ENH: ReduceLROnPlateau records the learning rate and works on batches#1075
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BenjaminBossan merged 3 commits intomasterfrom Dec 19, 2024
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Previously, when using ReduceLROnPlateau, we would not record the learning rates in history. The comment says that's because this class does not expose the get_last_lr method. I checked it again and it's now present, so let's use it. Furthermore, I made a change to enable ReduceLROnPlateau to step on each batch instead of each epoch. This is consistent with other learning rate schedulers.
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The CI is failing because of a change in sklearn 1.6 and requires PR #1076. |
githubnemo
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Dec 19, 2024
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Please welcome skorch 1.1.0 - a smaller release with a few fixes, a new notebook showcasing learning rate schedulers and mainly support for scikit-learn 1.6.0. Full list of changes: ### Added - Added a [notebook](https://github.com/skorch-dev/skorch/blob/master/notebooks/Learning_Rate_Scheduler.ipynb) that shows how to use Learning Rate Scheduler in skorch.(#1074) ### Changed - All neural net classes now inherit from sklearn's [`BaseEstimator`](https://scikit-learn.org/stable/modules/generated/sklearn.base.BaseEstimator.html). This is to support compatibility with sklearn 1.6.0 and above. Classification models additionally inherit from [`ClassifierMixin`](https://scikit-learn.org/stable/modules/generated/sklearn.base.ClassifierMixin.html) and regressors from [`RegressorMixin`](https://scikit-learn.org/stable/modules/generated/sklearn.base.RegressorMixin.html). (#1078) - When using the `ReduceLROnPlateau` learning rate scheduler, we now record the learning rate in the net history (`net.history[:, 'event_lr']` by default). It is now also possible to to step per batch, not only by epoch (#1075) - The learning rate scheduler `.simulate()` method now supports adding step args which is useful when simulation policies such as `ReduceLROnPlateau` which expect metrics to base their schedule on. (#1077) - Removed deprecated `skorch.callbacks.scoring.cache_net_infer` (#1088) ### Fixed - Fix an issue with using `NeuralNetBinaryClassifier` with `torch.compile` (#1058)
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Previously, when using
ReduceLROnPlateau, we would not record the learning rates in history. The code comment says that's because this class does not expose theget_last_lrmethod. I checked it again and it's now present, so let's use it.Furthermore, I made a change to enable
ReduceLROnPlateauto step on each batch (so far, only each epoch was supported). This is consistent with other learning rate schedulers.