Fix version module and add latest release notes; update some doc indexes and menus (#3714)

* Release notes 0.26.0-rc.3 and revise bridges overview * Fix version module and add latest release notes; update some doc menus * Let release notes be discoverable * Documentation master index * Documentation index pg * Update ops for version * Update illustration * Remove old illustration * Add note for 0-rc.4 * Add section on NGRAPH_PROFILE_PASS to backend API * rc-0.5 * Final preview 0.26 release notes * Note changes on Sum validation * Fix link syntax that breaks on Sphinx 3.0 * Revert file that triggers unnecessary review * Typo fix * PR feedback * Consistency on section title capitalizations * Update link * Section title consistency

Fix version module and add latest release notes; update some doc indexes and menus (#3714)
* Release notes 0.26.0-rc.3 and revise bridges overview * Fix version module and add latest release notes; update some doc menus * Let release notes be discoverable * Documentation master index * Documentation index pg * Update ops for version * Update illustration * Remove old illustration * Add note for 0-rc.4 * Add section on NGRAPH_PROFILE_PASS to backend API * rc-0.5 * Final preview 0.26 release notes * Note changes on Sum validation * Fix link syntax that breaks on Sphinx 3.0 * Revert file that triggers unnecessary review * Typo fix * PR feedback * Consistency on section title capitalizations * Update link * Section title consistency
18d20b7b · Leona C · Scott Cyphers · b7a87656 · 18d20b7b · 18d20b7b
Commit 18d20b7b authored Oct 10, 2019 by Leona C Committed by Scott Cyphers Oct 10, 2019
30 changed files
--- a/doc/sphinx/ngraph_theme/layout.html
+++ b/doc/sphinx/ngraph_theme/layout.html
@@ -84,9 +84,9 @@
 <body> 
  <div id="menu-float" class="menu-float">
-    <a href="https://www.ngraph.ai">Home</a>
+    <a href="https://www.ngraph.ai" target="_blank">Home</a>
-    <a href="https://www.youtube.com/embed/C9S0nmNS8bQ">Video</a>
+    <a href="https://www.youtube.com/embed/C9S0nmNS8bQ" target="_blank">Video</a>
-    <a href="https://www.ngraph.ai/ecosystem">Ecosystem</a>
+    <a href="https://www.ngraph.ai/ecosystem" target="_blank">Ecosystem</a>
    <a href="https://ngraph.nervanasys.com/docs/latest">Docs</a>
    <a href="https://www.ngraph.ai/tutorials">Tutorials</a>
    <a href="https://ngraph.slack.com/"><img src="https://cdn.brandfolder.io/5H442O3W/as/pl546j-7le8zk-5h439l/Slack_Mark_Monochrome_White.png?width=35&height=35"></a>

--- a/doc/sphinx/ngraph_theme/ngversions.html
+++ b/doc/sphinx/ngraph_theme/ngversions.html
@@ -10,13 +10,12 @@
        <dd><!-- Until our https://docs.ngraph.ai/ publishing is set up, we link to GitHub -->  
          <ul>
           <!-- <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.26">0.26</a></li> -->
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.26.0">0.26.0</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.26.0-rc.3">Prerelease 0.26</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.26.0">0.25.1</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.25.1-rc.4">0.25.1</a></li>
           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.25.0">0.25.0</a></li>
           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.24.0">0.24.0</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.23.0">0.23.0</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.22.2-rc.0">0.22.2</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.22.0">0.22.0</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.22.1">0.22.1</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.21.0">0.21.0</a></li>
         </ul></dd>
      </dl>
      <dl>

--- a/doc/sphinx/ngraph_theme/static/css/theme.css
+++ b/doc/sphinx/ngraph_theme/static/css/theme.css
@@ -1645,6 +1645,7 @@ h1 {
 h2 {
  font-size: 133%;
  text-decoration: underline 4px dotted #D3D3D3;
+  margin-top: -2px;
 }
 h2, .rst-content .toctree-wrapper p.caption {

