{"id":13443256,"url":"https://github.com/microsoft/nni","last_synced_at":"2025-10-05T16:31:11.351Z","repository":{"id":37436834,"uuid":"135673451","full_name":"microsoft/nni","owner":"microsoft","description":"An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter 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align=\"center\"\u003e\n\u003cimg src=\"docs/img/nni_logo.png\" width=\"600\"/\u003e\n\u003c/div\u003e\n\n\u003cbr/\u003e\n\n[![MIT licensed](https://img.shields.io/badge/license-MIT-brightgreen.svg)](LICENSE)\n[![Issues](https://img.shields.io/github/issues-raw/Microsoft/nni.svg)](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen)\n[![Bugs](https://img.shields.io/github/issues/Microsoft/nni/bug.svg)](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen+label%3Abug)\n[![Pull Requests](https://img.shields.io/github/issues-pr-raw/Microsoft/nni.svg)](https://github.com/Microsoft/nni/pulls?q=is%3Apr+is%3Aopen)\n[![Version](https://img.shields.io/github/release/Microsoft/nni.svg)](https://github.com/Microsoft/nni/releases)\n[![Documentation Status](https://readthedocs.org/projects/nni/badge/?version=stable)](https://nni.readthedocs.io/en/stable/?badge=stable)\n[![](https://img.shields.io/github/contributors-anon/microsoft/nni)](https://github.com/microsoft/nni/graphs/contributors)\n\n\n\n[\u003cimg src=\"docs/img/readme_banner.png\" width=\"100%\"/\u003e](https://nni.readthedocs.io/en/stable)\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://nni.readthedocs.io/) ([简体中文版点这里](https://nni.readthedocs.io/zh/stable))**.\n\n## What's NEW! \u0026nbsp;\u003ca href=\"#nni-released-reminder\"\u003e\u003cimg width=\"48\" src=\"docs/img/release_icon.png\"\u003e\u003c/a\u003e\n\n* **New release**: [v3.0 preview is available](https://github.com/microsoft/nni/releases/tag/v3.0rc1) - _released on May-5-2022_\n* **New demo available**: [Youtube entry](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw) | [Bilibili 入口](https://space.bilibili.com/1649051673) - _last updated on June-22-2022_\n* **New research paper**: [SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute](https://www.usenix.org/system/files/osdi22-zheng-ningxin.pdf) - _published in OSDI 2022_\n* **New research paper**: [Privacy-preserving Online AutoML for Domain-Specific Face Detection](https://openaccess.thecvf.com/content/CVPR2022/papers/Yan_Privacy-Preserving_Online_AutoML_for_Domain-Specific_Face_Detection_CVPR_2022_paper.pdf) - _published in CVPR 2022_\n* **Newly upgraded documentation**: [Doc upgraded](https://nni.readthedocs.io/en/stable)\n\n\n## Installation\n\nSee the [NNI installation guide](https://nni.readthedocs.io/en/stable/installation.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/img/overview.svg\" width=\"100%\"/\u003e\n\n\u003ctable\u003e\n\u003ctbody\u003e\n\u003ctr align=\"center\" valign=\"bottom\"\u003e\n\u003ctd\u003e\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eHyperparameter Tuning\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eNeural Architecture Search\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eModel Compression\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd align=\"center\" valign=\"middle\"\u003e\n\u003cb\u003eAlgorithms\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cb\u003eExhaustive search\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.gridsearch_tuner.GridSearchTuner\"\u003eGrid Search\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.random_tuner.RandomTuner\"\u003eRandom\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eHeuristic search\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.hyperopt_tuner.HyperoptTuner\"\u003eAnneal\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.evolution_tuner.EvolutionTuner\"\u003eEvolution\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.hyperband_advisor.Hyperband\"\u003eHyperband\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.pbt_tuner.PBTTuner\"\u003ePBT\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eBayesian optimization\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.bohb_advisor.BOHB\"\u003eBOHB\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.dngo_tuner.DNGOTuner\"\u003eDNGO\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.gp_tuner.GPTuner\"\u003eGP\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.metis_tuner.MetisTuner\"\u003eMetis\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.smac_tuner.SMACTuner\"\u003eSMAC\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/reference/hpo.html#nni.algorithms.hpo.tpe_tuner.TpeTuner\"\u003eTPE\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cb\u003eMulti-trial\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#grid-search-strategy\"\u003eGrid Search\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#policy-based-rl-strategy\"\u003ePolicy Based RL\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#random-strategy\"\u003eRandom\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#regularized-evolution-strategy\"\u003eRegularized Evolution\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#tpe-strategy\"\u003eTPE\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eOne-shot\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#darts-strategy\"\u003eDARTS\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#enas-strategy\"\u003eENAS\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#fbnet-strategy\"\u003eFBNet\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#proxylessnas-strategy\"\u003eProxylessNAS\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/nas/exploration_strategy.html#spos-strategy\"\u003eSPOS\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cb\u003ePruning\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#level-pruner\"\u003eLevel\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#l1-norm-pruner\"\u003eL1 Norm\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#taylor-fo-weight-pruner\"\u003eTaylor FO Weight\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#movement-pruner\"\u003eMovement\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#agp-pruner\"\u003eAGP\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html#auto-compress-pruner\"\u003eAuto Compress\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/pruner.html\"\u003eMore...