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[issue#1270] Update NNI Introduction Board 

[issue#1270] Update NNI Introduction Board
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README.md
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...@@ -28,7 +28,9 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search ...@@ -28,7 +28,9 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search
<tbody> <tbody>
<tr align="center" valign="bottom"> <tr align="center" valign="bottom">
<td> <td>
<b>Supported Frameworks</b> </td>
<td>
<b>Frameworks & Libraries</b>
<img src="docs/img/bar.png"/> <img src="docs/img/bar.png"/>
</td> </td>
<td> <td>
...@@ -42,26 +44,52 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search ...@@ -42,26 +44,52 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search
</tr> </tr>
</tr> </tr>
<tr valign="top"> <tr valign="top">
<td align="center" valign="middle">
<b>Built-in</b>
</td>
<td> <td>
<ul><li><b>Supported Frameworks</b></li>
<ul> <ul>
<li>PyTorch</li> <li>PyTorch</li>
<li>TensorFlow</li>
<li>Keras</li> <li>Keras</li>
<li>TensorFlow</li>
<li>MXNet</li> <li>MXNet</li>
<li>Caffe2</li> <li>Caffe2</li>
<li>CNTK (Python language)</li> <a href="docs/en_US/SupportedFramework_Library.md">More...</a><br/>
<li>Chainer</li> </ul>
<li>Theano</li> </ul>
<ul>
<li><b>Supported Libraries</b></li>
<ul>
<li>Scikit-learn</li>
<li>XGBoost</li>
<li>LightGBM</li>
<a href="docs/en_US/SupportedFramework_Library.md">More...</a><br/>
</ul>
</ul>
<ul>
<li><b>Examples</b></li>
<ul>
<li><a href="examples/trials/mnist-distributed-pytorch">MNIST-pytorch</li></a>
<li><a href="examples/trials/mnist-distributed">MNIST-tensorflow</li></a>
<li><a href="examples/trials/mnist-keras">MNIST-keras</li></a>
<li><a href="docs/en_US/TrialExample/GbdtExample.md">Auto-gbdt</a></li>
<li><a href="docs/en_US/TrialExample/Cifar10Examples.md">Cifar10-pytorch</li></a>
<li><a href="docs/en_US/TrialExample/SklearnExamples.md">Scikit-learn</a></li>
<a href="docs/en_US/SupportedFramework_Library.md">More...</a><br/>
</ul>
</ul> </ul>
</td> </td>
<td align="left"> <td align="left" >
<a href="docs/en_US/Tuner/BuiltinTuner.md">Tuner</a> <a href="docs/en_US/Tuner/BuiltinTuner.md">Tuner</a>
<br />
<ul> <ul>
<b style="margin-left:-20px">General Tuner</b> <li><b>General Tuner</b></li>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#Random">Random Search</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#Random">Random Search</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#Evolution">Naïve Evolution</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#Evolution">Naïve Evolution</a></li>
<b style="margin-left:-20px">Tuner for HPO</b> </ul>
<li><b>Tuner for <a href="docs/en_US/CommunitySharings/HpoComparision.md">HPO</a></b></li>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#TPE">TPE</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#TPE">TPE</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#Anneal">Anneal</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#Anneal">Anneal</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#SMAC">SMAC</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#SMAC">SMAC</a></li>
...@@ -71,15 +99,20 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search ...@@ -71,15 +99,20 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#MetisTuner">Metis Tuner</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#MetisTuner">Metis Tuner</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#BOHB">BOHB</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#BOHB">BOHB</a></li>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#GPTuner">GP Tuner</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#GPTuner">GP Tuner</a></li>
<b style="margin-left:-20px">Tuner for NAS</b> </ul>
<li><b>Tuner for <a href="docs/en_US/CommunitySharings/NasComparision.md">NAS</a></b></li>
<ul>
<li><a href="docs/en_US/Tuner/BuiltinTuner.md#NetworkMorphism">Network Morphism</a></li> <li><a href="docs/en_US/Tuner/BuiltinTuner.md#NetworkMorphism">Network Morphism</a></li>
<li><a href="examples/tuners/enas_nni/README.md">ENAS</a></li> <li><a href="examples/tuners/enas_nni/README.md">ENAS</a></li>
</ul> </ul>
</ul>
<a href="docs/en_US/Assessor/BuiltinAssessor.md">Assessor</a> <a href="docs/en_US/Assessor/BuiltinAssessor.md">Assessor</a>
<ul> <ul>
<ul>
<li><a href="docs/en_US/Assessor/BuiltinAssessor.md#Medianstop">Median Stop</a></li> <li><a href="docs/en_US/Assessor/BuiltinAssessor.md#Medianstop">Median Stop</a></li>
<li><a href="docs/en_US/Assessor/BuiltinAssessor.md#Curvefitting">Curve Fitting</a></li> <li><a href="docs/en_US/Assessor/BuiltinAssessor.md#Curvefitting">Curve Fitting</a></li>
</ul> </ul>
</ul>
</td> </td>
<td> <td>
<ul> <ul>
...@@ -93,11 +126,40 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search ...@@ -93,11 +126,40 @@ The tool dispatches and runs trial jobs generated by tuning algorithms to search
</ul> </ul>
