Python Large-scale-optimization Resources

MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J

This open source Python library provide several solvers for optimization problems related to Optimal Transport for signal, image processing and machine learning.

pyroSAR A Python Framework for Large-Scale SAR Satellite Data Processing The pyroSAR package aims at providing a complete solution for the scalable or

STAR-FC This code is the implementation for the CVPR 2021 paper "Structure-Aware Face Clustering on a Large-Scale Graph with 10^7 Nodes" 🌟 🌟 . 🎓 Re

AOT-GAN for High-Resolution Image Inpainting Arxiv Paper | AOT-GAN: Aggregated Contextual Transformations for High-Resolution Image Inpainting Yanhong

This repository provides a script and recipe to run the highly optimized transformer-based encoder and decoder component, and it is tested and maintained by NVIDIA.

Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o

DensePhrases DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches th

ACMM [News] The code for ACMH is released!!! [News] The code for ACMP is released!!! About ACMM is a multi-scale geometric consistency guided multi-vi

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

torch-optimizer torch-optimizer -- collection of optimizers for PyTorch compatible with optim module. Simple example import torch_optimizer as optim

Description FairScale is a PyTorch extension library for high performance and large scale training on one or multiple machines/nodes. This library ext

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective. 10x Larger Models 10x Faster Trainin

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

TF Quant Finance: TensorFlow based Quant Finance Library Table of contents Introduction Installation TensorFlow training Development roadmap Examples

Open-L2O This repository establishes the first comprehensive benchmark efforts of existing learning to optimize (L2O) approaches on a number of proble

Summit Summit is a set of tools for optimising chemical processes. We’ve started by targeting reactions. What is Summit? Currently, reaction optimisat

Open Semantic Search https://opensemanticsearch.org Integrated search server, ETL framework for document processing (crawling, text extraction, text a

News Python3 implementations of PSENet [1], PAN [2] and PAN++ [3] are released at https://github.com/whai362/pan_pp.pytorch. [1] W. Wang, E. Xie, X. L

PSENet: Shape Robust Text Detection with Progressive Scale Expansion Network Introduction This is a tensorflow re-implementation of PSENet: Shape Robu

Large Scale Image Completion via Co-Modulated Generative Adversarial Networks, ICLR 2021 (Spotlight) Demo | Paper [NEW!] Time to play with our interac

Enjoy-Hamburger 🍔 Official implementation of Hamburger, Is Attention Better Than Matrix Decomposition? (ICLR 2021) Under construction. Introduction T

MathOptInterface Documentation Build Status Social An abstraction layer for mathematical optimization solvers. Replaces MathProgBase. Citing MathOptIn

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

TrueNAS CORE/Enterprise/SCALE main source repo Want to contribute or collaborate? Join our Slack instance. IMPORTANT NOTE: This is the master branch o

NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi

Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes

POT: Python Optimal Transport This open source Python library provide several solvers for optimization problems related to Optimal Transport for signa

Note: This package is for use with GPFlow 1. For Bayesian optimization using GPFlow 2 please see Trieste, a joint effort with Secondmind. GPflowOpt GP

Platypus What is Platypus? Platypus is a framework for evolutionary computing in Python with a focus on multiobjective evolutionary algorithms (MOEAs)

PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python. It is intended for swarm intelligence researchers, practit

Solid is a Python framework for gradient-free optimization. It contains basic versions of many of the most common optimization algorithms that do not

Scikit-Optimize Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements

SafeOpt - Safe Bayesian Optimization This code implements an adapted version of the safe, Bayesian optimization algorithm, SafeOpt [1], [2]. It also p

Bayesian Optimization Pure Python implementation of bayesian global optimization with gaussian processes. PyPI (pip): $ pip install bayesian-optimizat

hyperopt-sklearn Hyperopt-sklearn is Hyperopt-based model selection among machine learning algorithms in scikit-learn. See how to use hyperopt-sklearn

Hyperopt: Distributed Hyperparameter Optimization Hyperopt is a Python library for serial and parallel optimization over awkward search spaces, which

Optunity is a library containing various optimizers for hyperparameter tuning. Hyperparameter tuning is a recurrent problem in many machine learning t

SMAC v3 Project Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). Ho

BoTorch is a library for Bayesian Optimization built on PyTorch. BoTorch is currently in beta and under active development! Why BoTorch ? BoTorch Prov

monkeys "If an army of monkeys were strumming on typewriters they might write all the books in the British Museum." monkeys is a framework designed to

This project is now archived. It's been fun working on it, but it's time for me to move on. Thank you for all the support and feedback over the last c