\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eQuantization\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#naive-quantizer\"\u003eNaive\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#qat-quantizer\"\u003eQAT\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#lsq-quantizer\"\u003eLSQ\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#observer-quantizer\"\u003eObserver\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#dorefa-quantizer\"\u003eDoReFa\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/compression/quantizer.html#bnn-quantizer\"\u003eBNN\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003ctr align=\"center\" valign=\"bottom\"\u003e\n\u003ctd\u003e\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eSupported Frameworks\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eTraining Services\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cb\u003eTutorials\u003c/b\u003e\n\u003cimg src=\"docs/img/bar.png\" /\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr valign=\"top\"\u003e\n\u003ctd align=\"center\" valign=\"middle\"\u003e\n\u003cb\u003eSupports\u003c/b\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003ePyTorch\u003c/li\u003e\n\u003cli\u003eTensorFlow\u003c/li\u003e\n\u003cli\u003eScikit-learn\u003c/li\u003e\n\u003cli\u003eXGBoost\u003c/li\u003e\n\u003cli\u003eLightGBM\u003c/li\u003e\n\u003cli\u003eMXNet\u003c/li\u003e\n\u003cli\u003eCaffe2\u003c/li\u003e\n\u003cli\u003eMore...\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/local.html\"\u003eLocal machine\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/remote.html\"\u003eRemote SSH servers\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/aml.html\"\u003eAzure Machine Learning (AML)\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cb\u003eKubernetes Based\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/openpai.html\"\u003eOpenAPI\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/kubeflow.html\"\u003eKubeflow\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/frameworkcontroller.html\"\u003eFrameworkController\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/adaptdl.html\"\u003eAdaptDL\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/paidlc.html\"\u003ePAI DLC\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/experiment/hybrid.html\"\u003eHybrid training services\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003ctd\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cb\u003eHPO\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/hpo_quickstart_pytorch/main.html\"\u003ePyTorch\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/hpo_quickstart_tensorflow/main.html\"\u003eTensorFlow\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eNAS\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/hello_nas.html\"\u003eHello NAS\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/nasbench_as_dataset.html\"\u003eNAS Benchmarks\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cli\u003e\u003cb\u003eCompression\u003c/b\u003e\u003c/li\u003e\n\u003cul\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/pruning_quick_start.html\"\u003ePruning\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/pruning_speed_up.html\"\u003ePruning Speedup\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/quantization_quick_start.html\"\u003eQuantization\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003ca href=\"https://nni.readthedocs.io/en/latest/tutorials/quantization_speed_up.html\"\u003eQuantization Speedup\u003c/a\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003c/ul\u003e\n\u003c/td\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\n\u003cimg src=\"docs/static/img/webui.gif\" alt=\"webui\" width=\"100%\"/\u003e\n\n## Resources\n\n* [NNI Documentation Homepage](https://nni.readthedocs.io/en/stable)\n* [NNI Installation Guide](https://nni.readthedocs.io/en/stable/installation.html)\n* [NNI Examples](https://nni.readthedocs.io/en/latest/examples.html)\n* [Python API Reference](https://nni.readthedocs.io/en/latest/reference/python_api.html)\n* [Releases (Change Log)](https://nni.readthedocs.io/en/latest/release.html)\n* [Related Research and Publications](https://nni.readthedocs.io/en/latest/notes/research_publications.html)\n* [Youtube Channel of NNI](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw)\n* [Bilibili Space of NNI](https://space.bilibili.com/1649051673)\n* [Webinar of Introducing Retiarii: A deep learning exploratory-training framework on NNI](https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html)\n* [Community Discussions](https://github.com/microsoft/nni/discussions)\n\n## Contribution guidelines\n\nIf you want to contribute to NNI, be sure to review the [contribution guidelines](https://nni.readthedocs.io/en/stable/notes/contributing.html), which includes instructions of submitting feedbacks, best coding practices, and code of conduct.