Documentation updates for 0.21.0 (#3010)

* WIP more guides and tutorials for the docs

* Update Guides and structure

* Update Guides and structure

+ Test documentation build on Clear Linux OS;
+ Fix a few links and redirs.
+ Note rc-naming conventions in doc may be tag-generalized.

* documentation supports various rc-naming conventions

* Add instructions on building nGraph bridge from src

* Update ngtf bridge versions to 0.14.1 and TensorFlow's bazel dependency to 0.24.1

* Use consistent file naming on all BE indexes

* Fix comma

* Templatize versioning for releases starting 0.20 and add placeholders for changes by components

* Remove typo

* Minor formatting fixed

* Document how to find or display built version of nGraph

* Start a r0.21 for doc that also fixes broken link and typo

* Correct use of console command context for version check

* Minor fixes to doc-contributor-README

* Docs for version 0.21

* Ensure docs build without error

* Assign ownership project README and intro for new ngraph.ai site to Straw

* Note deprecated Tensor API in doc

* Update to generic versioning on core doc for importing via built wheels

* Resolve merge conflicts leftover from v20 version request changes

* remove typo and suggested use of prebuilt LLVM since newer OSes do not have them available

* Update to latest

* Update with review from PR and ngraph bridge team

* Update right section with review from PR and ngraph bridge team

* Ensure doc example folders have owners from the component

* Push edit of tensorflow_connect to v0.22 docs

* Update Python wheel building instructions to newer version

CODEOWNERS

@@ -19,10 +19,15 @@
 
 /doc/                               @indie
 /doc/examples/mnist_mlp/dist_*      @wenzhe-nrv @indie
-/README.md                          @indie
+/doc/*/*/frameworks/tensorflow_connect.rst      @shresthamalik @avijit-nervana @sayantan-nervana
+/doc/*/*/backends/plaidml-ng-api/   @flaub @brianretford @dgkutnic
+/doc/*/*/inspection/                @aproctor
+/doc/examples/onnx/                 @arogowie-intel @tsocha
+/README.md                          @adstraw
+project/introduction.rst            @adstraw
+project/governance.rst              @adstraw
 /changes.md                         @indie @diyessi
-/INSTALL.md                         @indie
-/CONTRIB.md                         @indie
+project/doc-contributor-README.rst  @indie
 
 /licenses/                          @diyessi @raramer01 @aslepko
 /LICENSE                            @diyessi @raramer01 @aslepko

doc/sphinx/conf.py

@@ -73,11 +73,13 @@ author = 'Intel Corporation'
 # built documents.
 #
 # The short X.Y version.
-version = '0.20'
+version = '0.22'
 
 # The Documentation full version, including alpha/beta/rc tags. Some features
-# available in the latest code will not necessarily be documented first
-release = '0.20.0'
+# available in the latest code will not necessarily be documented first.
+# rc syntax may be tagged; this documentation supports various rc-naming conventions 
+
+release = '0.22.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
@@ -121,14 +123,15 @@ else:
 
     # borrow this from the zephyr docs theme
     html_context = {
-        # 'show_license': html_show_license, we have a custom footer to attribute 
+        # 'show_license': html_show_license, we have custom footers to attribute 
         # RTD, WTD, and Sphinx contributors; so we do not enable this
         'docs_title': docs_title,
         'is_release': is_release,
         'theme_logo_only': False,
         'current_version': version,
         'versions': ( ("latest", "../"),
-                     ("0.19.0", "/0.19.0/"), #not yet sure how we'll do this
+                     ("0.20.0", "/0.20.0/"), #not yet sure how we'll do this
+                     ("0.19.0", "/0.19.0/"), 
                      ("0.18.0", "/0.18.0/"),
                      ("0.17.0", "/0.17.0/"),
                      ("0.16.0", "/0.16.0/"),
@@ -167,7 +170,7 @@ html_sidebars = {
 # list of tuples (old_url, new_url) for pages to redirect
 # (URLs should be relative to document root, only)
 html_redirect_pages = [
-        ('backends', 'backend-support/index'),
+        ('backend-support', 'backends/index'),
         ('core/core', 'core/overview.rst'),
         ('core/fusion', 'core/fusion/index'),
         ('frameworks/mxnet', 'frameworks/mxnet_intg.rst'),
@@ -177,6 +180,7 @@ html_redirect_pages = [
         ('inspection/inspection', 'inspection/index'),
         ('releases/release-notes', 'releases/index'),
         # ('getting_started/getting_starting', 'getting_started/index'),
+        #  mv to framework-specific helper directory
         ('project/project', 'project/index'),
         ('python_api/', 'python_api/index'),
 ]

