Merge pull request #3124 from NervanaSystems/leona/doc_igpu

Add initial igpu docs and other important fixes for 0.22

doc/sphinx/conf.py

@@ -76,9 +76,7 @@ author = 'Intel Corporation'
 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.
-# rc syntax may be tagged; this documentation supports various rc-naming conventions 
-
+# available in the latest code will not necessarily be documented first
 release = '0.22.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
@@ -107,38 +105,18 @@ todo_include_todos = True
 
 # -- Options for HTML output ----------------------------------------------
 
-html_title = 'nGraph Compiler stack Documentation'
+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.
+#
 html_theme = 'ngraph_theme'
 
+# Theme options are theme-specific and customize the look and feel of a theme
+# further.  For a list of options available for each theme, see the
+# documentation.
 # html_theme_options = {}
-html_theme_path = ["../"]
-
-if tags.has('release'):
-    is_release = True
-    docs_title = 'Docs / %s' %(version) %(release)
-else:
-    is_release = False
-    docs_title = 'Docs / Latest'
-
-    # borrow this from the zephyr docs theme
-    html_context = {
-        # '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", "../"),
-                     ("0.20.0", "/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/"),
-                    )
-    }
-
-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
@@ -151,6 +129,7 @@ html_favicon = '../ngraph_theme/static/favicon.ico'
 html_static_path = ['../ngraph_theme/static']
 
 # Add any paths that contain custom themes here, relative to this directory.
+html_theme_path = ["../"]
 
 # Custom sidebar templates, must be a dictionary that maps document names
 # to template names.
@@ -165,26 +144,6 @@ html_sidebars = {
 }
 
 
-# Custom added feature to allow redirecting old URLs
-#
-# list of tuples (old_url, new_url) for pages to redirect
-# (URLs should be relative to document root, only)
-html_redirect_pages = [
-        ('backend-support', 'backends/index'),
-        ('core/core', 'core/overview.rst'),
-        ('core/fusion', 'core/fusion/index'),
-        ('frameworks/mxnet', 'frameworks/mxnet_intg.rst'),
-        ('frameworks/onnx', 'frameworks/onnx_intg.rst'),
-        ('frameworks/tensorflow', 'frameworks/tensorflow_connect.rst'),
-        ('frameworks/paddle', 'frameworks/paddle_integ.rst'),
-        ('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'),
-]
-
 # -- Options for HTMLHelp output ------------------------------------------
 
 # Output file base name for HTML help builder.
@@ -195,11 +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.
     #
@@ -214,11 +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
@@ -244,22 +202,7 @@ breathe_projects = {
 }
 
 rst_epilog = u"""
-.. |codename| replace:: Intel nGraph
-.. |project| replace:: Intel nGraph Library
-.. |InG| replace:: Intel® nGraph
-.. |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/ngraph_theme/ngversions.html

@@ -6,16 +6,14 @@
     </span>
     <div class="rst-other-versions">
       <dl>
-        <dt>{{ _('Previous Versions') }}</dt>
+        <dt>{{ _('Recent 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/v0.22.0">0.22</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.21.0">0.21.0</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.20.0">0.20.0</a></li>
+           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.19.0">0.19.0</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>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.16.0-rc.3">0.16.0-rc.3</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.16.0-rc.2">0.16.0-rc.2</a></li>
-           <li><a href="https://github.com/NervanaSystems/ngraph/releases/tag/v0.16.0-rc.1">0.16.0-rc.1</a></li>
          </ul></dd>
       </dl>
       <dl>

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

@@ -7,4 +7,3 @@ Backend
 .. doxygenclass:: ngraph::runtime::Backend
    :project: ngraph
    :members:
-

doc/sphinx/source/backends/cpp-api.rst

@@ -7,9 +7,10 @@ Backend APIs
    :maxdepth: 1
    
    backend-api/index
-   executable-api/index
-   hosttensor-api/index
+   dynamicbackend-api/index
    plaidml-ng-api/index
+   executable-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 

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

 .. backends/hosttensor-api/index.rst:
 
 
-HostTensor
-==========
+DynamicBackend
+==============
 
-.. doxygenclass:: ngraph::runtime::HostTensor
+.. doxygenclass:: ngraph::runtime::dynamic::DynamicBackend
    :project: ngraph
    :members:

doc/sphinx/source/backends/executable-api/index.rst

@@ -7,7 +7,6 @@ Executable
 The ``compile`` function on an ``Executable`` has more direct methods to 
 actions such as ``validate``, ``call``, ``get_performance_data``, and so on. 
 
