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Co-authored-by: Lijiao <15910218274@163.com>
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Lijiaoa and lvybriage authored May 25, 2020
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146 changes: 89 additions & 57 deletions docs/en_US/_templates/index.html
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Expand Up @@ -23,6 +23,7 @@
<a href="{{ pathto('TrainingService/PaiMode') }}">OpenPAI</a>,
<a href="{{ pathto('TrainingService/KubeflowMode') }}">Kubeflow</a>,
<a href="{{ pathto('TrainingService/FrameworkControllerMode') }}">FrameworkController on K8S (AKS etc.)</a>
<a href="{{ pathto('TrainingService/DLTSMode') }}">DLWorkspace (aka. DLTS)</a>
and other cloud options.
</p>
<!-- Who should consider using NNI -->
Expand All @@ -41,7 +42,7 @@ <h1 class="title">Who should consider using NNI</h1>
</div>
<!-- nni release to version -->
<div class="inline">
<h3>NNI v1.4 has been released!</h3>
<h3><a href="https://github.com/microsoft/nni/releases">NNI {{ release }} has been released!</a></h3>
<img width="48" src="_static/img/release_icon.png">
</div>
<!-- NNI capabilities in a glance -->
Expand Down Expand Up @@ -104,43 +105,45 @@ <h1 class="title">NNI capabilities in a glance</h1>
<ul class="firstUl">
<li><b>Examples</b></li>
<ul class="circle">
<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.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>
<li><a href="docs/en_US/TrialExample/EfficientNet.md">EfficientNet</a></li>
<a href="docs/en_US/SupportedFramework_Library.md">More...</a><br />
<li><a href="https://github.com/microsoft/nni/tree/master/examples/trials/mnist-pytorch">MNIST-pytorch</li>
</a>
<li><a href="https://github.com/microsoft/nni/tree/master/examples/trials/mnist-tfv1">MNIST-tensorflow</li>
</a>
<li><a href="https://github.com/microsoft/nni/tree/master/examples/trials/mnist-keras">MNIST-keras</li></a>
<li><a href="{{ pathto('TrialExample/GbdtExample') }}">Auto-gbdt</a></li>
<li><a href="{{ pathto('TrialExample/Cifar10Examples') }}">Cifar10-pytorch</li></a>
<li><a href="{{ pathto('TrialExample/SklearnExamples') }}">Scikit-learn</a></li>
<li><a href="{{ pathto('TrialExample/EfficientNet') }}">EfficientNet</a></li>
<a href="{{ pathto('SupportedFramework_Library') }}">More...</a><br />
</ul>
</ul>
</td>
<td align="left">
<a href="{{ pathto('Tuner/BuiltinTuner') }}">Hyperparameter Tuning</a>
<ul class="firstUl">
<b>Exhaustive search</b>
<div><b>Exhaustive search</b></div>
<ul class="circle">
<li><a href="{{ pathto('Tuner/BuiltinTuner#Random') }}">Random Search</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#GridSearch') }}">Grid Search</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#Batch') }}">Batch</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Random Search</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Grid Search</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Batch</a></li>
</ul>
<b>Heuristic search</b>
<div><b>Heuristic search</b></div>
<ul class="circle">
<li><a href="{{ pathto('Tuner/BuiltinTuner#Evolution') }}">Naïve Evolution</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#Anneal') }}">Anneal</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#Hyperband') }}">Hyperband</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Naïve Evolution</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Anneal</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Hyperband</a></li>
</ul>
<b>Bayesian optimization</b>
<div><b>Bayesian optimization</b></div>
<ul class="circle">
