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Releases: sktime/pytorch-forecasting

Make pip installable from master branch

23 Aug 20:09
5eb136e
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Update build system requirements to be parsed correctly when installing with pip install https://github.com/jdb78/pytorch-forecasting/

Improving tests

23 Aug 17:07
72e687b
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  • Add tests for MacOS
  • Automatic releases
  • Coverage reporting

Patch release

23 Aug 11:18
a3fbb80
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This release improves robustness of the code.

Fixing bug across code, in particularly

  • Ensuring that code works on GPUs
  • Adding tests for models, dataset and normalisers
  • Test using GitHub Actions (tests on GPU are still missing)

Extend documentation by improving docstrings and adding two tutorials.

Improving default arguments for TimeSeriesDataSet to avoid surprises

Minor release

16 Aug 21:05
b9758be
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Minor release

Added

  • Basic tests for data and model (mostly integration tests)
  • Automatic target normalization
  • Improved visualization and logging of temporal fusion transformer
  • Model bugfixes and performance improvements for temporal fusion transformer

Modified

  • Metrics are reduced to calculating loss. Target transformations are done by new target transformer