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fix docs
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docs/source-pytorch/cli/lightning_cli_intermediate_2.rst

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@@ -201,9 +201,10 @@ If the scheduler you want needs other arguments, add them via the CLI (no need t
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.. code:: bash
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python main.py fit --optimizer=Adam --lr_scheduler=ReduceLROnPlateau --lr_scheduler.monitor=epoch
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python main.py fit --optimizer=Adam --lr_scheduler=ReduceLROnPlateau --lr_scheduler.monitor=train_loss
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Furthermore, any custom subclass of ``torch.optim.lr_scheduler.LRScheduler`` can be used as learning rate scheduler:
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(assuming you have a ``train_loss`` metric logged). Furthermore, any custom subclass of
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``torch.optim.lr_scheduler.LRScheduler`` can be used as learning rate scheduler:
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.. code:: python
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@@ -212,7 +213,6 @@ Furthermore, any custom subclass of ``torch.optim.lr_scheduler.LRScheduler`` can
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from lightning.pytorch.cli import LightningCLI
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from lightning.pytorch.demos.boring_classes import DemoModel, BoringDataModule
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class LitLRScheduler(torch.optim.lr_scheduler.CosineAnnealingLR):
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def step(self):
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print("", "using LitLRScheduler", "")

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