Commit 1e5e7145 authored by L.S. Cook's avatar L.S. Cook Committed by Scott Cyphers

Architecture and feature docs5 (#2146)

* New branch for doc changes

* Slightly out of scope doc requests to make some people happier;
this does technically change the API

* Doc versioning even with Beta release

* Don't remove markdown version of contrib guidelines after all

* Update changes from earlier branch

* Make sure ngraph-tf links to readme
parent 281c8ea1
# nGraph Compiler Stack
# nGraph Compiler Stack (Beta)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://github.com/NervanaSystems/ngraph/blob/master/LICENSE) [![Build Status][build-status-badge]][build-status]
......@@ -16,12 +16,12 @@ workloads on CPU for inference, please refer to the links below.
| Framework (Version) | Installation guide | Notes
|----------------------------|----------------------------------------|-----------------------------------
| TensorFlow* 1.12 | [Pip package] or [Build from source] | 17 [Validated workloads]
| MXNet* 1.4 | [Enable the module] or [Source compile]| 17 [Validated workloads]
| ONNX 1.3 | [Pip package] | 14 [Validated workloads]
| TensorFlow* 1.12 | [Pip install](https://github.com/NervanaSystems/ngraph-tf) or [Build from source](https://github.com/NervanaSystems/ngraph-tf) | 20 [Validated workloads]
| MXNet* 1.3 | [Pip install](https://github.com/NervanaSystems/ngraph-mxnet#Installation) or [Build from source](https://github.com/NervanaSystems/ngraph-mxnet#building-with-ngraph-support)| 18 [Validated workloads]
| ONNX 1.3 | [Pip install](https://github.com/NervanaSystems/ngraph-onnx#installation) | 14 [Validated workloads]
Frameworks using nGraph Compiler stack to execute workloads have shown
**up to 45X** performance boost when compared to native framework
[**up to 45X**](https://ai.intel.com/ngraph-compiler-stack-beta-release/) performance boost when compared to native framework
implementations. We've also seen performance boosts running workloads that
are not included on the list of [Validated workloads], thanks to our
powerful subgraph pattern matching.
......@@ -100,9 +100,6 @@ to improve it:
[develop-without-lockin]: doc/sphinx/source/graphics/develop-without-lockin.png "Develop on any part of the stack wtihout lockin"
[Movidius™ Myriad™ 2]:https://www.movidius.com/solutions/vision-processing-unit
[PlaidML]: https://github.com/plaidml/plaidml
[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/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/
......
......@@ -1634,7 +1634,7 @@ body {
color: #38403f;
min-height: 100%;
overflow-x: hidden;
background: #edf0f2;
background: #fcfcfc;
}
.wy-text-left {
......@@ -3193,7 +3193,7 @@ footer span.commit code, footer span.commit .rst-content tt, .rst-content footer
}
@media screen and (min-width: 1400px) {
.wy-nav-content-wrap {
background: #0C7881;
background: #fcfcfc;
}
.wy-nav-content {
......
......@@ -73,9 +73,11 @@ author = 'Intel Corporation'
# built documents.
#
# The short X.Y version.
version = '0.9'
# The full version, including alpha/beta/rc tags.
release = '0.9.0'
version = '0.10'
# The Documentation full version, including alpha/beta/rc tags. Some features
# available in the latest code will not necessarily be documented first
release = '0.10.1'
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
......
......@@ -50,4 +50,4 @@ nGraph-TensorFlow bridge.
.. _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
.. _ngraph tensorflow bridge README: https://github.com/NervanaSystems/ngraph-tf
.. _ngraph tensorflow bridge README: https://github.com/NervanaSystems/ngraph-tf/blob/master/README.md
......@@ -15,19 +15,22 @@ TensorFlow
:widths: 27, 53
:escape: ~
Resnet50 v1 and v2, Image recognition
Inception V3 and V4, Image recognition
Resnet50 v1, Image recognition
Resnet50 v2, Image recognition
Inception V3, Image recognition
Inception V4, Image recognition
Inception-ResNetv2, Image recognition
MobileNet v1, Image recognition
SqueezeNet v1.1, Image recognition
DenseNet-121, Image recognition
MobileNet v2, Image recognition
VGG16, Image recognition
SSD-VGG16, Object detection
SSD-MobileNetv1, Object detection
R-FCN, Object detection
Faster RCNN, Object detection
Yolo v2, Object detection
Transformer-LT, Language translation
Wide & Deep, Recommender system
NCF, Recommender system
WaveNet, Speech generation
U-Net, Image segmentation
DCGAN, Generative adversarial network
DRAW, Image generation
......@@ -41,7 +44,8 @@ MXNet
:widths: 27, 53
:escape: ~
Resnet50 v1 and v2, Image recognition
Resnet50 v1, Image recognition
Resnet50 v2, Image recognition
DenseNet-121, Image recognition
InceptionV3, Image recognition
InceptionV4, Image recognition
......@@ -70,10 +74,10 @@ Additionally, we validated the following workloads are functional through nGraph
:widths: 27, 53
:escape: ~
ResNet-50, Image recognition
DenseNet-121, Image recognition
Inception-v1, Image recognition
Inception-v2, Image recognition
ResNet-50, Image recognition
Shufflenet, Image recognition
SqueezeNet, Image recognition
VGG-19, Image recognition
......
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