Mxnet

Latest version: v1.9.1

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0.8

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

0.7

0.6

- 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](https://github.com/apache/mxnet/tree/v0.7.0/example/neural-style) by antinucleon
- [Detection](https://github.com/apache/mxnet/tree/v0.7.0/example/rcnn), RCNN bt precedenceguo
- [Segmentation](https://github.com/apache/mxnet/tree/v0.7.0/example/fcn-xs), FCN by tornadomeet
- [Face identification](https://github.com/tornadomeet/mxnet-face) by tornadomeet
- More on the example

0.5

- All basic modules ready

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