doc/sphinx/ngraph_theme/ngversions.html

@@ -6,9 +6,10 @@
     </span>
     <div class="rst-other-versions">
       <dl>
-        <dt>{{ _('Previous Verified Versions') }}</dt>
+        <dt>{{ _('Previous Versions') }}</dt>
         <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/v0.20.0">0.20.0-rc.0</a></li>
            <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.19.0-rc.2">0.19.0-rc.2</a></li>
            <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.18.1">0.18.1</a></li>
            <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.17.0-rc.1">0.17.0-rc.1</a></li>

doc/sphinx/ngraph_theme/static/theme.css

@@ -2407,9 +2407,10 @@ div[class^='highlight'] pre {
 }
 .rst-content h1 .headerlink:after, .rst-content h2 .headerlink:after, .rst-content .toctree-wrapper p.caption .headerlink:after, .rst-content h3 .headerlink:after, .rst-content h4 .headerlink:after, .rst-content h5 .headerlink:after, .rst-content h6 .headerlink:after, .rst-content dl dt .headerlink:after, .rst-content p.caption .headerlink:after {
   visibility: visible;
-  content: "";
   font-family: "NeoSansIntel";
   display: inline-block;
+  background-color: #27ae41;
+  font-size: 0.93em;
 }
 .rst-content h1:hover .headerlink, .rst-content h2:hover .headerlink, .rst-content .toctree-wrapper p.caption:hover .headerlink, .rst-content h3:hover .headerlink, .rst-content h4:hover .headerlink, .rst-content h5:hover .headerlink, .rst-content h6:hover .headerlink, .rst-content dl dt:hover .headerlink, .rst-content p.caption:hover .headerlink {
   display: inline-block;
@@ -2727,7 +2728,6 @@ span[id*='MathJax-Span'] {
 }
 .wy-menu-horiz:before, .wy-menu-horiz:after {
   display: table;
-  content: "";
 }
 .wy-menu-horiz:after {
   clear: both;

doc/sphinx/source/_templates/format_release_notes.rst

+format_release_notes.rst
+
+
+Release Notes
+#############
+
+
+This is the `Release Notes` template for latest nGraph Compiler stack 
+release versioning.
+
+We are pleased to announce the release of version |version|.
+
+
+What's new?
+-----------
+
+Additional functionality included with this release:
+
+
+
+
+What's updated?
+---------------
+
+The following sections provide detailed lists of major updates/removals 
+by component:
+
+
+Core
+~~~~
+
+
+
+Frameworks
+~~~~~~~~~~
+
+
+
+Backends
+~~~~~~~~
+
+
+
+Visualization Tools
+~~~~~~~~~~~~~~~~~~~
+
+
+
+Other
+~~~~~
+
+

doc/sphinx/source/backend-support/tensor-api/index.rst

-.. backend-support/tensor-api/index.rst:
-
-
-Tensor
-======
-
-.. doxygenclass:: ngraph::runtime::Tensor
-   :project: ngraph
-   :members:

doc/sphinx/source/backend-support/backend-api/index.rst → doc/sphinx/source/backends/backend-api/index.rst

-.. backend-support/backend-api/index.rst:
+.. backends/backend-api/index.rst:
 
 
 Backend

doc/sphinx/source/backend-support/cpp-api.rst → doc/sphinx/source/backends/cpp-api.rst

-.. backend-support/cpp-api.rst:
+.. backends/cpp-api.rst:
 
 Backend APIs 
 ############
@@ -10,14 +10,13 @@ Backend APIs
    executable-api/index
    hosttensor-api/index
    plaidml-ng-api/index
-   tensor-api/index
-
 
 As of version ``0.15``, there is a new backend API to work with functions that 
 can be compiled as a runtime ``Executable``. Where previously ``Backend`` used a 
 ``shared_ptr<Function>`` as the handle passed to the ``call`` method to execute 
 a compiled object, the addition of the ``shared_ptr<Executable>`` object has 
-more direct methods to actions such as ``validate``, ``call``, ``get_performance_data``, and so on. This new API permits any executable to be saved or loaded *into* or 
+more direct methods to actions such as ``validate``, ``call``, ``get_performance_data``, 
+and so on. This new API permits any executable to be saved or loaded *into* or 
 *out of* storage and makes it easier to distinguish when a Function is compiled,
 thus making the internals of the ``Backend`` and ``Executable`` easier to 
 implement.  

doc/sphinx/source/backend-support/executable-api/index.rst → doc/sphinx/source/backends/executable-api/index.rst

-.. backend-support/executable-api/index.rst:
+.. backends/executable-api/index.rst:
 
 
 Executable

doc/sphinx/source/backend-support/hosttensor-api/index.rst → doc/sphinx/source/backends/hosttensor-api/index.rst

-.. backend-support/hosttensor-api/index.rst:
+.. backends/hosttensor-api/index.rst:
 
 
 HostTensor

doc/sphinx/source/backend-support/index.rst → doc/sphinx/source/backends/index.rst

-.. backend-support/index.rst
+.. backends/index.rst
 
-About backends
-##############
+#################################
+Developer Resources for Backends
+#################################
 
