MXNet Change Log

0.10.0

Overhauled documentation for commonly used Python APIs, Installation instructions, Tutorials, HowTos and MXNet Architecture.
Updated mxnet.io for improved readability.
Pad operator now support reflection padding.
Fixed a memory corruption error in threadedengine.
Added CTC loss layer to contrib package. See mx.contrib.sym.ctc_loss.
Added new sampling operators for several distributions (normal,uniform,gamma,exponential,negative binomial).
Added documentation for experimental RNN APIs.

Move symbolic API to NNVM @tqchen
- Most front-end C API are backward compatible
- Removed symbolic API in MXNet and relies on NNVM
New features:
- MXNet profiler for profiling operator-level executions
- mxnet.image package for fast image loading and processing
Change of JSON format
- param and attr field are merged to attr
- New code is backward-compatible can load old json format
OpProperty registration now is deprecated
- New operators are encouraged to register their property to NNVM op registry attribute
Known features removed limitations to be fixed
- Bulk segment execution not yet added.

This is the last release before the NNVM refactor.

CaffeOp and CaffeIter for interfacing with Caffe by @HrWangChengdu @cjolivier01
WrapCTC plugin for sequence learning by @xlvector
Improved Multi-GPU performance by @mli
CuDNN RNN support by @sbodenstein
OpenCV plugin for parallel image IO by @piiswrong
More operators as simple op
- Simple OP @tqchen
- element wise op with axis and broadcast @mli @sxjscience
Cudnn auto tuning for faster convolution by @piiswrong
More applications
- Faster RCNN by @precedenceguo

0.6 is skipped because there are a lot of improvements since initial release
More math operators
- elementwise ops and binary ops
Attribute support in computation graph
- Now user can use attributes to give various hints about specific learning rate, allocation plans etc
MXNet is more memory efficient
- Support user defined memory optimization with attributes
Support mobile applications by @antinucleon
Refreshed update of new documents
Model parallel training of LSTM by @tqchen
Simple operator refactor by @tqchen
- add operator_util.h to enable quick registration of both ndarray and symbolic ops
Distributed training by @mli
Support Torch Module by @piiswrong
- MXNet now can use any of the modules from Torch.
Support custom native operator by @piiswrong
Support data types including fp16, fp32, fp64, int32, and uint8 by @piiswrong
Support monitor for easy printing and debugging by @piiswrong
Support new module API by @pluskid
- Module API is a middle level API that can be used in imperative manner like Torch-Module
Support bucketing API for variable length input by @pluskid
Support CuDNN v5 by @antinucleon
More applications
- Speech recognition by @yzhang87
- Neural art by @antinucleon
- Detection, RCNN bt @precedenceguo
- Segmentation, FCN by @tornadomeet
- Face identification by @tornadomeet
- More on the example