<li><a href="{{ pathto('Tuner/BuiltinTuner#BOHB') }}">BOHB</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#TPE') }}">TPE</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#SMAC') }}">SMAC</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#MetisTuner') }}">Metis Tuner</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner#GPTuner') }}">GP Tuner</a> </li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">BOHB</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">TPE</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">SMAC</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">Metis Tuner</a></li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">GP Tuner</a> </li>
</ul>
<b>RL Based</b>
<div><b>RL Based</b></div>
<ul class="circle">
<li><a href="{{ pathto('Tuner/BuiltinTuner#PPOTuner') }}">PPO Tuner</a> </li>
<li><a href="{{ pathto('Tuner/BuiltinTuner') }}">PPO Tuner</a> </li>
</ul>
</ul>
<a href="{{ pathto('NAS/Overview') }}">Neural Architecture Search</a>
Expand All @@ -150,18 +153,21 @@ <h1 class="title">NNI capabilities in a glance</h1>
<li><a href="{{ pathto('NAS/DARTS') }}">DARTS</a></li>
<li><a href="{{ pathto('NAS/PDARTS') }}">P-DARTS</a></li>
<li><a href="{{ pathto('NAS/CDARTS') }}">CDARTS</a></li>
<li><a href="{{ pathto('NAS/SPOS') }}">SPOS</a></li>
<li><a href="{{ pathto('NAS/Proxylessnas') }}">ProxylessNAS</a></li>
<li><a href="{{ pathto('Tuner/NetworkmorphismTuner') }}">Network Morphism</a> </li>
<li><a href="{{ pathto('NAS/TextNAS') }}">TextNAS</a> </li>
</ul>
</ul>
<a href="{{ pathto('Compressor/Overview') }}">Model Compression</a>
<ul class="firstUl">
<b>Pruning</b>
<div><b>Pruning</b></div>
<ul class="circle">
<li><a href="{{ pathto('Compressor/Pruner') }}">AGP Pruner</a></li>
<li><a href="{{ pathto('Compressor/Pruner') }}">Slim Pruner</a></li>
<li><a href="{{ pathto('Compressor/Pruner') }}">FPGM Pruner</a></li>
</ul>
<b>Quantization</b>
<div><b>Quantization</b></div>
<ul class="circle">
<li><a href="{{ pathto('Compressor/Quantizer') }}">QAT Quantizer</a></li>
<li><a href="{{ pathto('Compressor/Quantizer') }}">DoReFa Quantizer</a></li>
Expand All @@ -172,10 +178,10 @@ <h1 class="title">NNI capabilities in a glance</h1>
<li><a href="{{ pathto('FeatureEngineering/GradientFeatureSelector') }}">GradientFeatureSelector</a></li>
<li><a href="{{ pathto('FeatureEngineering/GBDTSelector') }}">GBDTSelector</a></li>
</ul>
<a href="{{ pathto('FeatureEngineering/BuiltinAssessor') }}">Early Stop Algorithms</a>
<a href="{{ pathto('Assessor/BuiltinAssessor') }}">Early Stop Algorithms</a>
<ul class="circle">
<li><a href="{{ pathto('FeatureEngineering/BuiltinAssessor') }}">Median Stop</a></li>
<li><a href="{{ pathto('FeatureEngineering/BuiltinAssessor') }}">Curve Fitting</a></li>
<li><a href="{{ pathto('Assessor/BuiltinAssessor') }}">Median Stop</a></li>
<li><a href="{{ pathto('Assessor/BuiltinAssessor') }}">Curve Fitting</a></li>
</ul>
</td>
<td>
Expand All @@ -187,7 +193,9 @@ <h1 class="title">NNI capabilities in a glance</h1>
<li><a href="{{ pathto('TrainingService/PaiMode') }}">OpenPAI</a></li>
<li><a href="{{ pathto('TrainingService/KubeflowMode') }}">Kubeflow</a></li>
<li><a href="{{ pathto('TrainingService/FrameworkControllerMode') }}">FrameworkController on K8S
(AKSetc.)</a></li>
(AKSetc.)</a>
</li>
<li><a href="{{ pathto('TrainingService/DLTSMode') }}">DLWorkspace (aka. DLTS)</a></li>
</ul>
</ul>
</td>
Expand Down Expand Up @@ -231,17 +239,18 @@ <h2 class="second-title">Install</h2>
<div class="command">python3 -m pip install --upgrade nni</div>
<div class="command-intro">Windows</div>
<div class="command">python -m pip install --upgrade nni</div>
<p class="topMargin">If you want to try latest code, please <a href="{{ pathto('Tutorial/Installation') }}">install
<p class="topMargin">If you want to try latest code, please <a href="{{ pathto('Installation') }}">install
NNI</a> from source code.