--- a/doc/sphinx/source/backends/index.rst
+++ b/doc/sphinx/source/backends/index.rst
@@ -51,7 +51,7 @@ How to use?
 #. A single iteration of the executable is executed by calling the ``call``
   method on the ``Executable`` object.
-.. figure:: ../graphics/execution-interface.png
+.. figure:: ../graphics/ExecutionInterfaceRunGraphs.png
   :width: 650px
   The execution interface for nGraph 
@@ -69,6 +69,13 @@ interface; each backend implements the following five functions:
 * And, finally, the ``call()`` method is used to invoke an nGraph function 
  against a particular set of tensors.
+How to display ngraph-related passes executed during runtime?
+-------------------------------------------------------------
+One easy way to get info about passes is to set the environment variable 
+:envvar:`NGRAPH_PROFILE_PASS_ENABLE=1`. With this set, the pass manager 
+will dump the name and execution time of each pass.
 .. _ngraph_bridge:

--- a/doc/sphinx/source/core/constructing-graphs/index.rst
+++ b/doc/sphinx/source/core/constructing-graphs/index.rst
-.. howto/index: 
+.. core/constructing-graphs/index.rst:
-Constructing graphs
+.. _constructing_graphs:
+Constructing Graphs
 ===================
 .. toctree::

--- a/doc/sphinx/source/core/fusion/index.rst
+++ b/doc/sphinx/source/core/fusion/index.rst
 .. fusion/index.rst:
-Pattern matcher
+Pattern Matcher
 ###############
 .. toctree::

--- a/doc/sphinx/source/core/fusion/overview.rst
+++ b/doc/sphinx/source/core/fusion/overview.rst
-.. fusion/overview.rst
+.. core/fusion/overview.rst
+.. _fusion_overview:
 Overview: Optimize graphs with nGraph Compiler fusions
 -------------------------------------------------------

--- a/doc/sphinx/source/core/overview.rst
+++ b/doc/sphinx/source/core/overview.rst
 .. core/overview.rst:
-Overview
+Basic concepts
-========
+==============
-.. figure:: ../graphics/whole-stack.png
+.. figure:: ../graphics/nGraphCompilerstack.png
   :alt: The whole stack
   The whole nGraph Compiler stack  
@@ -13,7 +13,7 @@ The nGraph Compiler stack consists of bridges, core, and backends. We'll examine
 each of these briefly to get started. 
 A framework bridge interfaces with the "frontend" Core API. A framework bridge 
-is a component that sits between a framework like TensorFlow or MXNet, and the
+is a component that sits between a framework like TensorFlow or PaddlePaddle, and the
 nGraph Core frontend API. A framework bridge does two things: first, it 
 translates a framework's operations into graphs in nGraph’s in-memory 
 :abbr:`Intermediary Representation (IR)`. Second, it executes the nGraph IR 
@@ -24,8 +24,9 @@ are some common patterns: a fairly typical example for a graph-based framework
 is illustrated here, and consists of basically two phases: a **clustering** 
 phase and a **translation** phase.
-.. figure:: ../graphics/translation-flow-to-ng-fofx.png
+.. figure:: ../graphics/overview-translation-flow.svg
-   :alt: The whole stack
+   :width: 725px
+   :alt: Translation flow to an nGraph function graph
   Translation flow to an nGraph function 

--- a/doc/sphinx/source/core/passes/passes-that-use-matcher.rst
+++ b/doc/sphinx/source/core/passes/passes-that-use-matcher.rst
-.. fusion/passes-that-use-matcher.rst:
+.. core/passes/passes-that-use-matcher.rst:
 Passes that use Matcher