-
 .. doxygenclass:: ngraph::runtime::Executable
    :project: ngraph
    :members: 

doc/sphinx/source/backends/index.rst

@@ -6,6 +6,7 @@ Developer Resources for Backends
 
 * :ref:`what_is_backend`
 * :ref:`how_to_use`
+* :ref:`miscellaneous_resources`
 
 
 .. _what_is_backend:
@@ -60,3 +61,57 @@ interface; each backend implements the following five functions:
   for later execution.
 * And, finally, the ``call()`` method is used to invoke an nGraph function 
   against a particular set of tensors.
+
+
+.. _miscellaneous_resources: 
+
+Miscellaneous resources
+=======================
+
+Additional resources for device or framework-specific configurations:
+
+OpenCL
+------
+
+OpenCL is needed for the :doc:`plaidml-ng-api/index`; this is not needed if 
+you have only a CPU backend.  
+
+#. Install the latest Linux driver for your system. You can find a list 
+   of drivers at https://software.intel.com/en-us/articles/opencl-drivers;
+   You may need to install `OpenCL SDK`_ in case of an ``libOpenCL.so`` absence.
+
+#. Any user added to "video" group: 
+
+   .. code-block:: console 
+
+      sudo usermod –a –G video <user_id>
+
+   may, for example, be able to find details at the ``/sys/module/[system]/parameters/`` location. 
+
+
+nGraph Bridge from TensorFlow\*
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+When specified as the generic backend -- either manually or automatically 
+from a framework --  ``NGRAPH`` defaults to CPU, and it also allows for 
+additional device configuration or selection. 
+
+Because nGraph can select backends, specifying the ``INTELGPU`` 
+backend as a runtime environment variable also works if one is 
+present in your system: 
+
+:envvar:`NGRAPH_TF_BACKEND="INTELGPU"`
+
+An `axpy.py example`_ is optionally available to test; outputs will vary 
+depending on the parameters specified. 
+
+.. code-block:: console
+
+   NGRAPH_TF_BACKEND="INTELGPU" python3 axpy.py
+
+* ``NGRAPH_INTELGPU_DUMP_FUNCTION`` -- dumps nGraph’s functions 
+  in dot format.
+
+
+.. _axpy.py example: https://github.com/tensorflow/ngraph-bridge/blob/master/examples/axpy.py
+.. _OpenCL SDK: https://software.intel.com/en-us/opencl-sdk

doc/sphinx/source/conf.py

@@ -73,11 +73,11 @@ author = 'Intel Corporation'
 # built documents.
 #
 # The short X.Y version.
-version = '0.21'
+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 = '0.21.0'
+release = '0.22.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

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

@@ -5,8 +5,8 @@ Integrating new 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 
-your system already has a version of nGraph installed with one of our supported
-backends. 
+your system already has a version of nGraph installed with one or more of our 
+supported :doc:`../backends/index`.
 
 Regardless of the framework, after the :doc:`../buildlb` step, a good place 
 to start usually involves making the libraries available to the framework. On 
@@ -19,15 +19,59 @@ something like:
    export LD_LIBRARY_PATH=path/to/ngraph_dist/lib/
 
 
-Find or display nGraph Version
--------------------------------
-
+Find or display version
+=======================
 
+If you're working with the :doc:`../python_api/index`, the following command 
+may be useful:
 
 .. code-block:: console
 
    python3 -c "import ngraph as ng; print('nGraph version: ',ng.__version__)";
 
+To manually build a newer version than is available from the latest `PyPI`_
+(:abbr:`Python Package Index (PyPI)`), see our nGraph Python API `BUILDING.md`_ 
+documentation.
+
+
+Activate logtrace-related environment variables
+===============================================
+
+Another configuration option is to activate ``NGRAPH_CPU_DEBUG_TRACER``,
+a runtime environment variable that supports extra logging and debug detail. 
+
+This is a useful tool for data scientists interested in outputs from logtrace 
+files that can, for example, help in tracking down model convergences. It can 
+also help engineers who might want to add their new ``Backend`` to an existing 
+framework to compare intermediate tensors/values to references from a CPU 
+backend.
+
+To activate this tool, set the ``env`` var ``NGRAPH_CPU_DEBUG_TRACER=1``.
+It will dump ``trace_meta.log`` and ``trace_bin_data.log``. The names of the 
+logfiles can be customized.
+
+To specify the names of logs with those flags:
+
+:: 
+
+  NGRAPH_TRACER_LOG = "meta.log"
+  NGRAPH_BIN_TRACER_LOG = "bin.log"
+
+The meta_log contains::
+ 
+  kernel_name, serial_number_of_op, tensor_id, symbol_of_in_out, num_elements, shape, binary_data_offset, mean_of_tensor, variance_of_tensor
+
+A line example from a unit-test might look like::
+
+  K=Add S=0 TID=0_0 >> size=4 Shape{2, 2} bin_data_offset=8 mean=1.5 var=1.25
+
+The binary_log line contains::
+
+  tensor_id, binary data (tensor data)
+
+A reference for the implementation of parsing these logfiles can also be found 
+in the unit test for this feature.
+
 
