and Language Model Augmented Self-Training, p

Real-ESRGAN Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data Ported from https://github.com/xinntao/Real-ESRGAN Depend

Pre-trained (foundation) models across tasks (understanding, generation and translation), languages (100+ languages), and modalities (language, image, audio, vision + language, audio + language, etc.)

Efficient Conformer: Progressive Downsampling and Grouped Attention for Automatic Speech Recognition Official implementation of the Efficient Conforme

近年来，图计算在搜索、推荐和风控等场景中获得显著的效果，但也面临超大规模异构图训练，与现有的深度学习框架Tensorflow和PyTorch结合等难题。 Galileo（伽利略）是一个图深度学习框架，具备超大规模、易使用、易扩展、高性能、双后端等优点，旨在解决超大规模图算法在工业级场景的落地难题，提

Transformer Captioning This repository contains the code for Transformer-based image captioning. Based on meshed-memory-transformer, we further optimi

The code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"

End-to-end neural table-text understanding models.

Efficient ML solutions for long-tailed demands.

Generate text line images for training deep learning OCR model (e.g. CRNN)

Model Training as a CI/CD System This project demonstrates the machine model training as a CI/CD system in GCP platform. You will see more detailed wo

COTREC Codes for CIKM'21 paper 'Self-Supervised Graph Co-Training for Session-based Recommendation'. Requirements: Python 3.7, Pytorch 1.6.0 Best Hype

Searching for Efficient Multi-Stage Vision Transformers This repository contains the official Pytorch implementation of "Searching for Efficient Multi

Lorien: A Unified Infrastructure for Efficient Deep Learning Workloads Delivery Lorien is an infrastructure to massively explore/benchmark the best sc

rl: An efficient framework for reinforcement learning Requirements Introduction PPO Test Requirements name version Python =3.7 numpy =1.19 torch =1

Aqueduct Framework for creating efficient data processing pipelines. Contact Feel free to ask questions in telegram t.me/avito-ml Key Features Increas

TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE

Megatron (1 and 2) is a large, powerful transformer developed by the Applied Deep Learning Research team at NVIDIA.

AdaFocus (ICCV 2021) This repo contains the official code and pre-trained models for AdaFocus. Adaptive Focus for Efficient Video Recognition Referenc

WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU

Train longer, generalize better - Big batch training This is a code repository used to generate the results appearing in "Train longer, generalize bet

FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra

forward-thinking-pytorch Pytorch implementation of Forward Thinking: Building and Training Neural Networks One Layer at a Time Requirements Python 2.7

PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based

efficient_densenet_pytorch A PyTorch =1.0 implementation of DenseNets, optimized to save GPU memory. Recent updates Now works on PyTorch 1.0! It uses

RevLib Simple and efficient RevNet-Library with DeepSpeed support Features Half the constant memory usage and faster than RevNet libraries Less memory

Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas

Pixel Difference Convolution This repository contains the PyTorch implementation for "Pixel Difference Networks for Efficient Edge Detection" by Zhuo

Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph

Flood Detection Challenge This repository contains code for our submission to the ETCI 2021 Competition on Flood Detection (Winning Solution #2). Acco

ST++ This is the official PyTorch implementation of our paper: ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation. Lihe Ya