--- a/doc/sphinx/source/core/passes/passes.rst
+++ b/doc/sphinx/source/core/passes/passes.rst
-.. core/passes:
+.. core/passes/passes.rst:
-Compiler passes
+.. _core_compiler_passes:
+Compiler Passes
 ===============
 .. toctree::
@@ -11,9 +13,8 @@ Compiler passes
   passes-that-use-matcher.rst
+Basic concepts
-Overview
+--------------
--------
 *Generic graph optimization passes*

--- a/doc/sphinx/source/frameworks/fw_overview.rst
+++ b/doc/sphinx/source/frameworks/fw_overview.rst
+:orphan: 
+.. frameworks/fw_overview:
+.. _fw_overview:
+Overview
+========
+A framework is "supported" with a framework :term:`bridge` that can be written or
+cloned and used to connect to nGraph device backends while maintaining the 
+framework's programmatic or user interface. There is a bridge for the 
+`TensorFlow framework`_. We also have a :doc:`paddle_integ` bridge. Intel 
+previously contributed work to an MXNet bridge; however, support for this 
+bridge is no longer active.
+`ONNX`_ on its own is not a framework; however, it can be used with nGraph's
+:doc:`../python_api/index` to import and execute ONNX models.
+.. figure:: ../graphics/overview-framework-bridges.svg
+   :width: 960px
+   :alt: Framework bridge to a graph construction
+   Framework bridge to nGraph
+Once connected via the bridge, the framework can then run and train a deep
+learning model with various workloads on various backends using nGraph Compiler
+as an optimizing compiler available through the framework.
+While a :abbr:`Deep Learning (DL)` :term:`framework` is ultimately meant for
+end use by data scientists, or for deployment in cloud container environments,
+nGraph Core ops and the nGraph C++ Library are designed for framework builders
+themselves. We invite anyone working on new and novel frameworks or neural
+network designs to explore our highly-modularized stack of components that
+can be implemented or integrated in countless ways.
+Please read this section if you are considering incorporating components from
+the nGraph Compiler stack in your framework or neural network design. Contents
+here are also useful if you are working on something built-from-scratch, or on
+an existing framework that is less widely-supported than the popular frameworks
+like TensorFlow and PyTorch.
+.. figure:: ../graphics/overview-translation-flow.svg
+   :width: 725px
+   :alt: Translation flow to nGraph function graph
+.. _TensorFlow framework: https://github.com/tensorflow/ngraph-bridge/README.md
+.. _ONNX: http://onnx.ai/
+.. _tune the workload to extract best performance: https://ai.intel.com/accelerating-deep-learning-training-inference-system-level-optimizations
+.. _a few small: https://software.intel.com/en-us/articles/boosting-deep-learning-training-inference-performance-on-xeon-and-xeon-phi
--- a/doc/sphinx/source/frameworks/index.rst
+++ b/doc/sphinx/source/frameworks/index.rst
 .. frameworks/index.rst
 Working with Frameworks
-=======================
+#######################
-.. include:: overview.rst
 .. toctree::
   :maxdepth: 1
-   getting_started.rst
+   overview.rst
+   quickstart.rst
   onnx_integ.rst 
   paddle_integ.rst
   tensorflow_connect.rst
-   generic_configs.rst
+   other.rst
--- a/doc/sphinx/source/frameworks/onnx_integ.rst
+++ b/doc/sphinx/source/frameworks/onnx_integ.rst
 .. frameworks/onnx_integ.rst:
-ONNX Support
+ONNX overview
-============
+=============
 nGraph is able to import and execute ONNX models. Models are converted to 
 nGraph's :abbr:`Intermediate Representation (IR)` and converted to ``Function`` 
@@ -78,7 +78,7 @@ data:
 Find more information about nGraph and ONNX in the 
-`nGraph ONNX`_ GitHub\* repository.
+`nGraph ONNX`_ GitHub repository.
 .. _ngraph ONNX: https://github.com/NervanaSystems/ngraph-onnx