\n\nWe use [GitHub issues](https://github.com/microsoft/nni/issues) to track tracking requests and bugs.\nPlease use [NNI Discussion](https://github.com/microsoft/nni/discussions) for general questions and new ideas.\nFor questions of specific use cases, please go to [Stack Overflow](https://stackoverflow.com/questions/tagged/nni).\n\nParticipating discussions via the following IM groups is also welcomed.\n\n|Gitter||WeChat|\n|----|----|----|\n|![image](https://user-images.githubusercontent.com/39592018/80665738-e0574a80-8acc-11ea-91bc-0836dc4cbf89.png)| OR |![image](https://github.com/scarlett2018/nniutil/raw/master/wechat.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://img.shields.io/github/contributors-anon/microsoft/nni\"/\u003e\n\n\u003ca href=\"https://github.com/microsoft/nni/graphs/contributors\"\u003e\u003cimg src=\"https://contrib.rocks/image?repo=microsoft/nni\u0026max=240\u0026columns=18\" /\u003e\u003c/a\u003e\n\n## Test status\n\n### Essentials\n\n| Type | Status |\n| :---: | :---: |\n| Fast test | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/fast%20test?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=54\u0026branchName=master) |\n| Full test - HPO | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/full%20test%20-%20HPO?repoName=microsoft%2Fnni\u0026branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=90\u0026repoName=microsoft%2Fnni\u0026branchName=master) |\n| Full test - NAS | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/full%20test%20-%20NAS?repoName=microsoft%2Fnni\u0026branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=89\u0026repoName=microsoft%2Fnni\u0026branchName=master) |\n| Full test - compression | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/full%20test%20-%20compression?repoName=microsoft%2Fnni\u0026branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=91\u0026repoName=microsoft%2Fnni\u0026branchName=master) |\n\n### Training services\n\n| Type | Status |\n| :---: | :---: |\n| Local - linux | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20local%20-%20linux?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=92\u0026branchName=master) |\n| Local - windows | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20local%20-%20windows?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=98\u0026branchName=master) |\n| Remote - linux to linux | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20remote%20-%20linux%20to%20linux?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=64\u0026branchName=master) |\n| Remote - windows to windows | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20remote%20-%20windows%20to%20windows?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=99\u0026branchName=master) |\n| OpenPAI | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20openpai%20-%20linux?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=65\u0026branchName=master) |\n| Frameworkcontroller | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20frameworkcontroller?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=70\u0026branchName=master) |\n| Kubeflow | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20kubeflow?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=69\u0026branchName=master) |\n| Hybrid | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20hybrid?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=79\u0026branchName=master) |\n| AzureML | [![Build Status](https://msrasrg.visualstudio.com/NNIOpenSource/_apis/build/status/integration%20test%20-%20aml?branchName=master)](https://msrasrg.visualstudio.com/NNIOpenSource/_build/latest?definitionId=78\u0026branchName=master) |\n\n## Related Projects\n\nTargeting at openness and advancing state-of-art technology, [Microsoft Research (MSR)](https://www.microsoft.com/en-us/research/group/systems-and-networking-research-group-asia/) had also released few other open source projects.\n\n* [OpenPAI](https://github.com/Microsoft/pai) : 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://github.com/Microsoft/frameworkcontroller) : an open source general-purpose Kubernetes Pod Controller that orchestrate all kinds of applications on Kubernetes by a single controller.\n* [MMdnn](https://github.com/Microsoft/MMdnn) : 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://github.com/Microsoft/SPTAG) : Space Partition Tree And Graph (SPTAG) is an open source library for large scale vector approximate nearest neighbor search scenario.\n* [nn-Meter](https://github.com/microsoft/nn-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","funding_links":[],"categories":["Toolbox","Python","🛠️ General ML Testing Frameworks","Python Frameworks and Tools","神经网络结构搜索_Neural_Architecture_Search","Tools","Frameworks and libraries","Neural Architecture Search (NAS)","Deep Learning Framework","Python Frameworks, Libraries, and Tools","Tools and projects","超参数优化和AutoML","Python Learning Resources","Libraries","Uncategorized","AutoML","📚 Project Purpose"],"sub_categories":["Libraries","In-memory data grids","Approximations Frameworks",":snake: Python","Performance (\u0026 Automated ML)","Auto ML \u0026 Hyperparameter Optimization","LLM","Interfaces","E-Books","VS Code Extensions for Developer Productivity","Objective-C Tools, Libraries, and Frameworks","viii. Linear Regression","Mesh networks","JavaScript Libraries for Machine Learning","Uncategorized","Machine Learning (Interview-Level"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmicrosoft%2Fnni","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmicrosoft%2Fnni","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmicrosoft%2Fnni/lists"}