Readme index update (#4722)

README.md

@@ -11,13 +11,9 @@
 [![Version](https://img.shields.io/github/release/Microsoft/nni.svg)](https://github.com/Microsoft/nni/releases)
 [![Documentation Status](https://readthedocs.org/projects/nni/badge/?version=stable)](https://nni.readthedocs.io/en/stable/?badge=stable)
 
-NNI 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))**. Quick links:
+[<img src="docs/img/readme_banner.png" width="100%"/>](https://nni.readthedocs.io/)
 
-* [Documentation homepage](https://nni.readthedocs.io/)
-* [Installation guide](https://nni.readthedocs.io/en/stable/installation.html)
-* [Tutorials](https://nni.readthedocs.io/en/stable/tutorials.html)
-* [Python API reference](https://nni.readthedocs.io/en/stable/reference/python_api.html)
-* [Releases](https://nni.readthedocs.io/en/stable/release.html)
+NNI 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))**.
 
 ## What's NEW! &nbsp;<a href="#nni-released-reminder"><img width="48" src="docs/img/release_icon.png"></a>
 
@@ -25,11 +21,23 @@ NNI automates feature engineering, neural architecture search, hyperparameter tu
 * **New demo available**: [Youtube entry](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw) | [Bilibili 入口](https://space.bilibili.com/1649051673) - _last updated on May-26-2021_
 * **New webinar**: [Introducing Retiarii: A deep learning exploratory-training framework on NNI](https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html) - _scheduled on June-24-2021_
 * **New community channel**: [Discussions](https://github.com/microsoft/nni/discussions)
-* **New emoticons release**: [nnSpider](./docs/source/Tutorial/NNSpider.md)
+* **New emoticons release**: [nnSpider](https://nni.readthedocs.io/en/latest/sharings/nn_spider.html)
 <div align="center">
-<a href="#nni-spider"><img width="100%" src="docs/img/emoicons/home.svg" /></a>
+<a href="#nni-spider"><img width="100%" src="docs/source/sharings/images/nn_spider/home.svg" /></a>
 </div>
 
+## Installation
+
+See the [NNI installation guide](https://nni.readthedocs.io/en/stable/installation.html) to install from pip, or build from source.
+
+To install the current release:
+
+```
+$ pip install nni
+```
+
+To update NNI to the latest version, add `--upgrade` flag to the above commands.
+
 ## NNI capabilities in a glance
 
 <img src="docs/img/overview.svg" width="100%"/>
@@ -194,41 +202,20 @@ NNI automates feature engineering, neural architecture search, hyperparameter tu
 </tbody>
 </table>
 
-## Installation
-
-See the [NNI installation guide](https://nni.readthedocs.io/en/stable/installation.html) to install from pip, or build from source.
-
-To install the current release:
-
-```
-$ pip install nni
-```
-
-To update NNI to the latest version, add `--upgrade` flag to the above commands.
-  
-## Run your first experiment
-
-<!-- delete this before next release -->
-
-**NOTE:** To run an experiment following instructions below, you need to build NNI from source. Installing from pip won't work until next release.
-
-To run this experiment, you need to have [PyTorch](https://pytorch.org/) (as well as [torchvision](https://pytorch.org/vision/stable/index.html)) installed.
-
-```shell
-$ nnictl hello
-```
-
-It will generate `nni_hello_hpo` folder in your current working directory, which contains a minimum hyper-parameter tuning example. It will also prompt you to run
-
-```shell
-python nni_hello_hpo/main.py
-```
-
-to launch your first NNI experiment. Use the web portal URL shown in the console to monitor the running status of your experiment.
-
 <img src="docs/static/img/webui.gif" alt="webui" width="100%"/>
 
-For more usages, please see [NNI tutorials](https://nni.readthedocs.io/en/stable/tutorials.html).
+## Resources
+
+* [NNI Documentation Homepage](https://nni.readthedocs.io/)
+* [NNI Installation Guide](https://nni.readthedocs.io/en/stable/installation.html)
+* [NNI Examples](https://nni.readthedocs.io/en/latest/examples.html)
+* [Python API Reference](https://nni.readthedocs.io/en/latest/reference/python_api.html)
+* [Releases (Change Log)](https://nni.readthedocs.io/en/latest/release.html)
+* [Related Research and Publications](https://nni.readthedocs.io/en/latest/notes/research_publications.html)
+* [Youtube Channel of NNI](https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw)
+* [Bilibili Space of NNI](https://space.bilibili.com/1649051673)
+* [Webinar of Introducing Retiarii: A deep learning exploratory-training framework on NNI](https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html)
+* [Community Discussions](https://github.com/microsoft/nni/discussions)
 