</td> </td>
</tr> </tr>
<tr align="center" valign="bottom">
</td>
</tr>
<tr valign="top">
<td valign="middle">
<b>References</b>
</td>
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="docs/en_US/sdk_reference.rst">Python API</a></li>
<li><a href="docs/en_US/Tutorial/AnnotationSpec.md">NNI Annotation</a></li>
<li><a href="docs/en_US/Tutorial/Installation.md">Supported OS</a></li>
</ul>
</td>
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="docs/en_US/Tuner/CustomizeTuner.md">CustomizeTuner</a></li>
<li><a href="docs/en_US/Assessor/CustomizeAssessor.md">CustomizeAssessor</a></li>
</ul>
</td>
<td style="border-top:#FF0000 solid 0px;">
<ul>
<li><a href="docs/en_US/TrainingService/SupportTrainingService.md">Support TrainingService</li>
<li><a href="docs/en_US/TrainingService/HowToImplementTrainingService.md">Implement TrainingService</a></li>
</ul>
</td>
</tr>
</tbody> </tbody>
</table> </table>
## **Who should consider using NNI** ## **Who should consider using NNI**
* Those who want to try different AutoML algorithms in their training code (model) at their local machine. * Those who want to try different AutoML algorithms in their training code (model) at their local machine.
...@@ -235,60 +297,69 @@ Maybe you want to read: ...@@ -235,60 +297,69 @@ Maybe you want to read:
* [NNI overview](docs/en_US/Overview.md) * [NNI overview](docs/en_US/Overview.md)
* [Quick start](docs/en_US/Tutorial/QuickStart.md) * [Quick start](docs/en_US/Tutorial/QuickStart.md)
* [Contributing](docs/en_US/Tutorial/Contributing.md)
* [Examples](docs/en_US/examples.rst)
* [References](docs/en_US/reference.rst)
* [WebUI tutorial](docs/en_US/Tutorial/WebUI.md) * [WebUI tutorial](docs/en_US/Tutorial/WebUI.md)
* [Contributing](docs/en_US/Tutorial/Contributing.md)
## **How to** ## **How to**
* [Install NNI](docs/en_US/Tutorial/Installation.md) * [Install NNI](docs/en_US/Tutorial/Installation.md)
* [Use command line tool nnictl](docs/en_US/Tutorial/Nnictl.md) * [Use command line tool nnictl](docs/en_US/Tutorial/Nnictl.md)
* [Use NNIBoard](docs/en_US/Tutorial/WebUI.md) * [Define a trial](docs/en_US/TrialExample/Trials.md)
* [How to define search space](docs/en_US/Tutorial/SearchSpaceSpec.md)
* [How to define a trial](docs/en_US/TrialExample/Trials.md)
* [How to choose tuner/search-algorithm](docs/en_US/Tuner/BuiltinTuner.md)
* [Config an experiment](docs/en_US/Tutorial/ExperimentConfig.md) * [Config an experiment](docs/en_US/Tutorial/ExperimentConfig.md)
* [How to use annotation](docs/en_US/TrialExample/Trials.md#nni-python-annotation) * [Define search space](docs/en_US/Tutorial/SearchSpaceSpec.md)
* [choose tuner/search-algorithm](docs/en_US/Tuner/BuiltinTuner.md)
* [Use annotation](docs/en_US/TrialExample/Trials.md#nni-python-annotation)
* [Use NNIBoard](docs/en_US/Tutorial/WebUI.md)
## **Tutorials** ## **Tutorials**
* [Run an experiment on local (with multiple GPUs)](docs/en_US/TrainingService/LocalMode.md)
* [Run an experiment on OpenPAI](docs/en_US/TrainingService/PaiMode.md) * [Run an experiment on OpenPAI](docs/en_US/TrainingService/PaiMode.md)
* [Run an experiment on Kubeflow](docs/en_US/TrainingService/KubeflowMode.md) * [Run an experiment on Kubeflow](docs/en_US/TrainingService/KubeflowMode.md)
* [Run an experiment on local (with multiple GPUs)](docs/en_US/TrainingService/LocalMode.md)
* [Run an experiment on multiple machines](docs/en_US/TrainingService/RemoteMachineMode.md) * [Run an experiment on multiple machines](docs/en_US/TrainingService/RemoteMachineMode.md)
* [Try different tuners](docs/en_US/Tuner/BuiltinTuner.md) * [Try different tuners](docs/en_US/Tuner/BuiltinTuner.md)
* [Try different assessors](docs/en_US/Assessor/BuiltinAssessor.md) * [Try different assessors](docs/en_US/Assessor/BuiltinAssessor.md)
* [Implement a customized tuner](docs/en_US/Tuner/CustomizeTuner.md) * [Implement a customized tuner](docs/en_US/Tuner/CustomizeTuner.md)
* [Implement a customized assessor](docs/en_US/Assessor/CustomizeAssessor.md) * [Implement a customized assessor](docs/en_US/Assessor/CustomizeAssessor.md)
* [Implement TrainingService in NNI](docs/en_US/TrainingService/HowToImplementTrainingService.md)
* [Use Genetic Algorithm to find good model architectures for Reading Comprehension task](docs/en_US/TrialExample/SquadEvolutionExamples.md) * [Use Genetic Algorithm to find good model architectures for Reading Comprehension task](docs/en_US/TrialExample/SquadEvolutionExamples.md)
* [Advanced Neural Architecture Search](docs/en_US/AdvancedFeature/AdvancedNas.md)
## **Contribute** ## **Contribute**
This project welcomes contributions and there are many ways in which you can participate in the project, for example: This project welcomes contributions and there are many ways in which you can participate in the project, for example:
* Review [source code changes](https://github.com/microsoft/nni/pulls) * Open [bug reports](https://github.com/microsoft/nni/issues/new/choose).