--- a/doc/sphinx/source/frameworks/generic_configs.rst
+++ b/doc/sphinx/source/frameworks/generic_configs.rst
-.. frameworks/generic_configs.rst:
+.. frameworks/other.rst:
-.. _generic_configs: 
+.. _fw_other: 
-Integrating new frameworks
+Integrating other frameworks
-==========================
+============================
 This section details some of the *configuration options* and some of the 
 *environment variables* that can be used to tune for optimal performance when 

--- a/doc/sphinx/source/frameworks/overview.rst
+++ b/doc/sphinx/source/frameworks/overview.rst
 .. frameworks/overview.rst
-.. _fw_overview:
+Basic concepts
+==============
-Overview
+.. figure:: ../graphics/overview-framework-bridges.svg
-========
+   :width: 960px
+   :alt: Bridge to nGraph graph construction API
-A framework is "supported" with a framework :term:`bridge` that can be written or
+   A framework bridge connects to the nGraph graph construction API
-cloned and used to connect to nGraph device backends while maintaining the 
-framework's programmatic or user interface. A `bridge currently exists`_ for the 
-TensorFlow framework. We also have a bridge to do :doc:`paddle_integ`.  Intel 
-previously contributed work to an MXNet bridge; however, support for this 
-bridge is no longer active.
-`ONNX`_ on its own is not a framework; however, it can be used with nGraph's
+To understand how a data science :term:`framework` (:doc:`TensorFlow <tensorflow_connect>`, 
-:doc:`../python_api/index` to import and execute ONNX models.
+PyTorch, :doc:`paddle_integ`, and others) can unlock acceleration available in 
+the nGraph Compiler, it helps to familiarize yourself with some basic concepts.
-.. figure:: ../graphics/overview-framework-bridges.svg
+We use the term :term:`bridge` to describe code that connects to any nGraph 
-   :width: 960px
+device backend(s) while maintaining the framework's programmatic or user 
-   :alt: JiT compiling of a computation
+interface. We have a `bridge for the TensorFlow framework`_. We also have a 
+:doc:`paddle_integ` bridge. Intel previously :doc:`contributed work to an MXNet bridge <../project/extras/testing_latency>`; 
+however, support for the MXNet bridge is no longer active. 
+`ONNX`_ on its own is not a framework; it can be used with nGraph's 
+:doc:`../python_api/index` to import and execute ONNX models.
-   :abbr:`Just-in-Time (JiT)` Compiling for computation. nGraph `Core`
+Because it is framework agnostic (providing opportunities to optimize at the 
-   components are colored in blue.
+graph level), nGraph can do the heavy lifting required by many popular 
+:doc:`workloads <validated/list>` without any additional effort of the framework user.
+Optimizations that were previously available only after careful integration of 
+a kernel or hardware-specific library are exposed via the 
+:doc:`Core graph construction API <../core/constructing-graphs/index>`
-Once connected via the bridge, the framework can then run and train a deep
+The illustration above shows how this works. 
-learning model with various workloads on various backends using nGraph Compiler
-as an optimizing compiler available through the framework.
-While a :abbr:`Deep Learning (DL)` :term:`framework` is ultimately meant for
+While a :abbr:`Deep Learning (DL)` framework is ultimately meant for end-use by 
-end use by data scientists, or for deployment in cloud container environments,
+data scientists, or for deployment in cloud container environments, nGraph's 
-nGraph Core ops and the nGraph C++ Library are designed for framework builders
+:doc:`Core ops <../core/overview>` are designed for framework builders themselves. 
-themselves. We invite anyone working on new and novel frameworks or neural