 ## Contribution guidelines
 

docs/source/conf.py

@@ -236,8 +236,8 @@ html_theme_options = {
 
     # Text to appear at the top of the home page in a "hero" div.
     'heroes': {
-        # We can have heroes for the home pages of HPO, NAS, Compression in future.
-        'index': 'An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning.'
+        'index': 'An open source AutoML toolkit for hyperparameter optimization, neural architecture search, '
+                 'model compression and feature engineering.'
     }
 }
 

docs/source/tutorials.rst → docs/source/examples.rst

-Tutorials
-=========
+Examples
+========
 
 .. TOC
 
@@ -16,6 +16,8 @@ Tutorials
 
 .. ----------------------
 
+More examples can be found in our :githublink:`GitHub repository <nni/examples>`.
+
 .. cardlinkitem::
    :header: HPO Quickstart with PyTorch
    :description: Use HPO to tune a PyTorch FashionMNIST model

docs/source/index.rst

-Neural Network Intelligence
-===========================
+NNI Documentation
+=================
 
 .. toctree::
    :maxdepth: 2
@@ -8,11 +8,10 @@ Neural Network Intelligence
 
    installation
    quickstart
-    Learning NNI <tutorials>
 
 .. toctree::
    :maxdepth: 2
-    :caption: Full-scale Materials
+   :caption: User Guide
    :hidden:
 
    Hyperparameter Optimization <hpo/index>
@@ -26,33 +25,31 @@ Neural Network Intelligence
    :caption: References
    :hidden:
 
-    nnictl Commands <reference/nnictl>
-    Experiment Configuration <reference/experiment_config>
    Python API <reference/python_api>
+   reference/experiment_config
+   reference/nnictl
 
 .. toctree::
    :maxdepth: 2
    :caption: Misc
    :hidden:
 
-    Use Cases and Solutions <sharings/community_sharings>
-    Research and Publications <notes/research_publications>
+   examples
+   sharings/community_sharings
+   notes/research_publications
    notes/build_from_source
-    Contribution Guide <notes/contributing>
-    Change Log <release>
+   notes/contributing
+   release
 
 **NNI (Neural Network Intelligence)** is a lightweight but powerful toolkit to help users **automate**:
 
-* :doc:`Hyperparameter Tuning </hpo/overview>`,
-* :doc:`Neural Architecture Search </nas/index>`,
-* :doc:`Model Compression </compression/index>`,
-* :doc:`Feature Engineering </feature_engineering/overview>`.
+* :doc:`Hyperparameter Optimization </hpo/overview>`
+* :doc:`Neural Architecture Search </nas/index>`
+* :doc:`Model Compression </compression/index>`
+* :doc:`Feature Engineering </feature_engineering/overview>`
 
-.. Can't use section title here due to the limitation of toc
-
-.. raw:: html
-   
-   <h2>Get Started Now</h2>
+Get Started
+-----------
 
 To install the current release:
 
@@ -62,33 +59,27 @@ To install the current release:
 
 See the :doc:`installation guide </installation>` if you need additional help on installation.
 
-Then, please read :doc:`quickstart` and :doc:`tutorials` to start your journey with NNI!
+Try your first NNI experiment
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. Please keep this part sync with readme
+To run your first NNI experiment:
 
-.. raw:: html
+.. code-block:: shell
 
-   <h2>Latest Updates
+   $ nnictl hello
 
-.. image:: ../img/release_icon.png
-   :class: release-icon
+.. note:: you need to have `PyTorch <https://pytorch.org/>`_ (as well as `torchvision <https://pytorch.org/vision/stable/index.html>`_) installed to run this experiment.
 
-.. raw:: html
+To start your journey now, please follow the :doc:`absolute quickstart of NNI <quickstart>`!
 