* Review the [documentation](https://github.com/microsoft/nni/tree/master/docs) and make pull requests for anything from typos to new content * Request a [new feature](https://github.com/microsoft/nni/issues/new/choose).
* Suggest or ask some questions on the [How to Debug](docs/en_US/Tutorial/HowToDebug.md) guidance document.
* Find the issues tagged with ['good first issue'](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) or ['help-wanted'](https://github.com/microsoft/nni/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22), these are simple and easy to start , we recommend new contributors to start with. * Find the issues tagged with ['good first issue'](https://github.com/Microsoft/nni/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) or ['help-wanted'](https://github.com/microsoft/nni/issues?q=is%3Aopen+is%3Aissue+label%3A%22help+wanted%22), these are simple and easy to start , we recommend new contributors to start with.
Before providing your hacks, there are a few simple guidelines that you need to follow:
Before providing your hacks, you can review the [Contributing Instruction](docs/en_US/Tutorial/Contributing.md) to get more information. In addition, we also provide you with the following documents:
* [NNI developer environment installation tutorial](docs/en_US/Tutorial/SetupNniDeveloperEnvironment.md)
* [How to debug](docs/en_US/Tutorial/HowToDebug.md) * [How to debug](docs/en_US/Tutorial/HowToDebug.md)
* [Code Styles & Naming Conventions](docs/en_US/Tutorial/Contributing.md) * [Customize Your Own Advisor](docs/en_US/Tuner/CustomizeAdvisor.md)
* How to Set up [NNI developer environment](docs/en_US/Tutorial/SetupNniDeveloperEnvironment.md) * [Customize Your Own Tuner](docs/en_US/Tuner/CustomizeTuner.md)
* Review the [Contributing Instruction](docs/en_US/Tutorial/Contributing.md) and get familiar with the NNI Code Contribution Guideline * [Implement customized TrainingService](docs/en_US/TrainingService/HowToImplementTrainingService.md)
## **External Repositories** ## **External Repositories**
Now we have some external usage examples run in NNI from our contributors. Thanks our lovely contributors. And welcome more and more people to join us! Now we have some external usage examples run in NNI from our contributors. Thanks our lovely contributors. And welcome more and more people to join us!
* Run [ENAS](examples/tuners/enas_nni/README.md) in NNI * Run [ENAS](examples/tuners/enas_nni/README.md) in NNI
* Run [Neural Network Architecture Search](examples/trials/nas_cifar10/README.md) in NNI * Run [Neural Network Architecture Search](examples/trials/nas_cifar10/README.md) in NNI
* [Automatic Feature Engineering](examples/trials/auto-feature-engineering/README.md) in NNI
## **Feedback** ## **Feedback**
* Open [bug reports](https://github.com/microsoft/nni/issues/new/choose).<br/>
* Request a [new feature](https://github.com/microsoft/nni/issues/new/choose).
* Discuss on the NNI [Gitter](https://gitter.im/Microsoft/nni?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) in NNI * Discuss on the NNI [Gitter](https://gitter.im/Microsoft/nni?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) in NNI
* Ask a question with NNI tags on [Stack Overflow](https://stackoverflow.com/questions/tagged/nni?sort=Newest&edited=true)or [file an issue](https://github.com/microsoft/nni/issues/new/choose)on GitHub. * Ask a question with NNI tags on [Stack Overflow](https://stackoverflow.com/questions/tagged/nni?sort=Newest&edited=true)
* We are in construction of the instruction for [How to Debug](docs/en_US/Tutorial/HowToDebug.md), you are also welcome to contribute questions or suggestions on this area. * [File an issue](https://github.com/microsoft/nni/issues/new/choose) on GitHub.
## **License** ## **License**
The entire codebase is under [MIT license](LICENSE) The entire codebase is under [MIT license](LICENSE)
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