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DJL v0.6.0 release notes

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@keerthanvasist keerthanvasist released this 25 Jun 03:04
· 2076 commits to master since this release

DJL 0.6.0 brings stable Android support, ONNX Runtime experimental inference support, experimental training support for PyTorch.

Key Features

  • Stable Android inference support for PyTorch models
    • Provide abstraction for Image processing using ImageFactory
  • Experimental support for inference on ONNX models
  • Initial experimental training and imperative inference support for PyTorch engine
  • Experimental support for using multi-engine
  • Improved usage for NDIndex - support for ellipsis notation, arguments
  • Improvements to AbstractBlock to simplify custom block creation
  • Added new datasets

Documentation and examples

Breaking changes

  • ModelZoo Configuration changes
  • ImageFactory changes
  • Please refer to javadocs for minor API changes

Known issues

  • Issue with training with MXNet in multi-gpu instances


Thank you to the following community members for contributing to this release:

Christoph Henkelmann, Frank Liu, Jake Lee, JonTanS, Keerthan Vasist, Lai Wei, Qing, Qing Lan, Victor Zhu, Zach Kimberg, ai4java, aksrajvanshi