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Expand Up @@ -14,9 +14,9 @@

[NNI Doc](https://nni.readthedocs.io/) | [简体中文](README_zh_CN.md)

**NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate** <a href="docs/en_US/FeatureEngineering/Overview.rst">Feature Engineering</a>, <a href="docs/en_US/NAS/Overview.rst">Neural Architecture Search</a>, <a href="docs/en_US/Tuner/BuiltinTuner.rst">Hyperparameter Tuning</a> and <a href="docs/en_US/Compression/Overview.rst">Model Compression</a>.
**NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate** <a href="https://nni.readthedocs.io/en/latest/FeatureEngineering/Overview.html">Feature Engineering</a>, <a href="https://nni.readthedocs.io/en/latest/NAS/Overview.html">Neural Architecture Search</a>, <a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html">Hyperparameter Tuning</a> and <a href="https://nni.readthedocs.io/en/latest/Compression/Overview.html">Model Compression</a>.

The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <a href="docs/en_US/TrainingService/LocalMode.rst">Local Machine</a>, <a href="docs/en_US/TrainingService/RemoteMachineMode.rst">Remote Servers</a>, <a href="docs/en_US/TrainingService/PaiMode.rst">OpenPAI</a>, <a href="docs/en_US/TrainingService/KubeflowMode.rst">Kubeflow</a>, <a href="docs/en_US/TrainingService/FrameworkControllerMode.rst">FrameworkController on K8S (AKS etc.)</a>, <a href="docs/en_US/TrainingService/DLTSMode.rst">DLWorkspace (aka. DLTS)</a>, <a href="docs/en_US/TrainingService/AMLMode.rst">AML (Azure Machine Learning)</a>, <a href="docs/en_US/TrainingService/AdaptDLMode.rst">AdaptDL (aka. ADL)</a> , other cloud options and even <a href="docs/en_US/TrainingService/HybridMode.rst">Hybrid mode</a>.
The tool manages automated machine learning (AutoML) experiments, **dispatches and runs** experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in **different training environments** like <a href="https://nni.readthedocs.io/en/latest/TrainingService/LocalMode.html">Local Machine</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/RemoteMachineMode.html">Remote Servers</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/PaiMode.html">OpenPAI</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/KubeflowMode.html">Kubeflow</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/FrameworkControllerMode.html">FrameworkController on K8S (AKS etc.)</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/DLTSMode.html">DLWorkspace (aka. DLTS)</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/AMLMode.html">AML (Azure Machine Learning)</a>, <a href="https://nni.readthedocs.io/en/latest/TrainingService/AdaptDLMode.html">AdaptDL (aka. ADL)</a> , other cloud options and even <a href="https://nni.readthedocs.io/en/latest/TrainingService/HybridMode.html">Hybrid mode</a>.