 * :ref:`what_is_backend`
 * :ref:`how_to_use`

doc/sphinx/source/backend-support/plaidml-ng-api/index.rst → doc/sphinx/source/backends/plaidml-ng-api/index.rst

-.. plaidml-ng-api/index.rst:
+.. backends/plaidml-ng-api/index.rst:
 
 
 PlaidML from nGraph

doc/sphinx/source/conf.py

@@ -73,11 +73,11 @@ author = 'Intel Corporation'
 # built documents.
 #
 # The short X.Y version.
-version = '0.20'
+version = '0.21'
 
 # The Documentation full version, including alpha/beta/rc tags. Some features
 # available in the latest code will not necessarily be documented first
-release = '0.20.0'
+release = '0.21.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
@@ -105,6 +105,8 @@ todo_include_todos = True
 
 # -- Options for HTML output ----------------------------------------------
 
+html_title = "Documentation for the nGraph Library and Compiler stack"
+
 # The theme to use for HTML and HTML Help pages.  See the documentation for
 # a list of builtin themes.
 #
@@ -114,7 +116,7 @@ html_theme = 'ngraph_theme'
 # further.  For a list of options available for each theme, see the
 # documentation.
 # html_theme_options = {}
-html_logo = '../ngraph_theme/static/favicon.ico'
+html_logo = '../ngraph_theme/static/logo.png'
 
 # The name of an image file (within the static path) to use as favicon of the
 # docs.  This file should be a Windows icon file (.ico) being 16x16 or 32x32
@@ -152,11 +154,11 @@ htmlhelp_basename = 'IntelnGraphlibrarydoc'
 latex_elements = {
     # The paper size ('letterpaper' or 'a4paper').
     #
-    # 'papersize': 'letterpaper',
+    'papersize': 'letterpaper',
 
     # The font size ('10pt', '11pt' or '12pt').
     #
-    # 'pointsize': '10pt',
+    'pointsize': '10pt',
 
     # Additional stuff for the LaTeX preamble.
     #
@@ -171,11 +173,10 @@ latex_elements = {
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, 'nGraphCompilerStack.tex', 'nGraph Compiler Stack Documentation',
-     'Intel Corporation', 'manual'),
+    (master_doc, 'nGraphCompilerStack.tex', u'nGraph Compiler Stack Documentation',
+     u'Intel Corporation', 'manual'),
 ]
 
-
 # -- Options for manual page output ---------------------------------------
 
 # One entry per manual page. List of tuples
@@ -201,23 +202,7 @@ breathe_projects = {
 }
 
 rst_epilog = u"""
-.. |codename| replace:: Intel nGraph
-.. |project| replace:: Intel nGraph Library
-.. |InG| replace:: Intel® nGraph
-.. |nGl| replace:: nGraph library
-.. |copy|   unicode:: U+000A9 .. COPYRIGHT SIGN
-   :ltrim:
-.. |deg|    unicode:: U+000B0 .. DEGREE SIGN
-   :ltrim:
-.. |plusminus|  unicode:: U+000B1 .. PLUS-MINUS SIGN
-   :rtrim:
-.. |micro|  unicode:: U+000B5 .. MICRO SIGN
-   :rtrim:
-.. |trade|  unicode:: U+02122 .. TRADEMARK SIGN
-   :ltrim:
-.. |reg|    unicode:: U+000AE .. REGISTERED TRADEMARK SIGN
-   :ltrim:
-
+.. include:: /replacements.txt
 """
 
 # -- autodoc Extension configuration --------------------------------------

doc/sphinx/source/core/constructing-graphs/derive-for-training.rst

@@ -143,7 +143,7 @@ update computation for ``N`` will be given by the node
 
 The different update nodes will share intermediate computations. So to
 get the updated values for the weights as computed with the specified 
-:doc:`backend <../../backend-support/index>`:
+:doc:`backend <../../backends/index>`:
 
 .. literalinclude:: ../../../../examples/mnist_mlp/mnist_mlp.cpp
    :language: cpp

doc/sphinx/source/core/constructing-graphs/execute.rst

@@ -126,7 +126,7 @@ There are two backends for the CPU: the optimized ``"CPU"`` backend, which uses
 the `Intel MKL-DNN`_, and the ``"INTERPRETER"`` backend, which runs reference 
 versions of kernels that favor implementation clarity over speed. The 
 ``"INTERPRETER"`` backend can be slow, and is primarily intended for testing. 
-See the documentation on :doc:`runtime options for various backends <../../backend-support/index>` 
+See the documentation on :doc:`runtime options for various backends <../../backends/index>` 
 for additional details.
 
 To continue with our original example and select the ``"CPU_Backend"``: 
@@ -175,7 +175,7 @@ the three parameters and the return value.
 Each tensor is a shared pointer to a :term:`Tensorview`, which is the interface 
 backends implement for tensor use. When there are no more references to the 
 tensor view, it will be freed when convenient for the backend. See the 
-:doc:`../../backend-support/cpp-api` documentation for details on how to work 
+:doc:`../../backends/cpp-api` documentation for details on how to work 
 with ``Tensor``.
 