+We invite anyone working on new and novel frameworks or neural network designs 
-network designs to explore our highly-modularized stack of components that
+to explore our highly-modularized stack of components.
-can be implemented or integrated in countless ways.
-Please read this section if you are considering incorporating components from
+Please read the :doc:`other` section for other framework-agnostic 
-the nGraph Compiler stack in your framework or neural network design. Contents
+configurations available to users of the nGraph Compiler stack. 
-here are also useful if you are working on something built-from-scratch, or on
-an existing framework that is less widely-supported than the popular frameworks
-like TensorFlow and PyTorch.
 .. figure:: ../graphics/overview-translation-flow.svg
   :width: 725px
-   :alt: Translation flow to nGraph function graph
+   :alt: Translation flow to an nGraph function graph
-.. _bridge currently exists: https://github.com/tensorflow/ngraph-bridge/README.md
+.. _bridge for the TensorFlow framework: https://github.com/tensorflow/ngraph-bridge/README.md
 .. _ONNX: http://onnx.ai/
 .. _tune the workload to extract best performance: https://ai.intel.com/accelerating-deep-learning-training-inference-system-level-optimizations
 .. _a few small: https://software.intel.com/en-us/articles/boosting-deep-learning-training-inference-performance-on-xeon-and-xeon-phi
\ No newline at end of file
--- a/doc/sphinx/source/frameworks/paddle_integ.rst
+++ b/doc/sphinx/source/frameworks/paddle_integ.rst
 .. frameworks/paddle_integ.rst:
-PaddlePaddle
+PaddlePaddle integration
-============
+========================
-nGraph PaddlePaddle integration overview
----------------------------------------
 PaddlePaddle is an open source deep learning framework developed by Baidu. It 
 aims to enable performant large-scale distributed computation for deep learning. 
@@ -67,7 +64,7 @@ is organized in the following file structure:
 .. _figure-paddle-dir:
-.. figure:: ../graphics/paddlepaddle_directory.png
+.. figure:: ../graphics/PaddlePaddleDir.svg
   :width: 555px
   :alt: 
@@ -135,8 +132,8 @@ and nGraph bridges are provided below:
     are managed through a map.
   - SetOutputNode: sets the constructed node to the map.
   - Related code :
-     + ``Paddle/fluid/operators/ngraph/ngraph_bridge.h`` `link to ngraph_bridge header code`_
+      - ``Paddle/fluid/operators/ngraph/ngraph_bridge.h`` `link to ngraph_bridge header code`_
-     + ``Paddle/fluid/operators/ngraph/ngraph_bridge.cc``  `link to ngraph_bridge cpp code`_
+      - ``Paddle/fluid/operators/ngraph/ngraph_bridge.cc``  `link to ngraph_bridge cpp code`_
 nGraph compilation control and trigger method
 ----------------------------------------------
@@ -149,8 +146,9 @@ nGraph compilation control and trigger method
 #. **Trigger Control** -- ``FLAGS_use_ngraph`` triggers nGraph. If this option 
   is set to ``true``, nGraph will be triggered by the PaddlePaddle executor 
-   to convert and execute the supported subgraph. `Examples are provided`_ under    
+   to convert and execute the supported subgraph. Demos are provided under    
-   ``paddle/benchmark/fluid/ngraph``. 
+   ``paddle/benchmark/fluid/train/demo`` (link `train_demo`_) and ``paddle/benchmark/fluid/train/imdb_demo`` 
+   (link `imdb_demo`_) 
 .. _link to ngraph_engine_op header code: https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/ngraph/ngraph_engine_op.h
@@ -160,5 +158,5 @@ nGraph compilation control and trigger method
 .. _located in the ngraph ops: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/fluid/operators/ngraph/ops
 .. _link to ngraph_bridge header code: https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/ngraph/ngraph_bridge.h
