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neon 2.2 release notes (#1010)
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* neon 2.2 release notes
* mention "latest" tag
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wei-v-wang authored and Jennifer Myers committed Sep 27, 2017
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8 changes: 7 additions & 1 deletion ChangeLog
@@ -1,8 +1,14 @@
# ChangeLog

## v2.2.0 (2017-08-XX):
## v2.2.0 (2017-09-27):

* Update MKLML version 20170908 that fixes a bug related to data conversions)
* Add SSD example for bounding box object detection that works for both GPU and MKL backend
* Add DeepSpeech2 MKL backend optimization that features ~3X improvement
* Update aeon to 1.0.0 including new version of manifest (doc/source/loading_data.rst#aeon-dataloader)
* Add CHWD Support for Batch Normalization in mkl backend
* Modify ResNet-50 model's last layer to match the original ResNet-50 model paper
* Enable Seq2Seq testing and benchmarking

## v2.1.0 (2017-08-02):

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2 changes: 1 addition & 1 deletion README.md
Expand Up @@ -32,7 +32,7 @@ neon (conda users see the [guide](http://neon.nervanasys.com/docs/latest/install
. .venv/bin/activate
```

Starting after neon v2.2.0, the master branch of neon will be updated weekly with work-in-progress toward the next release. Check out a release tag (e.g., "git checkout v2.2.0") for a stable release.
Starting after neon v2.2.0, the master branch of neon will be updated weekly with work-in-progress toward the next release. Check out a release tag (e.g., "git checkout v2.2.0") for a stable release. Or simply check out the "latest" release tag to get the latest stable release (i.e., "git checkout latest")

**Warning**

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10 changes: 4 additions & 6 deletions doc/source/index.rst
Expand Up @@ -36,12 +36,10 @@ Features include:

New features in this release:

* Set MKL backend (-b mkl) as the default CPU backend on Linux (use -b cpu to specify original CPU backend)
* Update MKLML version 20170720 (AVX512 code paths enabled by default and conversion optimizations)
* Simplify ResNet example
* Makefiles now check for virtualenv and pkg-config (NervanaSystems/neon#383)
* Fix Deep Speech2 model on MKL backend
* Fix MKL installation for "make sysinstall"
* Update MKLML version 20170908 that fixes a bug related to data conversions)
* Add SSD example for bounding box object detection that works for both GPU and MKL backend
* Add DeepSpeech2 MKL backend optimization that features ~3X improvement
* Update aeon to 1.0.0 including new version of manifest (doc/source/loading_data.rst#aeon-dataloader)
* See more in the `change log`_.

We use neon internally at Intel Nervana to solve our `customers' problems`_
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9 changes: 9 additions & 0 deletions doc/source/installation.rst
Expand Up @@ -71,11 +71,20 @@ If you use the `Anaconda <http://docs.continuum.io/anaconda/index>`__ python
distribution, please see the Anaconda Install section. Otherwise, to
setup neon in this manner, run the following commands:

.. code-block:: bash
git clone https://github.com/NervanaSystems/neon.git
cd neon; git checkout latest; make
The above checks out the latest stable release (e.g. a tagged release version v2.2.0) and build neon.
Alternatively, you can check out and build the latest master branch:

.. code-block:: bash
git clone https://github.com/NervanaSystems/neon.git
cd neon; make
This will install the files in the ``neon/.venv/`` directory and will use the python version in the
default PATH. Note that neon would automatically download the released MKLML library that
features MKL support.
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11 changes: 11 additions & 0 deletions doc/source/previous_versions.rst
Expand Up @@ -16,6 +16,17 @@
Previous Versions
=================
neon v2.1.0
-----------

neon v2.1.0 released August 2, 2017 supporting:

* Set MKL backend (-b mkl) as the default CPU backend on Linux (use -b cpu to specify original CPU backend)
* Update MKLML version 20170720 (AVX512 code paths enabled by default and conversion optimizations)
* Simplify ResNet example
* Makefiles now check for virtualenv and pkg-config (NervanaSystems/neon#383)
* Fix Deep Speech2 model on MKL backend
* Fix MKL installation for "make sysinstall"

neon v2.0.0
-----------
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2 changes: 1 addition & 1 deletion setup.py
Expand Up @@ -18,7 +18,7 @@
import subprocess

# Define version information
VERSION = '2.1.0'
VERSION = '2.2.0'
FULLVERSION = VERSION
write_version = True

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