 

doc/sphinx/source/core/constructing-graphs/import.rst

@@ -45,7 +45,7 @@ everything at once; if an `ngraph_dist` is already installed on your system,
 skip ahead to the next section, :ref:`install_ngonnx`.
    
 
-#. Install prerequisites for the system and install nGraph as ``ngraph_dist``:
+#. Install prerequisites for the system and install nGraph as ``ngraph_dist``. 
   
    .. code-block:: console
 
@@ -54,7 +54,7 @@ skip ahead to the next section, :ref:`install_ngonnx`.
       $ apt install build-essential cmake curl clang-3.9 git zlib1g zlib1g-dev libtinfo-dev
       $ git clone https://github.com/NervanaSystems/ngraph.git
       $ cd ngraph && mkdir build
-      $ cd build && cmake ../ -DCMAKE_INSTALL_PREFIX=~/ngraph_dist -DNGRAPH_USE_PREBUILT_LLVM=TRUE
+      $ cd build && cmake ../ -DCMAKE_INSTALL_PREFIX=~/ngraph_dist
       $ make install
 
 #. Build the Python package (binary wheel) for ngraph and set up an env for ONNX;
@@ -77,8 +77,10 @@ skip ahead to the next section, :ref:`install_ngonnx`.
 
    .. code-block:: console
 
-      (onnx)$ pip install -U python/dist/ngraph-0.9.0-cp36-cp36m-linux_x86_64.whl    
+      (onnx)$ pip install -U python/dist/ngraph-[version]-cp36-cp36m-linux_x86_64.whl
 
+   Where ``[version]`` is the version number of the nGraph Python module 
+   you see in that directory.  
 
 #. Confirm ``ngraph`` is properly installed through a Python interpreter:
 

doc/sphinx/source/core/fusion/index.rst

@@ -12,7 +12,7 @@ Pattern matcher
 The nGraph Compiler is an optimizing compiler. As such, it provides a way to 
 capture a given :term:`function graph` and perform a series of optimization 
 passes over that graph. The result is a semantically-equivalent graph that, when 
-executed using any :doc:`backend <../../backend-support/index>`, has optimizations 
+executed using any :doc:`backend <../../backends/index>`, has optimizations 
 inherent at the hardware level: superior runtime characteristics to increase 
 training performance or reduce inference latency.
 

doc/sphinx/source/core/fusion/overview.rst

@@ -6,7 +6,7 @@ Overview: Optimize graphs with nGraph Compiler fusions
 The nGraph Compiler is an optimizing compiler. As such, it provides a way to 
 capture a given :term:`function graph` and perform a series of optimization 
 passes over that graph. The result is a semantically-equivalent graph that, when 
-executed using any :doc:`backend <../../backend-support/index>`, has 
+executed using any :doc:`backend <../../backends/index>`, has 
 hardware-agnostic *and* hardware-specific optimizations, providing superior 
 runtime characteristics to increase training performance or reduce inference 
 latency.   

doc/sphinx/source/core/overview.rst

@@ -15,8 +15,9 @@ 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
 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 graphs via 
-the backend execution interface.
+translates a framework's operations into graphs in nGraph’s in-memory 
+:abbr:`Intermediary Representation (IR)`. Second, it executes the nGraph IR 
+graphs via the backend execution interface.
 
 The details of bridge implementation vary from framework to framework, but there 
 are some common patterns: a fairly typical example for a graph-based framework 
@@ -59,16 +60,14 @@ descriptions:
 .. csv-table::
    :header: "Namespace", "Description", "Location in Repo", "Docs"
    :widths: 23, 53, 13, 23
-   :escape: ~
 
-   ``ngraph``, The Intel nGraph C++ API, `ngraph`_, Implicit namespace omitted from most API documentation
+   ``ngraph``, The Intel nGraph C++ API, ngraph, Implicit namespace omitted from most API documentation
    ``builder``, "Convenience functions that create additional graph nodes to implement commonly-used recipes; for example, auto-broadcast", `builder`_, Coming Soon
    ``descriptor``, Descriptors are compile-time representations of objects that will appear at run-time, `descriptor`_, Coming Soon
    ``op``, Ops used in graph construction, `op`_, :doc:`../ops/index`
-   ``runtime``, The objects and methods used for executing the graph, `runtime`_, :doc:`../backend-support/cpp-api`
+   ``runtime``, The objects and methods used for executing the graph, `runtime`_, :doc:`../backends/cpp-api`
 
