ReduceLROnPlateau LRScheduler error #462
Description
Hi,
I tried to use the LRScheduler handler for ReduceLROnPlateau from torch.optim and it threw an a TypeError:
plateau_scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer=optimizer, mode='min', factor=0.5, patience=1)
ignite_plateau_scheduler = LRScheduler(plateau_scheduler)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-13-56cb18e5af57> in <module>
1 plateau_scheduler = optim.lr_scheduler.ReduceLROnPlateau(optimizer=optimizer, mode='min', factor=0.5, patience=1)
----> 2 ignite_plateau_scheduler = LRScheduler(plateau_scheduler)
/net/vaosl01/opt/NFS/su0/anaconda3/envs/nlpbook/lib/python3.7/site-packages/pytorch_ignite-0.2.0-py3.7.egg/ignite/contrib/handlers/param_scheduler.py in __init__(self, lr_scheduler, save_history, **kwds)
424 if not isinstance(lr_scheduler, _LRScheduler):
425 raise TypeError("Argument lr_scheduler should be a subclass of torch.optim.lr_scheduler._LRScheduler, "
--> 426 "but given {}".format(type(lr_scheduler)))
427
428 if len(lr_scheduler.optimizer.param_groups) > 1:
TypeError: Argument lr_scheduler should be a subclass of torch.optim.lr_scheduler._LRScheduler, but given <class 'torch.optim.lr_scheduler.ReduceLROnPlateau'>
The example from the documentation with StepLR works without problems. It seems that the objects belong to different base classes. This is indeed true as can be from the source here. StepLR inherits from _LRScheduler, while ReduceLROnPlateau does not have a base class (inherits from object). Is there a way to bypass that check for this scheduler?
Thanks.