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Update for release 1.7.0
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Jennifer Myers committed Nov 21, 2016
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12 changes: 12 additions & 0 deletions ChangeLog
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# ChangeLog

## v1.7.0 (2016-11-21):

* Update Data Loader to aeon https://github.com/NervanaSystems/aeon for flexible,
multi-threaded data loading and transformations
* Add Neural Machine Translation model
* Remove Fast RCNN model (use Faster RCNN model instead)
* Remove music_genres example
* Fix super blocking for small N with 1D conv
* Fix update-direct conv kernel for small N
* Add gradient clipping to Adam optimizer
* Documentation updates and bug fixes

## v1.6.0 (2016-09-21):

* Faster RCNN model
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28 changes: 8 additions & 20 deletions doc/source/index.rst
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Expand Up @@ -36,26 +36,14 @@ Features include:

New features in this release:

* Faster RCNN model
* Sequence to Sequence container and char_rae recurrent autoencoder model
* Reshape Layer that reshapes the input [#221]
* Pip requirements in requirements.txt updated to latest versions [#289]
* Remove deprecated data loaders and update docs
* Use NEON_DATA_CACHE_DIR envvar as archive dir to store DataLoader ingested data
* Eliminate type conversion for FP16 for CUDA compute capability >= 5.2
* Use GEMV kernels for batch size 1
* Alter delta buffers for nesting of merge-broadcast layers
* Support for ncloud real-time logging
* Add fast_style Makefile target
* Fix Python 3 builds on Ubuntu 16.04
* Run setup.py for sysinstall to generate version.py [#282]
* Fix broken link in mnist docs
* Fix conv/deconv tests for CPU execution and fix i32 data type
* Fix for average pooling with batch size 1
* Change default scale_min to allow random cropping if omitted
* Fix yaml loading
* Fix bug with image resize during injest
* Update references to the ModelZoo and neon examples to their new locations
* Update Data Loader to aeon https://github.com/NervanaSystems/aeon
* Add Neural Machine Translation model
* Remove Fast RCNN model (use Faster RCNN model instead)
* Remove music_genres example
* Fix super blocking for small N with 1D conv
* Fix update-direct conv kernel for small N
* Add gradient clipping to Adam optimizer
* Documentation updates and bug fixes
* See `change log`_.

We use neon internally at Nervana to solve our `customers' problems`_
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30 changes: 30 additions & 0 deletions doc/source/previous_versions.rst
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Previous Versions
=================

neon v1.6.0
-----------

|Docs160|_

neon v1.6.0 released September 21 2016 supporting:

* Faster RCNN model
* Sequence to Sequence container and char_rae recurrent autoencoder model
* Reshape Layer that reshapes the input [#221]
* Pip requirements in requirements.txt updated to latest versions [#289]
* Remove deprecated data loaders and update docs
* Use NEON_DATA_CACHE_DIR envvar as archive dir to store DataLoader ingested data
* Eliminate type conversion for FP16 for CUDA compute capability >= 5.2
* Use GEMV kernels for batch size 1
* Alter delta buffers for nesting of merge-broadcast layers
* Support for ncloud real-time logging
* Add fast_style Makefile target
* Fix Python 3 builds on Ubuntu 16.04
* Run setup.py for sysinstall to generate version.py [#282]
* Fix broken link in mnist docs
* Fix conv/deconv tests for CPU execution and fix i32 data type
* Fix for average pooling with batch size 1
* Change default scale_min to allow random cropping if omitted
* Fix yaml loading
* Fix bug with image resize during injest
* Update references to the ModelZoo and neon examples to their new locations

neon v1.5.4
-----------

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Initial public release of neon.

.. |Docs160| replace:: Docs
.. |Docs154| replace:: Docs
.. |Docs153| replace:: Docs
.. |Docs152| replace:: Docs
Expand All @@ -349,6 +378,7 @@ Initial public release of neon.
.. |Docs9| replace:: Docs
.. |Docs8| replace:: Docs
.. _cudanet: https://github.com/NervanaSystems/cuda-convnet2
.. _Docs160: http://neon.nervanasys.com/docs/1.6.0
.. _Docs154: http://neon.nervanasys.com/docs/1.5.4
.. _Docs153: http://neon.nervanasys.com/docs/1.5.3
.. _Docs152: http://neon.nervanasys.com/docs/1.5.2
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2 changes: 1 addition & 1 deletion setup.py
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import subprocess

# Define version information
VERSION = '1.6.0'
VERSION = '1.7.0'
FULLVERSION = VERSION
write_version = True

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