</p>
<p>For detail system requirements of NNI, please refer to <a href="{{ pathto('Tutorial/Installation') }}">here</a> for Linux & macOS, and <a href="{{ pathto('Tutorial/InstallationWin') }}">here</a> for Windows.</p>
<p>For detail system requirements of NNI, please refer to <a href="{{ pathto('Tutorial/InstallationLinux') }}">here</a>
for Linux & macOS, and <a href="{{ pathto('Tutorial/InstallationWin') }}">here</a> for Windows.</p>
</div>
<div>
<p>Note:</p>
<ul>
<li>If there is any privilege issue, add --user to install NNI in the user directory.</li>
<li>Currently NNI on Windows supports local, remote and pai mode. Anaconda or Miniconda is highly
recommended to install NNI on Windows.</li>
recommended to install <a href="">NNI on Windows</a>.</li>
<li>If there is any error like Segmentation fault, please refer to <a
href="{{ pathto('Tutorial/Installation') }}">FAQ</a>. For FAQ on Windows, please refer
to NNI on Windows.</li>
Expand All @@ -256,7 +265,7 @@ <h2 class="second-title">Verify installation</h2>
<ul>
<li>
<p>Download the examples via clone the source code.</p>
<div class="command">python3 -m pip install --upgrade nni</div>
<div class="command">git clone -b v1.5 https://github.com/Microsoft/nni.git</div>
</li>
<li>
<p>Run the MNIST example.</p>
Expand Down Expand Up @@ -317,8 +326,7 @@ <h1 class="title">Documentation</h1>
<ul>
<li>To learn about what's NNI, read the <a href="{{ pathto('Overview') }}">NNI Overview</a>.</li>
<li>To get yourself familiar with how to use NNI, read the <a href="{{ pathto('index') }}">documentation</a>.</li>
<li>To get started and install NNI on your system, please refer to <a href="{{ pathto('Overview') }}"></a>Install
NNI.</li>
<li>To get started and install NNI on your system, please refer to <a href="{{ pathto('Installation') }}">Install NNI</a>.</li>
</ul>
</div>

Expand All @@ -340,7 +348,7 @@ <h1 class="title">Contributing</h1>
This project has adopted the <a href="https://opensource.microsoft.com/codeofconduct/">Microsoft Open Source Code of
Conduct</a>. For more information see the Code of
<a href="https://opensource.microsoft.com/codeofconduct/faq/">Conduct FAQ</a> or contact <a
href="opencode@microsoft.com">opencode@microsoft.com</a> with any additional questions or comments.
href="mailto:opencode@microsoft.com">opencode@microsoft.com</a> with any additional questions or comments.
</p>
<p>
After getting familiar with contribution agreements, you are ready to create your first PR =), follow the NNI
Expand All @@ -367,8 +375,7 @@ <h1 class="title">Contributing</h1>
<li><a href="{{ pathto('Tuner/CustomizeTuner') }}">Customize your own Tuner</a></li>
<li><a href="{{ pathto('TrainingService/HowToImplementTrainingService') }}">Implement customized TrainingService</a>
</li>
<!-- TODO: need to add a link -->
<li>Implement a new NAS trainer on NNI</li>
<li><a href="{{ pathto('NAS/Advanced') }}">Implement a new NAS trainer on NNI</a></li>
<li><a href="{{ pathto('Tuner/CustomizeAdvisor') }}">Customize your own Advisor</a></li>
</ul>
</div>
Expand All @@ -379,10 +386,12 @@ <h1 class="title">External Repositories and References</h1>
<p>With authors' permission, we listed a set of NNI usage examples and relevant articles.</p>
<ul>
<h2>External Repositories</h2>
<li>Run <a href="https://github.com/microsoft/nni/blob/master/examples/tuners/enas_nni/README.md"></a>ENAS with
NNI</li>
<li>Run Neural Network Architecture Search with NNI</li>
<li>Automatic Feature Engineering with NNI</li>
<li>Run <a href="{{ pathto('NAS/ENAS') }}">ENAS</a> with NNI</li>
<li>
<a
href="https://github.com/microsoft/nni/blob/master/examples/feature_engineering/auto-feature-engineering/README.md">Automatic
Feature Engineering</a> with NNI
</li>
<li><a
href="https://github.com/microsoft/recommenders/blob/master/notebooks/04_model_select_and_optimize/nni_surprise_svd.ipynb">Hyperparameter
Tuning for Matrix Factorization</a> with NNI</li>