 .. _link to ngraph_bridge cpp code: https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/fluid/operators/ngraph/ngraph_bridge.cc
-.. _Examples are provided: https://github.com/PaddlePaddle/Paddle/tree/develop/benchmark/fluid
+.. _train_demo: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/fluid/train/demo
+.. _imdb_demo: https://github.com/PaddlePaddle/Paddle/tree/develop/paddle/fluid/train/imdb_demo
--- a/doc/sphinx/source/frameworks/getting_started.rst
+++ b/doc/sphinx/source/frameworks/getting_started.rst
-.. frameworks/getting_started.rst
+.. frameworks/quickstart.rst
-Getting Started
+.. _fw_quickstart:
-###############
+Quick start
+===========
 No matter what your level of experience with :abbr:`Deep Learning (DL)` systems 
 may be, nGraph provides a path to start working with the DL stack. Let's begin 
 with the easiest and most straightforward options.
-.. figure:: ../graphics/translation-flow-to-ng-fofx.png
+TensorFlow
-   :width: 725px
+----------
-   :alt: Translation flow to nGraph function graph
 The easiest way to get started is to use the latest PyPI `ngraph-tensorflow-bridge`_,
-which has instructions for Linux* systems, and tips for users of Mac OS X. 
+which has instructions for Linux\* systems, and tips for users of Mac OS X. 
-You can install TensorFlow\* and nGraph to a virtual environment; otherwise, the code 
+You can install TensorFlow and nGraph in a virtual environment; otherwise, the code 
 will install to a system location.
 .. code-block:: console
@@ -43,17 +44,17 @@ Output will look something like:
    TensorFlow version used for this build: v[version-hash]
    CXX11_ABI flag used for this build: boolean
-More detail in the `ngraph_bridge examples`_ directory. 
+More detail in the `ngraph_bridge examples`_ directory.
+See also the `diagnostic tools`_.
 ONNX
-====
+----
 Another easy way to get started working with the :abbr:`DL (Deep Learning)`
 stack is to try the examples available via `nGraph ONNX`_.
-Installation
------------
 To prepare your environment to use nGraph and ONNX, install the Python packages
 for nGraph, ONNX and NumPy:
@@ -67,18 +68,18 @@ Now you can start exploring some of the :doc:`onnx_integ` examples.
 See also nGraph's :doc:`../python_api/index`.
 PlaidML
-=======
+-------
 See the :ref:`ngraph_plaidml_backend` section on how to build the 
 nGraph-PlaidML.
 Other integration paths
-=======================
+-----------------------
 If you are considering incorporating components from the nGraph Compiler stack 
 in your framework or neural network design, another useful doc is the section 
-on :doc:`generic-configs`. Contents here are also useful if you are working on 
+on :doc:`other` . Contents here are also useful if you are working on 
 something built-from-scratch, or on an existing framework that is less 
 widely-supported than the popular frameworks like TensorFlow and PyTorch.
@@ -86,3 +87,4 @@ widely-supported than the popular frameworks like TensorFlow and PyTorch.
 .. _ngraph-tensorflow-bridge: https://pypi.org/project/ngraph-tensorflow-bridge
 .. _ngraph ONNX: https://github.com/NervanaSystems/ngraph-onnx
 .. _ngraph_bridge examples: https://github.com/tensorflow/ngraph-bridge/blob/master/examples/README.md
+.. _diagnostic tools: https://github.com/tensorflow/ngraph-bridge/blob/master/diagnostics/README.md
\ No newline at end of file
--- a/doc/sphinx/source/frameworks/tensorflow_connect.rst
+++ b/doc/sphinx/source/frameworks/tensorflow_connect.rst
 .. frameworks/tensorflow_connect.rst:
-Connect TensorFlow\*
+nGraph Bridge for TensorFlow
-====================
+============================
 See the `README`_ on the `ngraph_bridge repo`_ for the many ways to connect 

