Feat/pytorch lightning #702
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dennisbader
requested review from
hrzn,
pennfranc and
tomasvanpottelbergh
as code owners
hrzn
reviewed
Dec 22, 2021
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Looks like a great start. Maybe so far my main comment concerns the PL trainer; I feel (but might be wrong) that it would be nice to change our models' signatures, in order to put everything training related in fit(). So for instance we could receive either the PL trainer kwargs (or the PL trainer itself?) as arguments to fit(). In init we could also receive training-related arguments (or PL trainer directly), but those would only be used as default if nothing is specified to fit() (as we are currently doing with epochs).
| def configure_optimizers(self): | ||
| """sets up optimizers""" | ||
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| # TODO: i think we can move this to to pl.Trainer(). and could probably be simplified |
hrzn
approved these changes
Feb 13, 2022
| <https://pytorch-lightning.readthedocs.io/en/stable/extensions/callbacks.html>`_ | ||
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| .. highlight:: python | ||
| .. code-block:: python |
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Addresses #577.
Update of #697
pl_trainer_pararms. This will set up a trainer with some darts specifics + the user's customization