[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-9628":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":16,"forks30d":16,"starsTrendScore":16,"compositeScore":19,"rankGlobal":10,"rankLanguage":10,"license":20,"archived":21,"fork":22,"defaultBranch":23,"hasWiki":21,"hasPages":22,"topics":24,"createdAt":10,"pushedAt":10,"updatedAt":45,"readmeContent":46,"aiSummary":47,"trendingCount":16,"starSnapshotCount":16,"syncStatus":48,"lastSyncTime":49,"discoverSource":50},9628,"nni","microsoft\u002Fnni","microsoft","An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.","https:\u002F\u002Fnni.readthedocs.io",null,"Python",14352,1859,6,397,0,3,10,72.31,"MIT License",true,false,"master",[25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44],"automated-machine-learning","automl","bayesian-optimization","data-science","deep-learning","deep-neural-network","distributed","feature-engineering","hyperparameter-optimization","hyperparameter-tuning","machine-learning","machine-learning-algorithms","mlops","model-compression","nas","neural-architecture-search","neural-network","python","pytorch","tensorflow","2026-06-12 04:00:46","\u003Cdiv align=\"center\">\n\u003Cimg src=\"docs\u002Fimg\u002Fnni_logo.png\" width=\"600\"\u002F>\n\u003C\u002Fdiv>\n\n\u003Cbr\u002F>\n\n[![MIT licensed](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002Flicense-MIT-brightgreen.svg)](LICENSE)\n[![Issues](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-raw\u002FMicrosoft\u002Fnni.svg)](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fnni\u002Fissues?q=is%3Aissue+is%3Aopen)\n[![Bugs](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues\u002FMicrosoft\u002Fnni\u002Fbug.svg)](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fnni\u002Fissues?q=is%3Aissue+is%3Aopen+label%3Abug)\n[![Pull Requests](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fissues-pr-raw\u002FMicrosoft\u002Fnni.svg)](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fnni\u002Fpulls?q=is%3Apr+is%3Aopen)\n[![Version](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Frelease\u002FMicrosoft\u002Fnni.svg)](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fnni\u002Freleases)\n[![Documentation Status](https:\u002F\u002Freadthedocs.org\u002Fprojects\u002Fnni\u002Fbadge\u002F?version=stable)](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable\u002F?badge=stable)\n[![](https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors-anon\u002Fmicrosoft\u002Fnni)](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Fgraphs\u002Fcontributors)\n\n\n\n[\u003Cimg src=\"docs\u002Fimg\u002Freadme_banner.png\" width=\"100%\"\u002F>](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable)\n\nNNI automates feature engineering, neural architecture search, hyperparameter tuning, and model compression for deep learning. Find the latest features, API, examples and tutorials in our **[official documentation](https:\u002F\u002Fnni.readthedocs.io\u002F) ([简体中文版点这里](https:\u002F\u002Fnni.readthedocs.io\u002Fzh\u002Fstable))**.\n\n## What's NEW!  \u003Ca href=\"#nni-released-reminder\">\u003Cimg width=\"48\" src=\"docs\u002Fimg\u002Frelease_icon.png\">\u003C\u002Fa>\n\n* **New release**: [v3.0 preview is available](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Freleases\u002Ftag\u002Fv3.0rc1) - _released on May-5-2022_\n* **New demo available**: [Youtube entry](https:\u002F\u002Fwww.youtube.com\u002Fchannel\u002FUCKcafm6861B2mnYhPbZHavw) | [Bilibili 入口](https:\u002F\u002Fspace.bilibili.com\u002F1649051673) - _last updated on June-22-2022_\n* **New research paper**: [SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute](https:\u002F\u002Fwww.usenix.org\u002Fsystem\u002Ffiles\u002Fosdi22-zheng-ningxin.pdf) - _published in OSDI 2022_\n* **New research paper**: [Privacy-preserving Online AutoML for Domain-Specific Face Detection](https:\u002F\u002Fopenaccess.thecvf.com\u002Fcontent\u002FCVPR2022\u002Fpapers\u002FYan_Privacy-Preserving_Online_AutoML_for_Domain-Specific_Face_Detection_CVPR_2022_paper.pdf) - _published in CVPR 2022_\n* **Newly upgraded documentation**: [Doc upgraded](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable)\n\n\n## Installation\n\nSee the [NNI installation guide](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable\u002Finstallation.html) to install from pip, or build from source.\n\nTo install the current release:\n\n```\n$ pip install nni\n```\n\nTo update NNI to the latest version, add `--upgrade` flag to the above commands.