-   </h2>
+Why choose NNI?
+---------------
 
-* **New release**: `v2.6 is available <https://github.com/microsoft/nni/releases/tag/v2.6>`_ - *released on Jan-19-2022*
-* **New demo available**: `Youtube entry <https://www.youtube.com/channel/UCKcafm6861B2mnYhPbZHavw>`_ | `Bilibili 入口 <https://space.bilibili.com/1649051673>`_ - *last updated on May-26-2021*
-* **New webinar**: `Introducing Retiarii, A deep learning exploratory-training framework on NNI <https://note.microsoft.com/MSR-Webinar-Retiarii-Registration-Live.html>`_ - *scheduled on June-24-2021*
-* **New community channel**: `Discussions <https://github.com/microsoft/nni/discussions>`_
-* **New emoticons release**: :doc:`nnSpider <sharings/nn_spider/index>`
+NNI makes AutoML techniques plug-and-play
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 .. raw:: html
 
-   <h2>Why choose NNI?</h2>
-
-   <h3>NNI makes AutoML techniques plug-and-play.</h3>
-
    <div class="codesnippet-card-container">
 
 .. codesnippetcard::
@@ -227,7 +218,8 @@ Then, please read :doc:`quickstart` and :doc:`tutorials` to start your journey w
 
    </div>
 
-   <h3>NNI eases the effort to scale and manage AutoML experiments.</h3>
+NNI eases the effort to scale and manage AutoML experiments
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 .. codesnippetcard::
    :icon: ../img/thumbnails/training-service-small.svg
@@ -262,9 +254,8 @@ Then, please read :doc:`quickstart` and :doc:`tutorials` to start your journey w
    **Experiment management** provides the power to aggregate and compare tuning results from multiple experiments,
    so that the tuning workflow becomes clean and organized.
 
-.. raw:: html
-
-   <h2>Get Support and Contribute Back</h2>
+Get Support and Contribute Back
+-------------------------------
 
 NNI is maintained on the `NNI GitHub repository <https://github.com/microsoft/nni>`_. We collect feedbacks and new proposals/ideas on GitHub. You can:
 
@@ -284,9 +275,8 @@ NNI is maintained on the `NNI GitHub repository <https://github.com/microsoft/nn
      -
        .. image:: https://github.com/scarlett2018/nniutil/raw/master/wechat.png
 
-.. raw:: html
-
-   <h2>Citing NNI</h2>
+Citing NNI
+----------
 
 If you use NNI in a scientific publication, please consider citing NNI in your references.
 

docs/source/index_zh.rst

-.. 6b958f21bd23025c81836e54a7f4fbe4
+.. 57966d1be5afdd7a7fcb74e7ea25b1ec
 
 ###########################
 Neural Network Intelligence
@@ -12,7 +12,7 @@ Neural Network Intelligence
 
     入门 <quickstart>
     安装 <installation>
-    教程<tutorials>
+    教程<examples>
     自动（超参数）调优 <hpo/index>
     神经网络架构搜索<nas/index>
     模型压缩<compression/index>

docs/source/notes/contributing.rst

@@ -275,7 +275,7 @@ Writing new documents
 
 Other than built-in directives provided by Sphinx, we also provide some custom directives:
 
-* ``.. cardlinkitem::``: A tutorial card, useful in :doc:`../tutorials`.
+* ``.. cardlinkitem::``: A tutorial card, useful in :doc:`/examples`.
 * |githublink_example| or |githublink_example_2|: reference a file on the GitHub. Linked to the same commit id as where the documentation is built.
 
 Writing new tutorials

docs/source/reference/nnictl.rst

-nnictl
-======
+nnictl Commands
+===============
 
 .. argparse::
    :module: nni.tools.nnictl.nnictl

docs/source/reference/python_api.rst

-API Reference
-=============
+Python API Reference
+====================
 
 ..  toctree::
     :maxdepth: 1

docs/source/sharings/community_sharings.rst

@@ -12,3 +12,4 @@ Different from the tutorials and examples in the rest of the document which show
     Feature Engineering <feature_engineering>
     Performance measurement, comparison and analysis <perf_compare>
     Use NNI on Google Colab <nni_colab_support>
+    nnSpider Emoticons <nn_spider>