New Features

• Added Scala Inference APIs (#9678). See: MXNet Scala Inference API
• Added module to import ONNX models into MXNet (#9963). See: Proposal: ImportExport module
• Added support for Model Quantization with Calibration (#9552). 
• Added Exception Handling support for operators and iterators (#9681). See: Improved Exception Handling in MXNet
• Added MKLDNN support for MXNet (#9677). See: MKLDNN integration
• Added FP16 support for distributed training (#10183).
• Added Sparse support for Custom Operator (#10374).
• Add multi-proposal operator (CPU version) and fix the bug in multi-proposal operator (GPU version) (#9939).
• Profiling enhancements - VTune objects, individual operator profiling, C API profiling, Memory usage profiling   ()

Bug-fixes

• Test fixes - Flakiness/Bugs - (#9598, #9951, #10259, #10197, #10136, #10422). Please see: https://github.com/apache/incubator-mxnet/projects/9
• Fixed crash when profiler not enabled (#10306).
• Fixed uncaught exception for bucketing module when symbol name not specified (#10094).
• Fixed regression output layers (#9848).
• Fixed crash with mx.nd.ones (#10014).
• Fixed sample_multinomial crash when get_prob=True (#10413).
• Fixed buggy type inference in correlation (#10135).
• Fixed race condition for CPUSharedStorageManager->Free and launched workers at iter init stage to avoid frequent relaunch (#10096).
• Fixed DLTensor Conversion for int64 (#10083).
• Fixes for profiler (#9932)
• Fixed ndarray assignment issues (#10022, #9981).
• Fixed incorrect indices generated by device row sparse pull (#9887).
• Fixed print_summary bug in visualization module (#9492).
• Fixed cast storage support for same stypes (#10400).