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submodule
ngraph
Commits
38ebc0e1
Commit
38ebc0e1
authored
Nov 27, 2018
by
L.S. Cook
Committed by
Adam Procter
Nov 27, 2018
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Add release notes and improve rendering of changes.md (#2117)
parent
1e220dee
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10 changed files
with
57 additions
and
10 deletions
+57
-10
README.md
README.md
+1
-1
Dockerfile.ngraph
contrib/docker/Dockerfile.ngraph
+3
-0
Dockerfile.ngraph.centos74
contrib/docker/Dockerfile.ngraph.centos74
+5
-0
Dockerfile.ngraph.centos74_gpu
contrib/docker/Dockerfile.ngraph.centos74_gpu
+2
-0
Dockerfile.ngraph.ubuntu1604
contrib/docker/Dockerfile.ngraph.ubuntu1604
+3
-0
Dockerfile.ngraph.ubuntu1604_gpu
contrib/docker/Dockerfile.ngraph.ubuntu1604_gpu
+2
-0
conf.py
doc/sphinx/source/conf.py
+7
-2
framework-integration-guides.rst
doc/sphinx/source/framework-integration-guides.rst
+1
-1
index.rst
doc/sphinx/source/index.rst
+4
-2
release-notes.rst
doc/sphinx/source/project/release-notes.rst
+29
-4
No files found.
README.md
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38ebc0e1
...
...
@@ -103,7 +103,7 @@ to improve it:
[
Pip package
]:
https://github.com/NervanaSystems/ngraph-onnx#installing-ngraph-onnx
[
Build from source
]:
https://github.com/NervanaSystems/ngraph-tf
[
Enable the module
]:
https://github.com/NervanaSystems/ngraph/blob/mbrookhart/mxnet_tutorial/doc/sphinx/source/shared/mxnet_tutorial.rst
[
Source compile
]:
https://github.com/NervanaSystems/ngraph-mxnet/blob/master/
NGRAPH_
README.md
[
Source compile
]:
https://github.com/NervanaSystems/ngraph-mxnet/blob/master/README.md
[
nGraph-ONNX
]:
https://github.com/NervanaSystems/ngraph-onnx/blob/master/README.md
[
nGraph-ONNX adaptable
]:
https://ai.intel.com/adaptable-deep-learning-solutions-with-ngraph-compiler-and-onnx/
[
nGraph for PyTorch developers
]:
https://ai.intel.com/investing-in-the-pytorch-developer-community
...
...
contrib/docker/Dockerfile.ngraph
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38ebc0e1
...
...
@@ -38,4 +38,7 @@ RUN pip install breathe
# need numpy to successfully build docs for python_api
RUN pip install numpy
# release notes need this markdown extension
# RUN python3 -m pip install m2r
WORKDIR /home
contrib/docker/Dockerfile.ngraph.centos74
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38ebc0e1
...
...
@@ -46,6 +46,7 @@ RUN c++ --version
RUN easy_install pip
RUN pip install virtualenv
# Install some pip packages
# need to use sphinx version 1.6 to build docs
...
...
@@ -61,4 +62,8 @@ RUN pip install breathe
# need numpy to successfully build docs for python_api
RUN pip install numpy
# release notes need this markdown extension
# RUN python3 -m pip install m2r
WORKDIR /home
contrib/docker/Dockerfile.ngraph.centos74_gpu
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38ebc0e1
...
...
@@ -43,4 +43,6 @@ RUN pip install breathe
# need numpy to successfully build docs for python_api
RUN pip install numpy
# RUN python3 -m pip install m2r
WORKDIR /home
contrib/docker/Dockerfile.ngraph.ubuntu1604
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38ebc0e1
...
...
@@ -41,4 +41,7 @@ RUN pip install breathe
# need numpy to successfully build docs for python_api
RUN pip install numpy
# release notes need this markdown extension
# RUN python3 -m pip install m2r
WORKDIR /home
contrib/docker/Dockerfile.ngraph.ubuntu1604_gpu
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38ebc0e1
...
...
@@ -58,4 +58,6 @@ RUN pip install breathe
# need numpy to successfully build docs for python_api
RUN pip install numpy
# RUN python3 -m pip install m2r
WORKDIR /home
doc/sphinx/source/conf.py
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38ebc0e1
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
...
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@@ -42,6 +44,10 @@ extensions = [
'breathe'
,
]
# source_suffix = '.rst'
source_suffix
=
[
'.rst'
,
'.md'
]
# Add any paths that contain templates here, relative to this directory.
templates_path
=
[
'_templates'
]
static_path
=
[
'static'
]
...
...
@@ -60,8 +66,7 @@ project = u'Intel® nGraph Library'
copyright
=
'2018, Intel Corporation'
author
=
'Intel Corporation'
# License specifics
# TBD
# License specifics see LICENSE of component
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
...
...
doc/sphinx/source/framework-integration-guides.rst
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38ebc0e1
...
...
@@ -46,7 +46,7 @@ nGraph-TensorFlow bridge.
.. _nGraph-MXNet: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/
NGRAPH_
README.md
.. _nGraph-MXNet: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/README.md
.. _MXNet: http://mxnet.incubator.apache.org
.. _DSO: http://csweb.cs.wfu.edu/%7Etorgerse/Kokua/More_SGI/007-2360-010/sgi_html/ch03.html
.. _being the fastest: https://github.com/soumith/convnet-benchmarks
...
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doc/sphinx/source/index.rst
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...
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@@ -21,6 +21,9 @@
Welcome
=======
See the latest :doc:`project/release-notes`.
.. figure:: graphics/599px-Intel-ngraph-ecosystem.png
:width: 599px
...
...
@@ -127,4 +130,4 @@ Indices and tables
.. _Movidius: https://www.movidius.com/
.. _contributions: https://github.com/NervanaSystems/ngraph#how-to-contribute
.. _TensorFlow bridge to nGraph: https://github.com/NervanaSystems/ngraph-tf/blob/master/README.md
.. _Compiling MXNet with nGraph: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/NGRAPH_README.md
\ No newline at end of file
.. _Compiling MXNet with nGraph: https://github.com/NervanaSystems/ngraph-mxnet/blob/master/README.md
doc/sphinx/source/project/release-notes.rst
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@@ -3,12 +3,37 @@
Release Notes
#############
This is release |release|.
|release|
This release focuses on accelerating deep learning inference workloads on
Intel® Xeon® (CPU processor) and has the following key features:
API Changes
===========
* Out-of-box installation experience for TensorFlow*, MXNet*, and ONNX.
* Validated optimizations for 17 workloads each on both TensorFlow and MXNet,
as well as 14 for ONNX.
* Support for Ubuntu 16.04 (TensorFlow, MXNet and ONNX).
* Support for OSX 10.13.x (buildable for TensorFlow and MXNet).
.. literalinclude:: ../../../../changes.md
This |version| release includes optimizations built for popular workloads
already widely deployed in production environments. These workloads cover
the following categories:
* ``image recognition & segmentation``
* ``object detection``
* ``language translation``
* ``speech generation & recognition``
* ``recommender systems``
* ``Generative Adversarial Networks (GAN)``
* ``reinforcement learning``
In our tests, the optimized workloads can perform up to 45X faster than native
frameworks, and we expect performance gains for other workloads due to our
powerful :doc:`../fusion/index` feature.
See also our recent `API changes`_
.. _API changes: https://github.com/NervanaSystems/ngraph/blob/master/changes.md
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