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update changelog and readme
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Jopyth committed May 28, 2019
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6 changes: 6 additions & 0 deletions CHANGELOG.md
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Expand Up @@ -6,6 +6,12 @@ All notable changes to this project will be documented in this file.
The format is based on [Keep a Changelog](http://keepachangelog.com/)
and this project adheres to [Semantic Versioning](http://semver.org/).

## [0.3.1] - 2019-05-28

### Changed

- Upgrade base version of mxnet to *mxnet v1.4.1*

## [0.3.0] - 2019-05-21

### Added
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17 changes: 10 additions & 7 deletions README.md
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Expand Up @@ -5,17 +5,20 @@ A fork of the deep learning framework [mxnet](http://mxnet.io) to study and impl
This project is based on the [first version of BMXNet](https://github.com/hpi-xnor/BMXNet), but is different in that it reuses more of the original MXNet operators.
This aim was to have only minimal changes to C++ code to get better maintainability with future versions of mxnet.

## mxnet version

This version of BMXNet 2 is based on: *mxnet v1.4.1*

## News

- **May 21, 2019** - Upgraded to MXNet v1.4.0
- Model converter released ([Test & Example](tests/binary/test_converter.py))
- All changes: [Changelog](CHANGELOG.md)
- **Sep 01, 2018** - MXNet v1.3.0
- We are currently rebuilding BMXNet to utilize the new Gluon API for better maintainability
See all BMXNet changes: [Changelog](CHANGELOG.md).

- **May 21, 2019**
- Model converter for deployment released ([Test & Example](tests/binary/test_converter.py))
- **Sep 01, 2018**
- We rebuilt BMXNet to utilize the new Gluon API for better maintainability
- To build binary neural networks, you can use drop in replacements of convolution and dense layers (see [Usage](#usage)):
- Changes are now documented in the [Changelog](CHANGELOG.md)
- Note that this project is still in beta and changes might be frequent
- We do not yet support deployment and inference with binary operations and models (please use the [first version of BMXNet](https://github.com/hpi-xnor/BMXNet) instead if you need this).

# Setup

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