 
-.. _ngraph: https://github.com/NervanaSystems/ngraph/tree/master/src/ngraph
 .. _builder: https://github.com/NervanaSystems/ngraph/tree/master/src/ngraph/builder
 .. _descriptor: https://github.com/NervanaSystems/ngraph/tree/master/src/ngraph/descriptor
 .. _op: https://github.com/NervanaSystems/ngraph/tree/master/src/ngraph/op

doc/sphinx/source/frameworks/generic-configs.rst

@@ -19,6 +19,15 @@ something like:
    export LD_LIBRARY_PATH=path/to/ngraph_dist/lib/
 
 
+Find or display nGraph Version
+-------------------------------
+
+
+
+.. code-block:: console
+
+   python3 -c "import ngraph as ng; print('nGraph version: ',ng.__version__)";
+
 
 FMV
 ---

doc/sphinx/source/frameworks/index.rst

 .. frameworks/index.rst: 
 
-Current framework integrations  
-==============================
+Connect a framework  
+===================
 
 .. toctree::
    :maxdepth: 1
@@ -12,7 +12,6 @@ Current framework integrations
    paddle_integ.rst
    validated/testing-latency.rst
 
-
 A framework is "supported" when there is a framework :term:`bridge` that can be 
 cloned from one of our GitHub repos and built to connect to nGraph device 
 backends while maintaining the framework's programmatic or user interface. Bridges 

doc/sphinx/source/index.rst

@@ -13,33 +13,39 @@
 .. limitations under the License.
 .. ---------------------------------------------------------------------------
 
-
-.. This documentation is available online at
-.. https://ngraph.nervanasys.com/docs/latest
-
 ######################
 nGraph Compiler stack 
 ######################
 
 
-nGraph is an open-source graph compiler for :abbr:`Artificial Neural Networks (ANNs)`. 
-The nGraph Compiler stack provides an inherently efficient graph-based compilation 
-infrastructure designed to be compatible with many upcoming 
-:abbr:`Application-Specific Integrated Circuits (ASICs)`, like the Intel® Nervana™ 
-Neural Network Processor (Intel® Nervana™ NNP), while also unlocking a massive 
-performance boost on any existing hardware targets for your neural network: both 
-GPUs and CPUs. Using its flexible infrastructure, you will find it becomes much 
-easier to create Deep Learning (DL) models that can adhere to the "write once, 
-run anywhere" mantra that enables your AI solutions to easily go from concept to 
-production to scale.
+.. _ngraph_home:
+
+.. only:: release
+
+  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|).
+
+For information about the releases, see the :doc:`../project/release-notes`. 
+
+The nGraph Library and Compiler stack are provided under the `Apache 2.0 license`_ 
+(found in the LICENSE file in the project's `GitHub 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
+.. _GitHub repo: https://github.com/NervanaSystems/ngraph
 
-Frameworks using nGraph to execute workloads have shown `up to 45X`_ performance 
-boost compared to native implementations. For a high-level overview, see the 
-:doc:`project/introduction` and our latest :doc:`project/release-notes`.
 
 .. toctree::
    :maxdepth: 1
-   :caption: Connecting Frameworks
+   :caption: Getting Started
    
    frameworks/index.rst
    frameworks/validated/list.rst
@@ -57,6 +63,7 @@ boost compared to native implementations. For a high-level overview, see the
    core/constructing-graphs/index.rst
    core/passes/passes.rst
 
+   
 .. toctree::
    :maxdepth: 1
    :caption: nGraph Python API
@@ -66,10 +73,10 @@ boost compared to native implementations. For a high-level overview, see the
    
 .. toctree::
    :maxdepth: 1
-   :caption: Backend Support
+   :caption: Backend Developers
 
-   backend-support/index.rst
-   backend-support/cpp-api.rst
+   backends/index.rst
+   backends/cpp-api.rst
 
 
 .. toctree::
@@ -91,14 +98,10 @@ boost compared to native implementations. For a high-level overview, see the
    project/extras.rst 
    glossary.rst
 
+.. only:: html
+
 Indices and tables
 ==================
 
    * :ref:`search`
    * :ref:`genindex`
-
-
-
-
-.. nGraph: https://www.ngraph.ai
-.. _up to 45X: https://ai.intel.com/ngraph-compiler-stack-beta-release/
\ No newline at end of file

doc/sphinx/source/project/doc-contributor-README.rst

@@ -20,22 +20,26 @@ Contributing to documentation
 
 .. important:: Read this for changes affecting **anything** in ``ngraph/doc``
 
-For updates to the Intel® nGraph Library ``/doc`` repo, please submit a PR with 
+For updates to the nGraph Library ``/doc`` repo, please submit a PR with 
 any changes or ideas you'd like integrated. This helps us maintain trackability 
-with respect to additions or feature requests.
+with respect to changes made, additions, deletions, and feature requests.
 
 If you prefer to use a containerized application, like Jupyter\* notebooks, 
-Google Docs\*, or MS Word\* to explain, write, or share documentation contributions, 
-you can convert the ``doc/sphinx/source/*.rst`` files to another format with a tool 
-like ``pypandoc`` and share a link to your docs on our `wiki`_.
+Google Docs\*, the GitHub* GUI, or MS Word\* to explain, write, or share 
+documentation contributions, you can convert the ``doc/sphinx/source/*.rst`` 
+files to another format with a tool like ``pypandoc`` and share a link   
+to your efforts on our `wiki`_. 
 