\n\n## NNI capabilities in a glance\n\n\u003Cimg src=\"docs\u002Fimg\u002Foverview.svg\" width=\"100%\"\u002F>\n\n\u003Ctable>\n\u003Ctbody>\n\u003Ctr align=\"center\" valign=\"bottom\">\n\u003Ctd>\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Hyperparameter Tuning\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Neural Architecture Search\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Model Compression\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr valign=\"top\">\n\u003Ctd align=\"center\" valign=\"middle\">\n\u003Cb>Algorithms\u003C\u002Fb>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>\u003Cb>Exhaustive search\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.gridsearch_tuner.GridSearchTuner\">Grid Search\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.random_tuner.RandomTuner\">Random\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>Heuristic search\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.hyperopt_tuner.HyperoptTuner\">Anneal\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.evolution_tuner.EvolutionTuner\">Evolution\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.hyperband_advisor.Hyperband\">Hyperband\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.pbt_tuner.PBTTuner\">PBT\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>Bayesian optimization\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.bohb_advisor.BOHB\">BOHB\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.dngo_tuner.DNGOTuner\">DNGO\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.gp_tuner.GPTuner\">GP\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.metis_tuner.MetisTuner\">Metis\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.smac_tuner.SMACTuner\">SMAC\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fhpo.html#nni.algorithms.hpo.tpe_tuner.TpeTuner\">TPE\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>\u003Cb>Multi-trial\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#grid-search-strategy\">Grid Search\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#policy-based-rl-strategy\">Policy Based RL\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#random-strategy\">Random\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#regularized-evolution-strategy\">Regularized Evolution\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#tpe-strategy\">TPE\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>One-shot\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#darts-strategy\">DARTS\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#enas-strategy\">ENAS\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#fbnet-strategy\">FBNet\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#proxylessnas-strategy\">ProxylessNAS\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnas\u002Fexploration_strategy.html#spos-strategy\">SPOS\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>\u003Cb>Pruning\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#level-pruner\">Level\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#l1-norm-pruner\">L1 Norm\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#taylor-fo-weight-pruner\">Taylor FO Weight\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#movement-pruner\">Movement\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#agp-pruner\">AGP\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html#auto-compress-pruner\">Auto Compress\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fpruner.html\">More...\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>Quantization\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#naive-quantizer\">Naive\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#qat-quantizer\">QAT\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#lsq-quantizer\">LSQ\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#observer-quantizer\">Observer\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#dorefa-quantizer\">DoReFa\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fcompression\u002Fquantizer.html#bnn-quantizer\">BNN\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003Ctr align=\"center\" valign=\"bottom\">\n\u003Ctd>\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Supported Frameworks\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Training Services\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cb>Tutorials\u003C\u002Fb>\n\u003Cimg src=\"docs\u002Fimg\u002Fbar.png\" \u002F>\n\u003C\u002Ftd>\n\u003C\u002Ftr>\n\u003Ctr valign=\"top\">\n\u003Ctd align=\"center\" valign=\"middle\">\n\u003Cb>Supports\u003C\u002Fb>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>PyTorch\u003C\u002Fli>\n\u003Cli>TensorFlow\u003C\u002Fli>\n\u003Cli>Scikit-learn\u003C\u002Fli>\n\u003Cli>XGBoost\u003C\u002Fli>\n\u003Cli>LightGBM\u003C\u002Fli>\n\u003Cli>MXNet\u003C\u002Fli>\n\u003Cli>Caffe2\u003C\u002Fli>\n\u003Cli>More...