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

auto-sklearn auto-sklearn is an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. Find the documentation here

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Operating system Build Status Linux/Mac Windows tick tick is a Python 3 module for statistical learning, with a particular emphasis on time-dependent

[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

Optimization for Oriented Object Detection via Representation Invariance Loss By Qi Ming, Zhiqiang Zhou, Lingjuan Miao, Xue Yang, and Yunpeng Dong. Th

TriOp Tool for quickly gathering information from Shodan.io about the number of IPs which satisfy large number of different queries For furt

MazeRL is an application oriented Deep Reinforcement Learning (RL) framework, addressing real-world decision problems. Our vision is to cover the complete development life cycle of RL applications ranging from simulation engineering up to agent development, training and deployment.

Model search (MS) is a framework that implements AutoML algorithms for model architecture search at scale. It aims to help researchers speed up their exploration process for finding the right model architecture for their classification problems (i.e., DNNs with different types of layers).

NeuralQA: A Usable Library for (Extractive) Question Answering on Large Datasets with BERT Still in alpha, lots of changes anticipated. View demo on n

ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis

ec2-spot-converter This tool converts existing AWS EC2 instances back and forth between On-Demand and 'persistent' Spot billing models while preservin

SAHI: Slicing Aided Hyper Inference A vision library for performing sliced inference on large images/small objects Overview Object detection and insta

This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.

NeuralQA: A Usable Library for (Extractive) Question Answering on Large Datasets with BERT Still in alpha, lots of changes anticipated. View demo on n

Haystack is an end-to-end framework for Question Answering & Neural search that enables you to ... ... ask questions in natural language and find gran

ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Apache Spark Spark is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an op

The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou

DALL-E in Mesh-Tensorflow [WIP] Open-AI's DALL-E in Mesh-Tensorflow. If this is similarly efficient to GPT-Neo, this repo should be able to train mode

UltraOpt : Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. UltraOpt is a simple and efficient library to minimize expensive

- 基于标题的大规模商品实体检索top1 一、任务介绍 CCKS 2020：基于标题的大规模商品实体检索，任务为对于给定的一个商品标题，参赛系统需要匹配到该标题在给定商品库中的对应商品实体。 输入：输入文件包括若干行商品标题。 输出：输出文本每一行包括此标题对应的商品实体，即给定知识库中商品 ID，

Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap

Contextual Non-Local Alignment over Full-Scale Representation for Text-Based Person Search This is an implementation for our paper Contextual Non-Loca

Geometric Vector Perceptron Implementation of Geometric Vector Perceptron, a simple circuit with 3d rotation equivariance for learning over large biom

The Falcon Web Framework Falcon is a reliable, high-performance Python web framework for building large-scale app backends and microservices. It encou

Opytimizer: A Nature-Inspired Python Optimizer Welcome to Opytimizer. Did you ever reach a bottleneck in your computational experiments? Are you tired

Determined: Deep Learning Training Platform Determined is an open-source deep learning training platform that makes building models fast and easy. Det

MLJAR Automated Machine Learning Documentation: https://supervised.mljar.com/ Source Code: https://github.com/mljar/mljar-supervised Table of Contents

BayesO: A Bayesian optimization framework in Python Simple, but essential Bayesian optimization package. http://bayeso.org Online documentation Instal

Neuraxle Pipelines Code Machine Learning Pipelines - The Right Way. Neuraxle is a Machine Learning (ML) library for building machine learning pipeline

MiraiML Mirai: future in japanese. MiraiML is an asynchronous engine for continuous & autonomous machine learning, built for real-time usage. Usage In

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Xcessiv Xcessiv is a tool to help you create the biggest, craziest, and most excessive stacked ensembles you can think of. Stacked ensembles are simpl

Master status: Development status: Package information: TPOT stands for Tree-based Pipeline Optimization Tool. Consider TPOT your Data Science Assista

Spearmint Spearmint is a software package to perform Bayesian optimization. The Software is designed to automatically run experiments (thus the code n

Run inference at scale Cortex is an open source platform for large-scale machine learning inference workloads. Workloads Realtime APIs - respond to pr

auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au

scikit-opt Swarm Intelligence in Python (Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Algorithm, Immune Algorithm,A

Ray provides a simple, universal API for building distributed applications. Ray is packaged with the following libraries for accelerating machine lear

Latest Salt Documentation Open an issue (bug report, feature request, etc.) Salt is the world’s fastest, most intelligent and scalable automation engi

pyinfra automates/provisions/manages/deploys infrastructure super fast at massive scale. It can be used for ad-hoc command execution, service deployme