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Comment: fused RNN OPs for CPU

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  • Code Freeze: End of June
  • Release published: July

 

Proposed content:

ProjectLead ContributorProject DocsNotes
Scala Inference APINaveen SwamyMXNet Scala Inference API 
ONNX Export from MXNetRoshani NagmoteProposal: ImportExport module 
Gluon Vision Model Zoozhasheng@apache.org  
Fix Flaky Testszhasheng@apache.orgGithub Flaky Tests 
MKL-DNNPatric Zhao, Da ZhengMKL-DNN integration designexperimental in v1.2, upgrade to GA in v1.3
Proper support for Types

Sebastian (Wolfram)

(sebastianbod@gmail.com) or taliesinb@gmail.com


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

Sparse Tensor support for GluonHaibin Lin
experimental feature
Android supportAnton
experimental feature or can it be GA?
Topology-aware AllReduce

Carl Yang

Topology-aware AllReduce Proposalexperimental feature
control flow operatorsDa Zheng,Optimize dynamic neural networksThis is the first step towards optimizing dynamic neural networks by adding symbolic and imperative control flow operators (foreach, while_loop, maybe ifelse). This step extends Gluon to hybridize models with control flow.
Clojure packageCarin MeierMXNet Clojureexperimental clojure language binding
Fused RNN Operators for CPUPatric Zhao, Tao LvFused CPU RNN DesignLSTM/GRU PR has been merged; vRNN will PR soon


Completed in v1.2Lead ContributorProject DocsNotes
Distributed Training for FP16 https://github.com/apache/incubator-mxnet/pull/10183v1.2
Model Quantization - ExperimentalExperimental quantizationv1.2
Support for TensorBoard
 Jun Wu 
Logging MXNet Data for Visualization in TensorBoard (a separate repo)v1.2 
Friendly exception handling Anirudh SubramanianImproved Exception Handling in MXNetv1.2

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