\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Flocal.html\">Local machine\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fremote.html\">Remote SSH servers\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Faml.html\">Azure Machine Learning (AML)\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Cb>Kubernetes Based\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fopenpai.html\">OpenAPI\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fkubeflow.html\">Kubeflow\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fframeworkcontroller.html\">FrameworkController\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fadaptdl.html\">AdaptDL\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fpaidlc.html\">PAI DLC\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexperiment\u002Fhybrid.html\">Hybrid training services\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003Ctd>\n\u003Cul>\n\u003Cli>\u003Cb>HPO\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fhpo_quickstart_pytorch\u002Fmain.html\">PyTorch\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fhpo_quickstart_tensorflow\u002Fmain.html\">TensorFlow\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>NAS\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fhello_nas.html\">Hello NAS\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fnasbench_as_dataset.html\">NAS Benchmarks\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003Cli>\u003Cb>Compression\u003C\u002Fb>\u003C\u002Fli>\n\u003Cul>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fpruning_quick_start.html\">Pruning\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fpruning_speed_up.html\">Pruning Speedup\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fquantization_quick_start.html\">Quantization\u003C\u002Fa>\u003C\u002Fli>\n\u003Cli>\u003Ca href=\"https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Ftutorials\u002Fquantization_speed_up.html\">Quantization Speedup\u003C\u002Fa>\u003C\u002Fli>\n\u003C\u002Ful>\n\u003C\u002Ful>\n\u003C\u002Ftd>\n\u003C\u002Ftbody>\n\u003C\u002Ftable>\n\n\u003Cimg src=\"docs\u002Fstatic\u002Fimg\u002Fwebui.gif\" alt=\"webui\" width=\"100%\"\u002F>\n\n## Resources\n\n* [NNI Documentation Homepage](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable)\n* [NNI Installation Guide](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable\u002Finstallation.html)\n* [NNI Examples](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fexamples.html)\n* [Python API Reference](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Freference\u002Fpython_api.html)\n* [Releases (Change Log)](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Frelease.html)\n* [Related Research and Publications](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Flatest\u002Fnotes\u002Fresearch_publications.html)\n* [Youtube Channel of NNI](https:\u002F\u002Fwww.youtube.com\u002Fchannel\u002FUCKcafm6861B2mnYhPbZHavw)\n* [Bilibili Space of NNI](https:\u002F\u002Fspace.bilibili.com\u002F1649051673)\n* [Webinar of Introducing Retiarii: A deep learning exploratory-training framework on NNI](https:\u002F\u002Fnote.microsoft.com\u002FMSR-Webinar-Retiarii-Registration-Live.html)\n* [Community Discussions](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Fdiscussions)\n\n## Contribution guidelines\n\nIf you want to contribute to NNI, be sure to review the [contribution guidelines](https:\u002F\u002Fnni.readthedocs.io\u002Fen\u002Fstable\u002Fnotes\u002Fcontributing.html), which includes instructions of submitting feedbacks, best coding practices, and code of conduct.\n\nWe use [GitHub issues](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Fissues) to track tracking requests and bugs.\nPlease use [NNI Discussion](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Fdiscussions) for general questions and new ideas.\nFor questions of specific use cases, please go to [Stack Overflow](https:\u002F\u002Fstackoverflow.com\u002Fquestions\u002Ftagged\u002Fnni).\n\nParticipating discussions via the following IM groups is also welcomed.\n\n|Gitter||WeChat|\n|----|----|----|\n|![image](https:\u002F\u002Fuser-images.githubusercontent.com\u002F39592018\u002F80665738-e0574a80-8acc-11ea-91bc-0836dc4cbf89.png)| OR |![image](https:\u002F\u002Fgithub.com\u002Fscarlett2018\u002Fnniutil\u002Fraw\u002Fmaster\u002Fwechat.png)|\n\nOver the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull requests from hundreds of contributors.\nWe appreciate all contributions from community to make NNI thrive.