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@BenjaminBossan BenjaminBossan released this 12 Apr 16:37
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v0.8.0
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Learn about vigilant mode.

This release contains improvements on the callback side of things. Thanks to new contributors, skorch now integrates with neptune through NeptuneLogger and Weights & Biases through WandbLogger. We also added PassthroughScoring, which automatically creates epoch level scores based on computed batch level scores.

If you want skorch not to meddle with moving modules and data to certain devices, you can now pass device=None and thus have full control. And if you would like to pass pandas DataFrames as input data but were unhappy with how skorch currently handles them, take a look at DataFrameTransformer. Moreover, we cleaned up duplicate code in the fit loop, which should make it easier for users to make their own changes to it. Finally, we improved skorch compatibility with sklearn 0.22 and added minor performance improvements.

As always, we're very thankful for everyone who opened issues and asked questions on diverse channels; all forms of feedback and questions are welcome. We're also very grateful for all contributors, some old but many new:

Alexander Kolb
Benjamin Ajayi-Obe
Boris Dayma
Jakub Czakon
Riccardo Di Maio
Thomas Fan
Yann Dubois

Here is a list of all the changes and their corresponding ticket numbers in detail:

Added

  • Added NeptuneLogger callback for logging experiment metadata to neptune.ai (#586)
  • Add DataFrameTransformer, an sklearn compatible transformer that helps working with pandas DataFrames by transforming the DataFrame into a representation that works well with neural networks (#507)
  • Added WandbLogger callback for logging to Weights & Biases (#607)
  • Added None option to device which leaves the device(s) unmodified (#600)
  • Add PassthroughScoring, a scoring callback that just calculates the average score of a metric determined at batch level and then writes it to the epoch level (#595)

Changed

  • When using caching in scoring callbacks, no longer uselessly iterate over the data; this can save time if iteration is slow (#552, #557)
  • Cleaned up duplicate code in the fit_loop (#564)

Fixed

  • Make skorch compatible with sklearn 0.22 (#571, #573, #575)
  • Fixed a bug that could occur when a new "settable" (via set_params) attribute was added to NeuralNet whose name starts the same as an existing attribute's name (#590)
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