 FMV
 ---
@@ -37,7 +81,7 @@ number of generic ways to patch or bring architecture-based optimizations to
 the :abbr:`Operating System (OS)` that is handling your ML environment. See 
 the `GCC wiki for details`_.
 
-If your nGraph build is a Neural Network configured on Clear Linux* OS 
+If your nGraph build is a Neural Network configured on Clear Linux\* OS 
 for Intel® Architecture, and it includes at least one older CPU, the 
 `following article may be helpful`_.
 
@@ -63,11 +107,14 @@ For CPU (and most cuDNN) backends, the preferred layout is currently ``NCHW``.
 Intel® Math Kernel Library for Deep Neural Networks 
 ---------------------------------------------------
 
--The following `KMP options`_ were originally optimized for models using the 
+.. important:: Intel® MKL-DNN is automatically enabled as part of an
+   nGraph default :doc:`build <../buildlb>`; you do *not* need to add it 
+   separately or as an additional component to be able to use these 
+   configuration settings.
+
+The following `KMP`_ options were originally optimized for models using the 
 Intel® `MKL-DNN`_ to train models with the ``NCHW`` data layout; however, other 
-configurations can be explored. MKL-DNN is automatically enabled as part of an 
-nGraph compilation; you do *not* need to add MKL-DNN separately or as an 
-additional component to be able to use these configuration settings.   
+configurations can be explored.    
 
 * ``KMP_BLOCKTIME`` Sets the time, in milliseconds, that a thread should wait 
   after completing the execution of a parallel region, before sleeping.
@@ -128,10 +175,11 @@ Convolution shapes
 ``OMP_NUM_THREADS``
 ^^^^^^^^^^^^^^^^^^^
 
-The best resource for this configuration option is the `gnu.org site`_ 
-``OMP_NUM_THREADS`` defaults to the number of logical cores. To check the 
-number of cores on your system, you can run the following on the command-line to 
-see the details of your CPU: 
+The best resource for this configuration option is the Intel® OpenMP\* docs 
+at the following link: `Intel OpenMP documentation`_. ``OMP_NUM_THREADS`` 
+defaults to the number of logical cores. To check the number of cores on your 
+system, you can run the following on the command-line to see the details 
+of your CPU:
 
 .. code-block:: console
 
@@ -171,11 +219,12 @@ achieve the best performance for NN workloads on CPU platforms. The nGraph
 Compiler stack runs on transformers handled by Intel® Architecture (IA), and 
 thus can make more efficient use of the underlying hardware.
 
-
-.. _KMP options: https://software.intel.com/en-us/cpp-compiler-developer-guide-and-reference-controlling-thread-allocation
-.. KMP options: https://software.intel.com/en-us/node/522691
+.. _PyPI: https://pypi.org/project/ngraph-core
+.. _KMP: https://software.intel.com/en-us/node/522691
 .. _MKL-DNN: https://github.com/intel/mkl-dnn
-.. _gnu.org site: https://gcc.gnu.org/onlinedocs/libgomp/Environment-Variables.html
+.. _Intel OpenMP documentation: https://www.openmprtl.org/documentation
 .. _Movidius: https://www.movidius.com/
+.. _BUILDING.md: https://github.com/NervanaSystems/ngraph/blob/master/python/BUILDING.md
 .. _GCC wiki for details: https://gcc.gnu.org/wiki/FunctionMultiVersioning
 .. _following article may be helpful: https://clearlinux.org/documentation/clear-linux/tutorials/fmv
+

doc/sphinx/source/frameworks/mxnet_integ.rst

 .. frameworks/mxnet_integ.rst:
 
 MXNet\* bridge
-===============
+==============
+
+.. deprecated:: 0.21.0
+
 
 * See the nGraph-MXNet `Integration Guide`_ on the nGraph-MXNet repo.
 

doc/sphinx/source/frameworks/onnx_integ.rst

@@ -10,7 +10,7 @@ nGraph's internal representation and converted to ``Function`` objects, which
 can be compiled and executed on one of nGraph's backends.
 