 Another option is to fork the `ngraph repo`_, essentially snapshotting it at 
 that point in time, and to build a Jupyter\* notebook or other set of docs around 
-it for a specific use case; then share a link with the community on our wiki.   
+it for a specific use case. Add a note on our wiki to show us what you 
+did; new and novel applications may have their projects highlighted on an 
+upcoming `ngraph.ai`_ release.   
 
-.. note:: Please do not submit Jupyter* notebook code to the Intel nGraph library 
+
+.. note:: Please do not submit Jupyter* notebook code to the nGraph Library 
    or core repos; best practice is to maintain any project-specific examples, 
-   tests, or walk-throughs separately. 
+   tests, or walk-throughs in a separate repository.
 
 
 Documenting source code examples 
@@ -43,7 +47,7 @@ Documenting source code examples
 
 When **verbosely** documenting functionality of specific sections of code -- whether 
 they are entire code blocks within a file, or code strings that are **outside** 
-the Intel nGraph `documentation repo`_, here is an example of best practice: 
+the nGraph Library's `documentation repo`_, here is an example of best practice: 
 
 Say a file has some interesting functionality that could benefit from more 
 explanation about one or more of the pieces in context. To keep the "in context" 
@@ -68,7 +72,6 @@ the code. The trick here is to add the file you want to reference relative to
 the folder where the ``Makefile`` is that generates the documentation you're 
 writing. 
 
-
 See the **note** at the bottom of this page for more detail about how 
 this works in the current |version| version of Intel nGraph library 
 documentation. 
@@ -136,7 +139,7 @@ To build documentation locally, run:
 
 Then point your browser at ``localhost:8000``.
 
-To build documentation in a python3 virtualenv, run: 
+To build documentation in a python3 virtualenv, try: 
 
    .. code-block:: console
 
@@ -159,6 +162,7 @@ For tips on writing reStructuredText-formatted documentation, see the `sphinx`_
 stable reST documentation.
 
 .. _ngraph repo: https://github.com/NervanaSystems/ngraph/
+.. _ngraph.ai: https://www.ngraph.ai
 .. _documentation repo: https://github.com/NervanaSystems/ngraph/tree/master/doc
 .. _sphinx: http://www.sphinx-doc.org/en/stable/rest.html
 .. _wiki: https://github.com/NervanaSystems/ngraph/wiki/

doc/sphinx/source/project/introduction.rst

-.. introduction:
+.. project/introduction.rst:
 
-############
-Introduction
-############
+#######
+Summary
+#######
 
+nGraph is an open-source graph compiler for :abbr:`Artificial Neural Networks (ANNs)`. 
+The nGraph Compiler stack provides an inherently efficient graph-based compilation 
+infrastructure designed to be compatible with many upcoming 
+:abbr:`Application-Specific Integrated Circuits (ASICs)`, like the Intel® Nervana™ 
+Neural Network Processor (Intel® Nervana™ NNP), while also unlocking a massive 
+performance boost on any existing hardware targets for your neural network: both 
+GPUs and CPUs. Using its flexible infrastructure, you will find it becomes much 
+easier to create Deep Learning (DL) models that can adhere to the "write once, 
+run anywhere" mantra that enables your AI solutions to easily go from concept to 
+production to scale.
+
+Frameworks using nGraph to execute workloads have shown `up to 45X`_ performance 
+boost compared to native implementations. 
+
+For a detailed overview, see below; for a more historical perspective, see 
+our `arXiv`_ paper.
+
+Motivations
+===========
 
 Developers working to craft solutions with :abbr:`Artificial Intelligence (AI)`
 face a steep learning curve in taking their concepts from design to 
@@ -49,10 +68,6 @@ larger datasets, data that must be encrypted, and data-in-motion. Our solution
 also addresses the scalability issue with kernel libraries, the current 
 popular solution to accelerating deep learning performance. 
 
-
-Motivations
-===========
-
 The current state-of-the-art software solution for speeding up deep learning 
 computation is to integrate kernel libraries like Intel® Math Kernel Library 
 for Deep Neural Networks (Intel® MKL DNN) and Nvidia\*'s CuDNN into deep 
@@ -151,7 +166,7 @@ final product of required kernels is increasing exponentially.
 
 PlaidML addresses the kernel explosion problem in a manner that lifts a heavy 
 burden off kernel developers. It automatically lowers networks from nGraph 
-into Tile, a :abbr:Domain-Specific Language (DSL) designed for deep learning 
+into Tile, a :abbr:`Domain-Specific Language (DSL)` designed for deep learning 
 that allows developers to express how an operation should calculate tensors in
 an intuitive, mathematical form via `Stripe`_. Integration of PlaidML with 
 nGraph means extra flexibility to support newer deep learning models in the 
@@ -187,6 +202,7 @@ will make life easier for many kinds of developers:
 #. New DL accelerator developers creating an end-to-end software stack from 
    a deep learning framework to their silicon.  
 
