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| Project | Lead Contributor | Project Docs | Link to design discussion on dev@ | Notes | ||
|---|---|---|---|---|---|---|
| Horovod-MXNet Integration | Carl Yang, Lin Yuan, Darren Hu | Horovod-MXNet Integration | Discussion | Upgrade from experimental feature to GA? | ||
| Gluon Vision Model Zoo | zhasheng@apache.org | |||||
| Fix Flaky Tests | zhasheng@apache.org | Github Flaky Tests | Discussion | Resolve remaining flaky tests? | ||
| MKL-DNN | Patric Zhao, Da Zheng | MKL-DNN integration design | Discussion | Upgrade from experimental feature to GA | ||
| MKL-DNN based graph optimization and quantization by subgraph | Patric Zhao | MXNet Graph Optimization and Quantization based on subgraph and MKL-DNN | Discussion | experimental feature | ||
| Sparse Tensor support for Gluon | Haibin Lin | Gluon Sparse Support | Discussion | Upgrade from experimental feature to GA? |
Backlog (to be considered for post 1.4.0 MXNet release):
| Proper support for Types | Sebastian (Wolfram) | Backend for general purpose numerical packages (support for multipe types, proper testing for all supported types). Derive test priorities from Mathematica internal suite or integrate Mathematica into CI? Feedback: Users are observing instability, incomplete behavior vs. quality delivered by numpy / Pytorch. Haibin: many tests are not well written, most test only cover fp32, don't have good guidelines for community, operator tutorial lacks guidance on test requirements, suggest to develop guidelines (results are deterministic, cover all supported types), need to set quality standards as community grows Sebastian: presentation how it is done in Mathematica based on experience and learnings | ||
| Android support | Anton |
| Experimental feature or can it be GA? | ||||
| TensorRT Runtime Integration | Runtime Integration with TensorRT | Discussion | Upgrade from experimental feature for GA? |
1.3.0 release statistics
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