 You can use nGraph's Python API to run an ONNX model and nGraph can be used 
-as an ONNX backend using the add-on package `nGraph-ONNX <ngraph_onnx>`_.
+as an ONNX backend using the add-on package `nGraph ONNX`_.
 
 
 .. note:: In order to support ONNX, nGraph must be built with the 
@@ -33,8 +33,7 @@ for nGraph, ONNX and NumPy:
 Importing an ONNX model
 -----------------------
 
-You can download models from the `ONNX Model Zoo <onnx_model_zoo_>`_.
-For example ResNet-50:
+You can download models from the `ONNX Model Zoo`_. For example, ResNet-50:
 
 ::
 
@@ -92,9 +91,9 @@ data:
 
 
 Find more information about nGraph and ONNX in the 
-`nGraph-ONNX <ngraph_onnx>`_ GitHub repository.
+`nGraph ONNX`_ GitHub repository.
 
 
-.. _ngraph_onnx: https://github.com/NervanaSystems/ngraph-onnx/
-.. _ngraph_onnx_building: https://github.com/NervanaSystems/ngraph-onnx/blob/master/BUILDING.md
-.. _onnx_model_zoo: https://github.com/onnx/models
+.. _ngraph ONNX: https://github.com/NervanaSystems/ngraph-onnx
+.. _ngraph ONNX building: https://github.com/NervanaSystems/ngraph-onnx/blob/master/BUILDING.md
+.. _ONNX model zoo: https://github.com/onnx/models

doc/sphinx/source/index.rst

-.. ---------------------------------------------------------------------------
 .. Copyright 2018-2019 Intel Corporation
 .. Licensed under the Apache License, Version 2.0 (the "License");
 .. you may not use this file except in compliance with the License.

doc/sphinx/source/inspection/index.rst

@@ -6,9 +6,9 @@ Visualization Tools
 nGraph provides serialization and deserialization facilities, along with the 
 ability to create image formats or a PDF. 
 
-When visualization is enabled, a ``dot`` file gets generated, along with a 
-``png``. The default can be adjusted by setting the 
-``NGRAPH_VISUALIZE_TREE_OUTPUT_FORMAT`` flag to another format, like PDF. 
+When visualization is enabled, ``svg`` files for your graph get generated. The 
+default can be adjusted by setting the ``NGRAPH_VISUALIZE_TRACING_FORMAT`` 
+flag to another format, like PNG or PDF. 
 
 .. note:: Large graphs are usually not legible with formats like PDF.
 

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

@@ -18,9 +18,36 @@
 Contributing to documentation
 =============================
 
-.. important:: Read this for changes affecting **anything** in ``ngraph/doc``
+.. note:: Tips for contributors who are new to the highly-dynamic 
+   environment of documentation in AI software:
 
-For updates to the nGraph Library ``/doc`` repo, please submit a PR with 
+   * A good place to start is "document something you figured out how to 
+     get working". Content changes and additions should be targeted at 
+     something more specific than "developers". If you don't understand 
+     how varied and wide the audience is, you'll inadvertently break or block 
+     things.
+
+   * There are experts who work on all parts of the stack; try asking how 
+     documentation changes ought to be made in their respective sections.
+
+   * Start with something small. It is okay to add a "patch" to fix a typo 
+     or suggest a word change; larger changes to files or structure require 
+     research and testing first, as well as some logic for why you think 
+     something needs changed.
+
+   * Most documentation should wrap at about ``80``. We do our best to help 
+     authors source-link and maintain their own code and contributions; 
+     overwriting something already documented doesn't always improve it.
+
+   * Be careful editing files with links already present in them; deleting 
+     links to papers, citations, or sources is discouraged.
+
+   * 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 in a separate repository and to link 
+     back to the stable ``op`` or Ops that you use in your project.
+
+For updates within 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 changes made, additions, deletions, and feature requests.
 
