Python Efficient-training Resources

Multi-Modal Self-Supervision using GDT and StiCa This is an official pytorch implementation of papers: Multi-modal Self-Supervision from Generalized D

State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f

MixFaceNets This is the official repository of the paper: MixFaceNets: Extremely Efficient Face Recognition Networks. (Accepted in IJCB2021) https://i

ViPNAS: Efficient Video Pose Estimation via Neural Architecture Search [paper] Introduction This is the official implementation of ViPNAS: Efficient V

DepthNet training on Still Box Project page This code can replicate the results of our paper that was published in UAVg-17. If you use this repo in yo

The DETR approach applies the transformer encoder and decoder architecture to object detection and achieves promising performance. In this paper, we handle the critical issue, slow training convergence, and present a conditional cross-attention mechanism for fast DETR training. Our approach is motivated by that the cross-attention in DETR relies highly on the content embeddings and that the spatial embeddings make minor contributions, increasing the need for high-quality content embeddings and thus increasing the training difficulty.

Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation This is a pytorch project for the paper Dynamic Divide-and-Conquer Ad

Nasdaq Cloud Data Service (NCDS) Nasdaq Cloud Data Service (NCDS) provides a modern and efficient method of delivery for realtime exchange data and ot

Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp

An Image Captioning codebase This is a codebase for image captioning research. It supports: Self critical training from Self-critical Sequence Trainin

This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.

What is this fork of Megatron-LM and Megatron-DeepSpeed This is a detached fork of https://github.com/microsoft/Megatron-DeepSpeed, which in itself is

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

Kaleido-BERT: Vision-Language Pre-training on Fashion Domain Mingchen Zhuge*, Dehong Gao*, Deng-Ping Fan#, Linbo Jin, Ben Chen, Haoming Zhou, Minghui

VisualGPT Our Paper VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning Main Architecture of Our VisualGPT Downloa

Updates (2020/06/21) Code of PVTv2 is released! PVTv2 largely improves PVTv1 and works better than Swin Transformer with ImageNet-1K pre-training. Pyr

LightSeq: A High Performance Library for Sequence Processing and Generation

A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.

Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien

ODE GAN (Prototype) in PyTorch Partial implementation of ODE-GAN technique from the paper Training Generative Adversarial Networks by Solving Ordinary

ManiSkill-Learn ManiSkill-Learn is a framework for training agents on SAPIEN Open-Source Manipulation Skill Challenge, a large-scale learning-from-dem

SemCo The official pytorch implementation of the paper All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training

Epistemic Neural Networks A library for uncertainty representation and training in neural networks. Introduction Many applications in deep learning re

Active Testing: Sample-Efficient Model Evaluation Hi, good to see you here! 👋 This is code for "Active Testing: Sample-Efficient Model Evaluation". P

Kunyu(坤舆) - More efficient corporate asset collection English | 中文文档 0x00 Introduce Tool introduction Kunyu (kunyu), whose name is taken from , is act

背景 安装教程 快速上手 （一）预训练模型 （二）机器翻译 （三）文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台，支持多种预训练方式，以及序列生成和自然语言理解任务。 安装教程 git clone git

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

MASS: Masked Sequence to Sequence Pre-training for Language Generation

In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel

Bottom-Up and Top-Down Attention for Visual Question Answering An efficient PyTorch implementation of the winning entry of the 2017 VQA Challenge. The

Efficient Neural Architecture Search (ENAS) in PyTorch PyTorch implementation of Efficient Neural Architecture Search via Parameters Sharing. ENAS red

Proximal Backpropagation Proximal Backpropagation (ProxProp) is a neural network training algorithm that takes implicit instead of explicit gradient s

Use this instead: https://github.com/facebookresearch/maskrcnn-benchmark A Pytorch Implementation of Detectron Example output of e2e_mask_rcnn-R-101-F

Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning

Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks (SDPoint) This repository contains the cod

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

Bridging Multi-Task Learning and Meta-Learning Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Trainin

LTP: Learned Token Pruning for Transformers Check our paper for more details. Installation We follow the same installation procedure as the original H

Deduplicating Training Data Makes Language Models Better This repository contains code to deduplicate language model datasets as descrbed in the paper

This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m

Triangle Multiplicative Module - Pytorch Implementation of the Triangle Multiplicative module, used in Alphafold2 as an efficient way to mix rows or c

ViTGAN: Training GANs with Vision Transformers A PyTorch implementation of ViTGAN based on paper ViTGAN: Training GANs with Vision Transformers. Refer

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

Parallelformers: An Efficient Model Parallelization Toolkit for Deployment

ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A

Self-training for Few-shot Transfer Across Extreme Task Differences (STARTUP) Introduction This repo contains the official implementation of the follo

The Power of Scale for Parameter-Efficient Prompt Tuning Implementation of soft embeddings from https://arxiv.org/abs/2104.08691v1 using Pytorch and H

Adam-NSCL This is a PyTorch implementation of Adam-NSCL algorithm for continual learning from our CVPR2021 (oral) paper: Title: Training Networks in N

Efficient Self-Supervised Vision Transformers (EsViT) PyTorch implementation for EsViT, built with two techniques: A multi-stage Transformer architect

StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking Datasets You can download datasets that have been pre-pr

Computationally Efficient Optimization of Plackett-Luce Ranking Models for Relevance and Fairness This repository contains the code used for the exper

neural waveshaping synthesis real-time neural audio synthesis in the waveform domain paper • website • colab • audio by Ben Hayes, Charalampos Saitis,

MidiBERT-Piano Authors: Yi-Hui (Sophia) Chou, I-Chun (Bronwin) Chen Introduction This is the official repository for the paper, MidiBERT-Piano: Large-

AlphaNet: Improved Training of Supernet with Alpha-Divergence This repository contains our PyTorch training code, evaluation code and pretrained model

LiDAR R-CNN: An Efficient and Universal 3D Object Detector Introduction This is the official code of LiDAR R-CNN: An Efficient and Universal 3D Object

Accelerate PyTorch models with ONNX Runtime

Решения и подсказки к тренировке по алгоритмам от Яндекса Что есть внутри Решения с подсказками и комментариями; рекомендую сначала смотреть md файл п

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

HyperPose is a library for building high-performance custom pose estimation applications.