--- a/doc/sphinx/source/frameworks/validated/list.rst
+++ b/doc/sphinx/source/frameworks/validated/list.rst
@@ -3,7 +3,7 @@
 .. _validated:
-Validated workloads
+Validated Workloads
 ###################
 We have validated performance [#f1]_ for the following workloads:

--- a/doc/sphinx/source/graphics/ExecutionInterfaceRunGraphs.png
+++ b/doc/sphinx/source/graphics/ExecutionInterfaceRunGraphs.png
--- a/doc/sphinx/source/graphics/PaddlePaddleDir.svg
+++ b/doc/sphinx/source/graphics/PaddlePaddleDir.svg
--- a/doc/sphinx/source/graphics/execution-interface.png
+++ b/doc/sphinx/source/graphics/execution-interface.png
--- a/doc/sphinx/source/graphics/nGraphCompilerstack.png
+++ b/doc/sphinx/source/graphics/nGraphCompilerstack.png
--- a/doc/sphinx/source/index.rst
+++ b/doc/sphinx/source/index.rst
@@ -12,9 +12,9 @@
 .. limitations under the License.
 .. ---------------------------------------------------------------------------
-######################
-nGraph Compiler stack 
+nGraph Compiler stack Documentation 
-######################
+###################################
 .. _ngraph_home:
@@ -23,36 +23,25 @@ nGraph Compiler stack
   nGraph Compiler stack documentation for version |version|.
-   Documentation for the latest (master) development branch can be found 
-   at https://ngraph.nervanasys.com/docs/latest 
-   .. https://docs.ngraph.ai/
 .. only:: (development or daily)
   nGraph Compiler stack documentation for the master tree under development 
   (version |version|).
-The nGraph Library and Compiler stack are provided under the `Apache 2.0 license`_ 
-(found in the LICENSE file in the project's `repo`_). It may also import or reference 
-packages, scripts, and other files that use licensing.
-.. _Apache 2.0 license: https://github.com/NervanaSystems/ngraph/blob/master/LICENSE
-.. _repo: https://github.com/NervanaSystems/ngraph
 .. toctree::
   :name: mastertoctree
   :titlesonly: 
 .. toctree::
   :maxdepth: 1
-   :caption: Getting Started
   introduction.rst
   features.rst
+   project/release-notes.rst
 .. toctree::
-   :maxdepth: 1
+   :maxdepth: 2
   :caption: Framework Support
   frameworks/index.rst
@@ -89,15 +78,20 @@ packages, scripts, and other files that use licensing.
 .. toctree::
   :maxdepth: 1
-   :caption: Project Metadata
+   :caption: Contributing
-   project/release-notes.rst
   project/contribution-guide.rst
-   project/index.rst
-   project/extras/index.rst 
   glossary.rst
+.. toctree::
+   :maxdepth: 1
+   :hidden:
+   project/release-notes.rst
+   project/index.rst
+   project/extras/index.rst 
 .. only:: html

--- a/doc/sphinx/source/ops/index.rst
+++ b/doc/sphinx/source/ops/index.rst
@@ -160,15 +160,30 @@ Not currently a comprehensive list.
 More about Core Ops
 -------------------
-An ``Op``'s primary role is to function as a node in a directed acyclic graph 
+An ``Op``'s primary role is to function as a node in a ddirected acyclic 
-dependency computation graph.  
+computation graph.
 *Core ops* are ops that are available and generally useful to all framework 
 bridges and that can be compiled by all transformers. A framework bridge may 
 define framework-specific ops to simplify graph construction, provided that the 
 bridge can enable every transformer to replace all such ops with equivalent 
-clusters or subgraphs composed of core ops. In a similar manner, transformers may define 
+clusters or subgraphs composed of core ops. In a similar manner, transformers 
-transformer-specific ops to represent kernels or other intermediate operations. 
+may define transformer-specific ops to represent kernels or other intermediate 
+operations. 
+The  input and output ports of ops are any of the functions which work with 
+``Output<Node>/Input<Node>``. Previous functions that worked at the level 
+of ops are deprecated, like::
+   Node::get_element_type()
+as it does not take any input. This function has been replaced with new 
+functions like::
+   Node::get_output_element_type(index) 
+where there is no ambiguity.
 If a framework supports extending the set of ops it offers, a bridge may even 
 expose transformer-specific ops to the framework user.