-
+.. _arXiv: https://arxiv.org/abs/1801.08058
+.. _up to 45X: https://ai.intel.com/ngraph-compiler-stack-beta-release/
 .. _more transistors on denser and denser circuits: https://www.intel.com/content/www/us/en/silicon-innovations/moores-law-technology.html
 .. _Stripe: https://arxiv.org/abs/1903.06498

doc/sphinx/source/project/release-notes.rst

-.. ngraph/release-notes:
+.. project/release-notes.rst:
 
 Release Notes
 #############
 
-|version|
+nGraph is provided as source code, APIs, build scripts, and some binary formats 
+for various Compiler stack configurations and use cases. 
+
+This page includes additional documentation updates.
+
+We are pleased to announce the release of version |version|-doc.
+
+
+0.21-doc
+--------
+
+Documentation updates
+~~~~~~~~~~~~~~~~~~~~~
+
+Summary of documentation-related changes:
+
++ Update :doc:`doc-contributor-README` for new community-based contributions. 
++ Added instructions on how to test or display the installed nGraph version.
++ Added instructions on building nGraph bridge (ngraph-bridge).
++ Updated Backend Developer Guides and ToC structure.
++ Tested documentation build on Clear Linux OS; it works.
++ Fixed a few links and redirs affected by filename changes.
++ Some coding adjustments for options to render math symbols, so they can be 
+  documented more clearly and without excessive JS (see replacements.txt).
++ Consistent filenaming on all BE indexes.
++ Remove deprecated TensorAPI.
++ 
+
+
+Core updates for |version|
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
++ The offset argument in tensor reads and writes has been removed
++ Save/load API
++ More ONNX ops
++ Better tensor creation
++ More shape support
++ Provenance improvements
++ offset arg for tensor creation is deprecated
++ static linking support
 
-For downloads formatted as ``.zip`` and ``tar.gz``, see https://github.com/NervanaSystems/ngraph/releases; 
 
 .. important:: Pre-releases (``-rc-0.*``) have newer features, and are less stable.  
 
 
-Changelog 
-=========
+Changelog on Previous Releases
+==============================
+
+For downloads formatted as ``.zip`` and ``tar.gz``, see 
+https://github.com/NervanaSystems/ngraph/releases.
+
+0.20
+----
+
++ Save/load API
++ More ONNX ops
++ Better tensor creation
++ More shape support
++ Provenance improvements
+
 
 0.19
 ----
@@ -58,7 +109,8 @@ Changelog
 + Add code generation for some quantized ops
 + Preliminary dynamic shape support
 + initial distributed ops
-+ Pad op takes CoordinateDiff instead of Shape pad values to allow for negative padding.
++ Pad op takes CoordinateDiff instead of Shape pad values to allow for negative 
+  padding.
 
 
 0.16
@@ -77,6 +129,7 @@ Changelog
 + Concat optimization
 + Doc updates
 
+.. _0.20.0-rc.0: https://github.com/NervanaSystems/ngraph/releases/tag/v0.20.0-rc.0_
 .. _0.19.0-rc.2: https://github.com/NervanaSystems/ngraph/releases/tag/v0.19.0-rc.2_
 .. _0.18.1: https://github.com/NervanaSystems/ngraph/releases/tag/v0.18.1_
 .. _0.17.0-rc.1: `https://github.com/NervanaSystems/ngraph/releases/tag/v0.17.0-rc.1

