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[P] Torchbearer version 0.4.0 released, now with regularisers (Mixup, CutOut, CutMix, etc.), PyCM, LiveLossPlot, a set of Colab examples and much more

Now in the latest version of torchbearer:

  • A host of regularisers including: Mixup, CutOut, CutMix, Sample Pairing, Label Smoothing and Random Erase
  • Built-in integration with PyCM for generating confusion matrices
  • Built-in support for LiveLossPlot
  • A set of example colab notebooks
  • Bug fixes and more listed in the CHANGELOG: https://github.com/pytorchbearer/torchbearer/blob/master/CHANGELOG.md

Install: http://www.pytorchbearer.org/#install

Check out the examples at: http://www.pytorchbearer.org/#examples

Find us on GitHub: https://github.com/pytorchbearer/torchbearer

Please take a look and let us know what you think!

submitted by /u/ethanwharris
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.