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fix learning rate schedulers in PyTorch 2.0 (closes #3202) #3207

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merged 1 commit into from
May 17, 2023
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fix learning rate schedulers in PyTorch 2.0 (closes #3202) #3207

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14 changes: 10 additions & 4 deletions pyro/optim/optim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -138,10 +138,16 @@ def __call__(self, params: Union[List, ValuesView], *args, **kwargs) -> None:
if self.grad_clip[p] is not None:
self.grad_clip[p](p)

if isinstance(
self.optim_objs[p], torch.optim.lr_scheduler._LRScheduler
) or isinstance(
self.optim_objs[p], torch.optim.lr_scheduler.ReduceLROnPlateau
if (
hasattr(torch.optim.lr_scheduler, "_LRScheduler")
and isinstance(
self.optim_objs[p], torch.optim.lr_scheduler._LRScheduler
)
or hasattr(torch.optim.lr_scheduler, "LRScheduler")
and isinstance(self.optim_objs[p], torch.optim.lr_scheduler.LRScheduler)
or isinstance(
self.optim_objs[p], torch.optim.lr_scheduler.ReduceLROnPlateau
)
):
# if optim object was a scheduler, perform an optimizer step
self.optim_objs[p].optimizer.step(*args, **kwargs)
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