THIS IS A TEST INSTANCE. ALL YOUR CHANGES WILL BE LOST!!!!
New Features - Export MXNet models to ONNX format
- With this feature, now MXNet models can be exported to ONNX format.(#11213 ) Currently, MXNet supports ONNX v1.2.1 . API documentation.
- Checkout this example which shows how to use MXNet to ONNX exporter APIs. ONNX protobuf so that those models can be imported in other frameworks for inference.
New Features - Topology-aware AllReduce
New Features - Clojure package (experimental)
- MXNet now supports the Clojure programming language. The MXNet Clojure package brings flexible and efficient GPU computing and state-of-art deep learning to Clojure. It enables you to write seamless tensor/matrix computation with multiple GPUs in Clojure. It also lets you construct and customize the state-of-art deep learning models in Clojure, and apply them to tasks, such as image classification and data science challenges.(#11205)
- Checkout examples and API documentation here.
New Features - TensorRT Runtime Integration
- This feature introduces runtime integration of TensorRT into MxNet, in order to accelerate inference. (#11325)
New Features - Sparse Tensor support for Gluon
New Features - Fused RNN Operators for CPU
New Features - Control flow operators
- This is the first step towards optimizing dynamic neural networks by adding symbolic and imperative control flow operators (foreach, while_loop, maybe ifelse). foreach and while_loop have been merged. ifelse has been submitted for review, but is unlikely merged in this release.
MKL-DNN
Fix Flaky Tests