## **Who should consider using NNI**

Expand Down Expand Up @@ -72,7 +72,7 @@ Within the following table, we summarized the current NNI capabilities, we are g
<li>TensorFlow</li>
<li>MXNet</li>
<li>Caffe2</li>
<a href="docs/en_US/SupportedFramework_Library.rst">More...</a><br/>
<a href="https://nni.readthedocs.io/en/latest/SupportedFramework_Library.html">More...</a><br/>
</ul>
</ul>
<ul>
Expand All @@ -81,7 +81,7 @@ Within the following table, we summarized the current NNI capabilities, we are g
<li>Scikit-learn</li>
<li>XGBoost</li>
<li>LightGBM</li>
<a href="docs/en_US/SupportedFramework_Library.rst">More...</a><br/>
<a href="https://nni.readthedocs.io/en/latest/SupportedFramework_Library.html">More...</a><br/>
</ul>
</ul>
<ul>
Expand All @@ -90,100 +90,100 @@ Within the following table, we summarized the current NNI capabilities, we are g
<li><a href="examples/trials/mnist-pytorch">MNIST-pytorch</li></a>
<li><a href="examples/trials/mnist-tfv1">MNIST-tensorflow</li></a>
<li><a href="examples/trials/mnist-keras">MNIST-keras</li></a>
<li><a href="docs/en_US/TrialExample/GbdtExample.rst">Auto-gbdt</a></li>
<li><a href="docs/en_US/TrialExample/Cifar10Examples.rst">Cifar10-pytorch</li></a>
<li><a href="docs/en_US/TrialExample/SklearnExamples.rst">Scikit-learn</a></li>
<li><a href="docs/en_US/TrialExample/EfficientNet.rst">EfficientNet</a></li>
<li><a href="docs/en_US/TrialExample/OpEvoExamples.rst">Kernel Tunning</li></a>
<a href="docs/en_US/SupportedFramework_Library.rst">More...</a><br/>
<li><a href="https://nni.readthedocs.io/en/latest/TrialExample/GbdtExample.html">Auto-gbdt</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrialExample/Cifar10Examples.html">Cifar10-pytorch</li></a>
<li><a href="https://nni.readthedocs.io/en/latest/TrialExample/SklearnExamples.html">Scikit-learn</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrialExample/EfficientNet.html">EfficientNet</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrialExample/OpEvoExamples.html">Kernel Tunning</li></a>
<a href="https://nni.readthedocs.io/en/latest/SupportedFramework_Library.html">More...</a><br/>
</ul>
</ul>
</td>
<td align="left" >
<a href="docs/en_US/Tuner/BuiltinTuner.rst">Hyperparameter Tuning</a>
<a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html">Hyperparameter Tuning</a>
<ul>
<b>Exhaustive search</b>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#Random">Random Search</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#GridSearch">Grid Search</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#Batch">Batch</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#Random">Random Search</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#GridSearch">Grid Search</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#Batch">Batch</a></li>
</ul>
<b>Heuristic search</b>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#Evolution">Naïve Evolution</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#Anneal">Anneal</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#Hyperband">Hyperband</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#PBTTuner">PBT</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#Evolution">Naïve Evolution</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#Anneal">Anneal</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#Hyperband">Hyperband</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#PBTTuner">PBT</a></li>
</ul>
<b>Bayesian optimization</b>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#BOHB">BOHB</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#TPE">TPE</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#SMAC">SMAC</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#MetisTuner">Metis Tuner</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#GPTuner">GP Tuner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#BOHB">BOHB</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#TPE">TPE</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#SMAC">SMAC</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#MetisTuner">Metis Tuner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#GPTuner">GP Tuner</a></li>
</ul>
<b>RL Based</b>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#PPOTuner">PPO Tuner</a> </li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#PPOTuner">PPO Tuner</a> </li>
</ul>
</ul>
<a href="docs/en_US/NAS/Overview.rst">Neural Architecture Search</a>
<a href="https://nni.readthedocs.io/en/latest/NAS/Overview.html">Neural Architecture Search</a>
<ul>
<ul>
<li><a href="docs/en_US/NAS/ENAS.rst">ENAS</a></li>
<li><a href="docs/en_US/NAS/DARTS.rst">DARTS</a></li>
<li><a href="docs/en_US/NAS/PDARTS.rst">P-DARTS</a></li>
<li><a href="docs/en_US/NAS/CDARTS.rst">CDARTS</a></li>
<li><a href="docs/en_US/NAS/SPOS.rst">SPOS</a></li>
<li><a href="docs/en_US/NAS/Proxylessnas.rst">ProxylessNAS</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.rst#NetworkMorphism">Network Morphism</a></li>
<li><a href="docs/en_US/NAS/TextNAS.rst">TextNAS</a></li>
<li><a href="docs/en_US/NAS/Cream.rst">Cream</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/ENAS.html">ENAS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/DARTS.html">DARTS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/PDARTS.html">P-DARTS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/CDARTS.html">CDARTS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/SPOS.html">SPOS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/Proxylessnas.html">ProxylessNAS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/BuiltinTuner.html#NetworkMorphism">Network Morphism</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/TextNAS.html">TextNAS</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/NAS/Cream.html">Cream</a></li>
</ul>
</ul>
<a href="docs/en_US/Compression/Overview.rst">Model Compression</a>
<a href="https://nni.readthedocs.io/en/latest/Compression/Overview.html">Model Compression</a>
<ul>
<b>Pruning</b>
<ul>