--- a/doc/sphinx/source/ops/max.rst
+++ b/doc/sphinx/source/ops/max.rst
@@ -44,6 +44,6 @@ Outputs
 C++ Interface
 =============
-.. doxygenclass:: ngraph::op::Max
+.. doxygenclass:: ngraph::op::v0::Max
   :project: ngraph
   :members: m_axes
--- a/doc/sphinx/source/ops/min.rst
+++ b/doc/sphinx/source/ops/min.rst
@@ -44,6 +44,6 @@ Outputs
 C++ Interface
 =============
-.. doxygenclass:: ngraph::op::Min
+.. doxygenclass:: ngraph::op::v0::Min
   :project: ngraph
   :members: m_axes
--- a/doc/sphinx/source/project/contribution-guide.rst
+++ b/doc/sphinx/source/project/contribution-guide.rst
@@ -4,7 +4,7 @@
 .. _contribution_guide:
 ##################
-Contribution guide
+Contribution Guide
 ##################

--- a/doc/sphinx/source/project/release-notes.rst
+++ b/doc/sphinx/source/project/release-notes.rst
@@ -2,6 +2,8 @@
 :orphan:
+.. _release_notes:
 Release Notes
 #############
@@ -18,19 +20,33 @@ We are pleased to announce the release of version |version|.
 Core updates for |version|
 --------------------------
 + All ops support ``Output<Node>`` arguments
 + Additional ops
 + ONNX handling unknown domains
+ Provenance works with builders and fused ops
+ ``RPATH`` for finding openmpi
+ Negative indices/axes fixes
+ Migrate some ``get_argument`` removals
+ Negative indices/axes fixes
+ Better support for MKL-DNN 1.0 (DNNL)
+Latest documentation updates
+----------------------------
-Latest documentation updates for |version|
------------------------------------------
 + Note the only support for nGPU is now through PlaidML; nGraph support for nGPU 
  (via cuDNN) has been deprecated.  
 + iGPU works only with nGraph version `0.24`.
+ Add new Sphinx-friendly theme (can be built natively for an alternative to ngraph.ai docs). 
+ Update PaddlePaddle documentation to reflect demo directories instead of example directory.
+ Update doc regarding the validation of ``Sum`` op.
 .. important:: Pre-releases (``-rc-0.*``) have newer features, and are less stable.  
 Changelog on Previous Releases
 ==============================
@@ -41,7 +57,7 @@ Changelog on Previous Releases
 + Add rank id to trace file name
 + Allow provenance merging to be disabled
 + Remove some white-listed compiler warnings
-+ Provenance on builders and fused op expansions
+ Provenance, builders, ops that make ops, and fused op expansions
 0.25.0
@@ -136,8 +152,8 @@ Changelog on Previous Releases
 + Provenance improvements
-0.19
+pre-0.20
----
+--------
 + More dynamic shape preparation
 + Distributed interface factored out
@@ -153,11 +169,7 @@ Changelog on Previous Releases
 + Add graph visualization tools to doc
 + Update doxygen to be friendlier to frontends
+.. 0.18
-0.18
----
 + Python formatting issue
 + mkl-dnn work-around
 + Event tracing improvements
@@ -166,10 +178,7 @@ Changelog on Previous Releases
 + ONNX quantization
 + More fusions
+.. 0.17
-0.17
----
 + Allow negative padding in more places
 + Add code generation for some quantized ops
 + Preliminary dynamic shape support
@@ -177,10 +186,7 @@ Changelog on Previous Releases
 + Pad op takes CoordinateDiff instead of Shape pad values to allow for negative 
  padding.
+.. 0.16
-0.16
----
 + NodeInput and NodeOutput classes prepare for simplifications of Node
 + Test improvements
 + Additional quantization ops

--- a/doc/sphinx/source/sitemap.rst
+++ b/doc/sphinx/source/sitemap.rst
-:orphan:
-  .. toctree::
-     :includehidden:
-     frameworks/index
-     project/index
-     python_api/index
-     inspection/index
-     core/overview
-     backends/index
-     project/extras/index