Heterogeneous INteract and aggreGatE (GraphHINGE) This is a pytorch implementation of GraphHINGE model. This is the experiment code in the following w

Piotr: Pythonic IoT exploitation and Research Introduction to Piotr Piotr is an emulation helper for Qemu that provides a convenient way to create, sh

Chasing Sparsity in Vision Transformers: An End-to-End Exploration Codes for [Preprint] Chasing Sparsity in Vision Transformers: An End-to-End Explora

WAGMA-SGD is a decentralized asynchronous SGD based on wait-avoiding group model averaging. The synchronization is relaxed by making the collectives externally-triggerable, namely, a collective can be initiated without requiring that all the processes enter it. It partially reduces the data within non-overlapping groups of process, improving the parallel scalability.

Bagua is a flexible and performant distributed training algorithm development framework.

This software automatically sends you emails to notify you of the latest progress of your deep learning programs.

Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

Balancing Training for Multilingual Neural Machine Translation Implementation of the paper Balancing Training for Multilingual Neural Machine Translat

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch. 🔥

flax-sentence-embeddings This repository will be used to share code for the Flax / JAX community event to train sentence embeddings on 1B+ training pa

PLOME:Pre-training with Misspelled Knowledge for Chinese Spelling Correction (ACL2021) This repository provides the code and data of the work in ACL20

Data Efficient Stagewise Knowledge Distillation Table of Contents Data Efficient Stagewise Knowledge Distillation Table of Contents Requirements Image

KGI (Knowledge Graph Induction) for slot filling This is the code for our KILT leaderboard submission to the T-REx and zsRE tasks. It includes code fo

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

PGT Code for paper PGT: A Progressive Method for Training Models on Long Videos. Install Run pip install -r requirements.txt. Run python setup.py buil

TransFill-Reference-Inpainting This is the official repo for TransFill: Reference-guided Image Inpainting by Merging Multiple Color and Spatial Transf

PPLNN is a Primitive Library for Neural Network is a high-performance deep-learning inference engine for efficient AI inferencing

BoB: BERT Over BERT for Training Persona-based Dialogue Models from Limited Personalized Data This repository provides the implementation details for

seno-blockchain https://seno.uno Seno is just a fork of Chia, designed to be efficient, decentralized, and secure. Here are some of the features and b

Efficient implementation of YOLOV5 in TensorFlow2

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great importance. We propose a novel orthogonal over-parameterized training (OPT) framework that can provably minimize the hyperspherical energy which characterizes the diversity of neurons on a hypersphere. See our previous work -- MHE for an in-depth introduction.

ncnnqat ncnnqat is a quantize aware training package for NCNN on pytorch. Table of Contents ncnnqat Table of Contents Installation Usage Code Examples

TAP: Text-Aware Pre-training TAP: Text-Aware Pre-training for Text-VQA and Text-Caption by Zhengyuan Yang, Yijuan Lu, Jianfeng Wang, Xi Yin, Dinei Flo

DatasetGAN This is the official code and data release for: DatasetGAN: Efficient Labeled Data Factory with Minimal Human Effort Yuxuan Zhang*, Huan Li

NodePiece - Compositional and Parameter-Efficient Representations for Large Knowledge Graphs NodePiece is a "tokenizer" for reducing entity vocabulary

One Thing One Click One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation (CVPR2021) Code for the paper One Thi

UC2 UC2: Universal Cross-lingual Cross-modal Vision-and-Language Pre-training Mingyang Zhou, Luowei Zhou, Shuohang Wang, Yu Cheng, Linjie Li, Zhou Yu,

SelfText Beyond Polygon: Unconstrained Text Detection with Box Supervisionand Dynamic Self-Training Introduction This is a PyTorch implementation of "

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

AdamBNN This is the pytorch implementation of our paper "How Do Adam and Training Strategies Help BNNs Optimization?", published in ICML 2021. In this

We evaluated the baseline with Resnet50 and Efficienet-v2 without using pretrained models. Also Resnet50-IBN-A and Efficientnet-v2 using pretrained on ImageNet. We used two datasets: Market-1501 and CUHK03.

This is a release of our VIMPAC paper to illustrate the implementations. The pretrained checkpoints and scripts will be soon open-sourced in HuggingFace transformers.

Secure Distributed Training at Scale This repository contains the implementation of experiments from the paper "Secure Distributed Training at Scale"

DistML is a Ray extension library to support large-scale distributed ML training on heterogeneous multi-node multi-GPU clusters

ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation models. It contains 17 different amateur subjects performing 30 sports-related actions each, for a total of 510 action clips.

ASPset-510 ASPset-510 (Australian Sports Pose Dataset) is a large-scale video dataset for the training and evaluation of 3D human pose estimation mode

Pipeline For NLP with Bloom's Taxonomy Using Improved Question Classification and Question Generation using Deep Learning This repository contains all

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

SinIR (Official Implementation) Requirements To install requirements: pip install -r requirements.txt We used Python 3.7.4 and f-strings which are in