Expand All @@ -393,41 +402,64 @@ <h2>External Repositories</h2>
<!-- Relevant Articles -->
<ul>
<h2>Relevant Articles</h2>
<li><a href="{{pathto('CommunitySharings/HpoComparision')}}">Hyper Parameter Optimization Comparison</a></li>
<li><a href="{{pathto('CommunitySharings/NasComparision')}}">Neural Architecture Search Comparison</a></li>
<li><a href="{{pathto('CommunitySharings/ParallelizingTpeSearch')}}">Parallelizing a Sequential Algorithm TPE</a>
<li><a href="{{ pathto('CommunitySharings/HpoComparision') }}">Hyper Parameter Optimization Comparison</a></li>
<li><a href="{{ pathto('CommunitySharings/NasComparision') }}">Neural Architecture Search Comparison</a></li>
<li><a href="{{ pathto('CommunitySharings/ParallelizingTpeSearch') }}">Parallelizing a Sequential Algorithm TPE</a>
</li>
<li><a href="{{pathto('CommunitySharings/RecommendersSvd')}}">Automatically tuning SVD with NNI</a></li>
<li><a href="{{pathto('CommunitySharings/SptagAutoTune')}}">Automatically tuning SPTAG with NNI</a></li>
<li><a href="{{ pathto('CommunitySharings/RecommendersSvd') }}">Automatically tuning SVD with NNI</a></li>
<li><a href="{{ pathto('CommunitySharings/SptagAutoTune') }}">Automatically tuning SPTAG with NNI</a></li>
<li><a
href="https://towardsdatascience.com/find-thy-hyper-parameters-for-scikit-learn-pipelines-using-microsoft-nni-f1015b1224c1">
Find thy hyper-parameters for scikit-learn pipelines using Microsoft NNI
</a></li>
<li>
Blog (in Chinese) -
<a
href="http://gaocegege.com/Blog/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/katib-new#%E6%80%BB%E7%BB%93%E4%B8%8E%E5%88%86%E6%9E%90">
Blog (in Chinese) - AutoML tools (Advisor, NNI and Google Vizier) comparison by @gaocegege - 总结与分析 section
of design and implementation of kubeflow/katib
AutoML tools (Advisor, NNI and Google Vizier) comparison
</a>
by @gaocegege - 总结与分析 section of design and implementation of kubeflow/katib
</li>
<li>
<a href="https://mp.weixin.qq.com/s/7_KRT-rRojQbNuJzkjFMuA">
Blog (in Chinese) - A summary of NNI new capabilities in 2019 by @squirrelsc</li>
</a>
Blog (in Chinese) -
<a href="https://mp.weixin.qq.com/s/7_KRT-rRojQbNuJzkjFMuA">A summary of NNI new capabilities in 2019</a> by @squirrelsc
</li>
</ul>
</div>

<!-- feedback -->
<div>
<h1 class="title">Feedback</h1>
<ul>
<li><a href="https://github.com/microsoft/nni/issues/new/choose">File an issue</a> on GitHub.</li>
<li>Ask a question with NNI tags on <a
href="https://stackoverflow.com/questions/tagged/nni?sort=Newest&edited=true">Stack Overflow</a>.
</li>
<li>Discuss on the NNI <a
href="https://gitter.im/Microsoft/nni?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge">Gitter</a>
in NNI.</li>
<li><a href="https://github.com/microsoft/nni/issues/new/choose">File an issue</a> on GitHub.</li>
<li>Ask a question with NNI tags on <a
href="https://stackoverflow.com/questions/tagged/nni?sort=Newest&edited=true">Stack Overflow</a>.</li>
</ul>
<div>
<div>Join IM discussion groups:</div>
<table border=1 style="border-collapse: collapse;">
<tbody>
<tr style="line-height: 30px;">
<th>Gitter</th>
<td></td>
<th>WeChat</th>
</tr>
<tr>
<td>
<img src="https://user-images.githubusercontent.com/39592018/80665738-e0574a80-8acc-11ea-91bc-0836dc4cbf89.png" alt="Gitter" />
</td>
<td width="80" align="center">OR</td>
<td>
<img src="https://github.com/JSong-Jia/NNI-user-group/blob/master/user%20group%20code_0512.png" alt="NNI Wechat" />
</td>
</tr>
</tbody>
</table>
</div>
</div>

<!-- Related Projects -->
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2 changes: 1 addition & 1 deletion docs/en_US/conf.py
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# The short X.Y version
version = ''
# The full version, including alpha/beta/rc tags
release = 'v1.4'
release = 'v1.6'

# -- General configuration ---------------------------------------------------

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