<li><a href="docs/en_US/Compression/Pruner.rst#agp-pruner">AGP Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#slim-pruner">Slim Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#fpgm-pruner">FPGM Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#netadapt-pruner">NetAdapt Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#simulatedannealing-pruner">SimulatedAnnealing Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#admm-pruner">ADMM Pruner</a></li>
<li><a href="docs/en_US/Compression/Pruner.rst#autocompress-pruner">AutoCompress Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#agp-pruner">AGP Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#slim-pruner">Slim Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#fpgm-pruner">FPGM Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#netadapt-pruner">NetAdapt Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#simulatedannealing-pruner">SimulatedAnnealing Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#admm-pruner">ADMM Pruner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Pruner.html#autocompress-pruner">AutoCompress Pruner</a></li>
</ul>
<b>Quantization</b>
<ul>
<li><a href="docs/en_US/Compression/Quantizer.rst#qat-quantizer">QAT Quantizer</a></li>
<li><a href="docs/en_US/Compression/Quantizer.rst#dorefa-quantizer">DoReFa Quantizer</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Quantizer.html#qat-quantizer">QAT Quantizer</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Compression/Quantizer.html#dorefa-quantizer">DoReFa Quantizer</a></li>
</ul>
</ul>
<a href="docs/en_US/FeatureEngineering/Overview.rst">Feature Engineering (Beta)</a>
<a href="https://nni.readthedocs.io/en/latest/FeatureEngineering/Overview.html">Feature Engineering (Beta)</a>
<ul>
<li><a href="docs/en_US/FeatureEngineering/GradientFeatureSelector.rst">GradientFeatureSelector</a></li>
<li><a href="docs/en_US/FeatureEngineering/GBDTSelector.rst">GBDTSelector</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/FeatureEngineering/GradientFeatureSelector.html">GradientFeatureSelector</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/FeatureEngineering/GBDTSelector.html">GBDTSelector</a></li>
</ul>
<a href="docs/en_US/Assessor/BuiltinAssessor.rst">Early Stop Algorithms</a>
<a href="https://nni.readthedocs.io/en/latest/Assessor/BuiltinAssessor.html">Early Stop Algorithms</a>
<ul>
<li><a href="docs/en_US/Assessor/BuiltinAssessor.rst#Medianstop">Median Stop</a></li>
<li><a href="docs/en_US/Assessor/BuiltinAssessor.rst#Curvefitting">Curve Fitting</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Assessor/BuiltinAssessor.html#MedianStop">Median Stop</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Assessor/BuiltinAssessor.html#Curvefitting">Curve Fitting</a></li>
</ul>
</td>
<td>
<ul>
<li><a href="docs/en_US/TrainingService/LocalMode.rst">Local Machine</a></li>
<li><a href="docs/en_US/TrainingService/RemoteMachineMode.rst">Remote Servers</a></li>
<li><a href="docs/en_US/TrainingService/HybridMode.rst">Hybrid mode</a></li>
<li><a href="docs/en_US/TrainingService/AMLMode.rst">AML(Azure Machine Learning)</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/LocalMode.html">Local Machine</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/RemoteMachineMode.html">Remote Servers</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/HybridMode.html">Hybrid mode</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/AMLMode.html">AML(Azure Machine Learning)</a></li>
<li><b>Kubernetes based services</b></li>
<ul>
<li><a href="docs/en_US/TrainingService/PaiMode.rst">OpenPAI</a></li>
<li><a href="docs/en_US/TrainingService/KubeflowMode.rst">Kubeflow</a></li>
<li><a href="docs/en_US/TrainingService/FrameworkControllerMode.rst">FrameworkController on K8S (AKS etc.)</a></li>
<li><a href="docs/en_US/TrainingService/DLTSMode.rst">DLWorkspace (aka. DLTS)</a></li>
<li><a href="docs/en_US/TrainingService/AdaptDLMode.rst">AdaptDL (aka. ADL)</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/PaiMode.html">OpenPAI</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/KubeflowMode.html">Kubeflow</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/FrameworkControllerMode.html">FrameworkController on K8S (AKS etc.)</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/DLTSMode.html">DLWorkspace (aka. DLTS)</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/AdaptDLMode.html">AdaptDL (aka. ADL)</a></li>
</ul>
</ul>
</td>
Expand All @@ -198,21 +198,21 @@ Within the following table, we summarized the current NNI capabilities, we are g
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="https://nni.readthedocs.io/en/latest/autotune_ref.html#trial">Python API</a></li>
<li><a href="docs/en_US/Tutorial/AnnotationSpec.rst">NNI Annotation</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tutorial/AnnotationSpec.html">NNI Annotation</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/installation.html">Supported OS</a></li>
</ul>
</td>
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="docs/en_US/Tuner/CustomizeTuner.rst">CustomizeTuner</a></li>
<li><a href="docs/en_US/Assessor/CustomizeAssessor.rst">CustomizeAssessor</a></li>
<li><a href="docs/en_US/Tutorial/InstallCustomizedAlgos.rst">Install Customized Algorithms as Builtin Tuners/Assessors/Advisors</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tuner/CustomizeTuner.html">CustomizeTuner</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Assessor/CustomizeAssessor.html">CustomizeAssessor</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/Tutorial/InstallCustomizedAlgos.html">Install Customized Algorithms as Builtin Tuners/Assessors/Advisors</a></li>
</ul>
</td>
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="docs/en_US/TrainingService/Overview.rst">Support TrainingService</li>
<li><a href="docs/en_US/TrainingService/HowToImplementTrainingService.rst">Implement TrainingService</a></li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/Overview.html">Support TrainingService</li>
<li><a href="https://nni.readthedocs.io/en/latest/TrainingService/HowToImplementTrainingService.html">Implement TrainingService</a></li>
</ul>
</td>
</tr>
Expand Down Expand Up @@ -244,8 +244,8 @@ For detail system requirements of NNI, please refer to [here](https://nni.readth
Note:

* If there is any privilege issue, add `--user` to install NNI in the user directory.
* Currently NNI on Windows supports local, remote and pai mode. Anaconda or Miniconda is highly recommended to install [NNI on Windows](docs/en_US/Tutorial/InstallationWin.rst).
* If there is any error like `Segmentation fault`, please refer to [FAQ](docs/en_US/Tutorial/FAQ.rst). For FAQ on Windows, please refer to [NNI on Windows](docs/en_US/Tutorial/InstallationWin.rst#faq).
* Currently NNI on Windows supports local, remote and pai mode. Anaconda or Miniconda is highly recommended to install [NNI on Windows](https://nni.readthedocs.io/en/latest/Tutorial/InstallationWin.html).
* If there is any error like `Segmentation fault`, please refer to [FAQ](https://nni.readthedocs.io/en/latest/Tutorial/FAQ.html). For FAQ on Windows, please refer to [NNI on Windows](https://nni.readthedocs.io/en/latest/Tutorial/InstallationWin.html#faq).

### **Verify installation**

Expand Down Expand Up @@ -297,7 +297,7 @@ You can use these commands to get more information about the experiment
-----------------------------------------------------------------------
```

* Open the `Web UI url` in your browser, you can view detail information of the experiment and all the submitted trial jobs as shown below. [Here](docs/en_US/Tutorial/WebUI.rst) are more Web UI pages.
* Open the `Web UI url` in your browser, you can view detail information of the experiment and all the submitted trial jobs as shown below. [Here](https://nni.readthedocs.io/en/latest/Tutorial/WebUI.html) are more Web UI pages.

<table style="border: none">
<th><img src="./docs/img/webui-img/full-oview.png" alt="drawing" width="395" height="300"/></th>
Expand Down
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