\n\n\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fgithub\u002Fcontributors-anon\u002Fmicrosoft\u002Fnni\"\u002F>\n\n\u003Ca href=\"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnni\u002Fgraphs\u002Fcontributors\">\u003Cimg src=\"https:\u002F\u002Fcontrib.rocks\u002Fimage?repo=microsoft\u002Fnni&max=240&columns=18\" \u002F>\u003C\u002Fa>\n\n## Test status\n\n### Essentials\n\n| Type | Status |\n| :---: | :---: |\n| Fast test | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Ffast%20test?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=54&branchName=master) |\n| Full test - HPO | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Ffull%20test%20-%20HPO?repoName=microsoft%2Fnni&branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=90&repoName=microsoft%2Fnni&branchName=master) |\n| Full test - NAS | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Ffull%20test%20-%20NAS?repoName=microsoft%2Fnni&branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=89&repoName=microsoft%2Fnni&branchName=master) |\n| Full test - compression | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Ffull%20test%20-%20compression?repoName=microsoft%2Fnni&branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=91&repoName=microsoft%2Fnni&branchName=master) |\n\n### Training services\n\n| Type | Status |\n| :---: | :---: |\n| Local - linux | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20local%20-%20linux?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=92&branchName=master) |\n| Local - windows | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20local%20-%20windows?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=98&branchName=master) |\n| Remote - linux to linux | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20remote%20-%20linux%20to%20linux?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=64&branchName=master) |\n| Remote - windows to windows | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20remote%20-%20windows%20to%20windows?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=99&branchName=master) |\n| OpenPAI | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20openpai%20-%20linux?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=65&branchName=master) |\n| Frameworkcontroller | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20frameworkcontroller?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=70&branchName=master) |\n| Kubeflow | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20kubeflow?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=69&branchName=master) |\n| Hybrid | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20hybrid?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=79&branchName=master) |\n| AzureML | [![Build Status](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_apis\u002Fbuild\u002Fstatus\u002Fintegration%20test%20-%20aml?branchName=master)](https:\u002F\u002Fmsrasrg.visualstudio.com\u002FNNIOpenSource\u002F_build\u002Flatest?definitionId=78&branchName=master) |\n\n## Related Projects\n\nTargeting at openness and advancing state-of-art technology, [Microsoft Research (MSR)](https:\u002F\u002Fwww.microsoft.com\u002Fen-us\u002Fresearch\u002Fgroup\u002Fsystems-and-networking-research-group-asia\u002F) had also released few other open source projects.\n\n* [OpenPAI](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fpai) : an open source platform that provides complete AI model training and resource management capabilities, it is easy to extend and supports on-premise, cloud and hybrid environments in various scale.\n* [FrameworkController](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002Fframeworkcontroller) : an open source general-purpose Kubernetes Pod Controller that orchestrate all kinds of applications on Kubernetes by a single controller.\n* [MMdnn](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002FMMdnn) : A comprehensive, cross-framework solution to convert, visualize and diagnose deep neural network models. The \"MM\" in MMdnn stands for model management and \"dnn\" is an acronym for deep neural network.\n* [SPTAG](https:\u002F\u002Fgithub.com\u002FMicrosoft\u002FSPTAG) : Space Partition Tree And Graph (SPTAG) is an open source library for large scale vector approximate nearest neighbor search scenario.\n* [nn-Meter](https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fnn-Meter) : An accurate inference latency predictor for DNN models on diverse edge devices.\n\nWe encourage researchers and students leverage these projects to accelerate the AI development and research.\n\n## License\n\nThe entire codebase is under [MIT license](LICENSE).\n","microsoft\u002Fnni 是一个开源的自动化机器学习工具包，旨在自动完成包括特征工程、神经架构搜索、模型压缩和超参数调优在内的机器学习生命周期。该项目支持多种优化算法如贝叶斯优化等，并且能够与 PyTorch 和 TensorFlow 等主流深度学习框架无缝集成，提供分布式训练能力以加速实验过程。适用于需要高效开发和优化深度学习模型的各种场景，无论是科研还是工业应用都能从中受益。采用 Python 语言编写，遵循 MIT 开源许可协议。",2,"2026-06-11 03:23:53","top_topic"]