@@ -36,7 +63,6 @@ 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 nGraph Library 
    or core repos; best practice is to maintain any project-specific examples, 
    tests, or walk-throughs in a separate repository.
@@ -45,9 +71,11 @@ upcoming `ngraph.ai`_ release.
 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 nGraph Library's `documentation repo`_, here is an example of best practice: 
+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 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" 
@@ -73,8 +101,7 @@ 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. 
+this works in the current |version| version of nGraph Library documentation.
 
 
 Adding captions to code blocks 

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

@@ -11,29 +11,36 @@ This page includes additional documentation updates.
 We are pleased to announce the release of version |version|-doc.
 
 
-0.21-doc
+==============================
+
+Core updates for |version|
+~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
++ More ONNX ops
++ Optimizations
++ Don't reseed RNG on each use
+
+0.22-doc
 --------
 
-Documentation updates
-~~~~~~~~~~~~~~~~~~~~~
++ Initial doc and API for IntelGPU backend. 
++ DynamicBackend API.
++ Note deprecation of support of MXNet's ``ngraph-mxnet`` PyPI.
++ Noted changes on graph inspection options resultant from PR 3016.
++ Added better tips and details to doc-contributor-README.
 
-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.
-+ 
+.. important:: Pre-releases (``-rc-0.*``) have newer features, and are less stable.  
 
 
-Core updates for |version|
-~~~~~~~~~~~~~~~~~~~~~~~~~~~
+Changelog on Previous Releases
+==============================
+
+For downloads formatted as ``.zip`` and ``tar.gz``, see 
+https://github.com/NervanaSystems/ngraph/releases.
+
+0.21
+----
 
 + The offset argument in tensor reads and writes has been removed
 + Save/load API
@@ -43,16 +50,24 @@ Core updates for |version|
 + Provenance improvements
 + offset arg for tensor creation is deprecated
 + static linking support
++ Initial test of 0.21-doc
 
+0.21-doc
+--------
 
-.. important:: Pre-releases (``-rc-0.*``) have newer features, and are less stable.  
-
+Summary of documentation-related changes:
 
-Changelog on Previous Releases
-==============================
++ Updated :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.
++ Removed deprecated TensorAPI.
 
-For downloads formatted as ``.zip`` and ``tar.gz``, see 
-https://github.com/NervanaSystems/ngraph/releases.
 
 0.20
 ----

python/BUILDING.md

@@ -2,10 +2,10 @@
 
 ## Building nGraph Python Wheels
 
-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:
+If you want to try a newer version of nGraph's Python API than is available 
+from PyPI, you can build the latest version from source code. This process is 
+very similar to what is outlined in our [ngraph_build] instructions with two 
+important differences:
 
 1. You must specify: `-DNGRAPH_PYTHON_BUILD_ENABLE=ON` and `-DNGRAPH_ONNX_IMPORT_ENABLE=ON` 
    when running `cmake`.
@@ -18,7 +18,7 @@ with two important differences:
 
 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: 
+checked out and built `0.21` for Python 3.7, you might see something like: 
 
     $ ls python/dist/
     ngraph-core-0.21.0rc0.tar.gz  

python/README.md

@@ -18,8 +18,8 @@ boost compared to native implementations.
 
 nGraph can be used directly with the [Python API][api_python] described here, or 
 with the [C++ API][api_cpp] described in the [core documentation]. Alternatively, 
-its performance benefits can be realized through a frontend such as 
-[TensorFlow][frontend_tf], [MXNet][frontend_mxnet], and [ONNX][frontend_onnx].
+its performance benefits can be realized through frontends such as 
+[TensorFlow][frontend_tf], [PaddlePaddle][paddle_paddle] and [ONNX][frontend_onnx].
 You can also create your own custom framework to integrate directly with the 
 [nGraph Ops] for highly-targeted graph execution.
 
@@ -77,7 +77,7 @@ print('Result = ', result)
 
 [up to 45X]: https://ai.intel.com/ngraph-compiler-stack-beta-release/
 [frontend_onnx]: https://pypi.org/project/ngraph-onnx/
-[frontend_mxnet]: https://pypi.org/project/ngraph-mxnet/ 
+[paddle_paddle]: https://ngraph.nervanasys.com/docs/latest/frameworks/paddle_integ.html 
 [frontend_tf]: https://pypi.org/project/ngraph-tensorflow-bridge/
 [ngraph_github]: https://github.com/NervanaSystems/ngraph "nGraph on GitHub"
 [ngraph_building]: https://github.com/NervanaSystems/ngraph/blob/master/python/BUILDING.md "Building nGraph"