This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
Releases: apache/mxnet
Releases · apache/mxnet
MinPy compatible release
WARNING: THIS IS NOT AN APACHE SOFTWARE FOUNDATION RELEASE OF MXNET AS IT PREDATES MXNET JOINING THE APACHE SOFTWARE FOUNDATION
NNVM refactor
WARNING: THIS IS NOT AN APACHE SOFTWARE FOUNDATION RELEASE OF MXNET AS IT PREDATES MXNET JOINING THE APACHE SOFTWARE FOUNDATION
Version 0.8.0 Release
WARNING: THIS IS NOT AN APACHE SOFTWARE FOUNDATION RELEASE OF MXNET AS IT PREDATES MXNET JOINING THE APACHE SOFTWARE FOUNDATION
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
v0.7.0
WARNING: THIS IS NOT AN APACHE SOFTWARE FOUNDATION RELEASE OF MXNET AS IT PREDATES MXNET JOINING THE APACHE SOFTWARE FOUNDATION
This is an incomplete list among the many features added
- 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, see https://github.com/dmlc/mxnet-memonger
- 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 recoginition by @yzhang87
- Neural art by @antinucleon
- Detection, RCNN bt @precedenceguo
- Segmentation, FCN by @tornadomeet
- Face identification by @tornadomeet
- More on the example