doc/sphinx/source/replacements.txt

+   
+.. |codename| replace:: nGraph
+.. |project| replace:: nGraph Compiler stack
+.. |Intel| replace:: Intel® 
+
+
+.. Replacement strings for commonly-used math symbols; renders in default font
+
+.. |lcsigma|    unicode:: U+03C3      .. sigma σ
+.. |sigma|      unicode:: U+03A3      .. Sigma Σ
+
+.. |lcdelta|    unicode:: U+03B4      .. delta δ
+.. |delta|      unicode:: U+0394      .. Delta Δ
+
+.. |lcgamma|    unicode:: U+03B3      .. gamma γ
+.. |gamma|      unicode:: U+0393      .. Gamma Γ
+
+.. |lcphi|      unicode:: U+03C6      .. phi φ
+.. |sphi|       unicode:: U+03D5      .. ϕ 
+.. |phi|        unicode:: U+03A6      .. Phi Φ
+
+.. |lcpi|       unicode:: U+03C0      .. pi π
+.. |pi|         unicode:: U+03A0      .. Pi Π
+
+.. |lctheta|    unicode:: U+03B8      .. theta θ
+.. |theta|      unicode:: U+03F4      .. Theta ϴ
+
+.. |lclambda|   unicode:: U+03BB      .. lambda λ
+.. |lambda|     unicode:: U+039B      .. Lambda Λ
+
+.. |vmlt|       unicode:: U+22D8      .. very much less than ⋘
+.. |vmgt|       unicode:: U+22D9      .. very much greater than ⋙
+
+
+.. Miscellaneous IP-related substitutions
+
+.. |trade|  unicode:: U+02122 .. TRADEMARK SIGN
+   :ltrim:
+.. |reg|    unicode:: U+000AE .. REGISTERED TRADEMARK SIGN
+   :ltrim:
+.. |copy|   unicode:: U+000A9 .. COPYRIGHT SIGN
+   :ltrim:
+
+
+.. Default substitutions 
+
+.. |bullet|     unicode:: U+2022      .. BULLET
+.. |bulletop|   unicode:: U+2219      .. BULLET OPERATOR
+
+
+.. |micro|      unicode:: U+000B5     .. MICRO SIGN
+   :rtrim:
+
+.. |sup2|       unicode:: U+00B2      .. SUPERSCRIPT TWO
+   :ltrim:
+
+.. |deg|        unicode:: U+000B0     .. DEGREE SIGN
+   :ltrim:
+
+.. |plusminus|  unicode:: U+000B1     .. PLUS-MINUS SIGN
+   :rtrim:
\ No newline at end of file

doc/sphinx/source/sitemap.rst

 :orphan:
 
-.. _sitemap.rst:
- 
 .. toctree::
-   :includehidden: 
+   :caption: Sitemap
+   :maxdepth: 1 
    
-   index.rst
+   frameworks/index
+   python_api/index
+   inspection/index
+   core/overview
+   backends/index
+   project/index

python/BUILDING.md

@@ -2,26 +2,27 @@
 
 ## Building nGraph Python Wheels
 
-[nGraph's build instructions][ngraph_build] give detailed instructions on building nGraph on different operating systems. Please make sure you specify the options `-DNGRAPH_PYTHON_BUILD_ENABLE=ON` and `-DNGRAPH_ONNX_IMPORT_ENABLE=ON` when building nGraph. Use the `make python_wheel` command to build nGraph and create Python packages. 
+If you want to try a newer version of nGraph's Python API than is available from
+PyPI, you can build your own latest version from the source code. This 
+process is very similar to what is outlined in our [ngraph_build] instructions 
+with two important differences:
 
-Basic build procedure on an Ubuntu system: 
+1. You must specify: `-DNGRAPH_PYTHON_BUILD_ENABLE=ON` and `-DNGRAPH_ONNX_IMPORT_ENABLE=ON` 
+   when running `cmake`.
 
-    # apt-get install build-essential cmake clang-3.9 clang-format-3.9 git curl zlib1g zlib1g-dev libtinfo-dev unzip autoconf automake libtool
-    # apt-get install python3 python3-dev python python-dev python-virtualenv
+2. Instead of running `make`, use the command `make python_wheel`.
 
-    $ git clone https://github.com/NervanaSystems/ngraph.git
-    $ cd ngraph/
-    $ mkdir build
-    $ cd build/
-    $ cmake ../ -DNGRAPH_PYTHON_BUILD_ENABLE=ON -DNGRAPH_ONNX_IMPORT_ENABLE=ON -DNGRAPH_USE_PREBUILT_LLVM=ON
-    $ make python_wheel
+    `$ cmake ../ -DNGRAPH_PYTHON_BUILD_ENABLE=ON -DNGRAPH_ONNX_IMPORT_ENABLE=ON -DNGRAPH_USE_PREBUILT_LLVM=ON`
 
-After this procedure completes, the `ngraph/build/python/dist` directory should contain Python packages. 
+    `$ make python_wheel`
+
+After this procedure completes, the `ngraph/build/python/dist` directory should 
+contain the Python packages of the version you cloned. For example, if you 
+checked out and built `0.21`, you may see something like: 
 
     $ ls python/dist/
-    ngraph-core-0.10.0.tar.gz  
-    ngraph_core-0.10.0-cp27-cp27mu-linux_x86_64.whl  
-    ngraph_core-0.10.0-cp35-cp35m-linux_x86_64.whl
+    ngraph-core-0.21.0rc0.tar.gz  
+    ngraph_core-0.21.0rc0-cp37-cp37m-linux_x86_64.whl  
 
 ### Using a virtualenv (optional)
 
@@ -35,7 +36,7 @@ You may wish to use a virutualenv for your installation.
 
 You may wish to use a virutualenv for your installation.
 
-    (venv) $ pip install ngraph/build/python/dist/ngraph_core-0.10.0-cp35-cp35m-linux_x86_64.whl
+    (venv) $ pip install ngraph/build/python/dist/ngraph_core-0.21.0rc0-cp37-cp37m-linux_x86_64.whl
 
 ## Running tests