Bugfix: Scheduler monitor for manual optimization

docs/source/common/optimizers.rst

@@ -230,6 +230,23 @@ If you want to call ``lr_scheduler.step()`` every ``n`` steps/epochs, do the fol
         if self.trainer.is_last_batch and (self.trainer.current_epoch + 1) % n == 0:
             sch.step()
 
+If you want to call schedulers that require a metric value after each epoch, consider doing the following:
+
+.. testcode::
+
+    def __init__(self):
+        super().__init__()
+        self.automatic_optimization = False
+
+    def training_epoch_end(self, outputs):
+        sch = self.lr_schedulers()
+
+        # If the selected scheduler is a ReduceLROnPlateau scheduler.
+        if isinstance(sch, torch.optim.lr_scheduler.ReduceLROnPlateau):
+            loss = th.stack([x['loss'] for x in outputs]).mean()
+            loss = self.all_gather(loss).mean()
+            sch.step(loss)
+
 -----
 
 Improve training speed with model toggling

pytorch_lightning/trainer/optimizers.py

@@ -122,7 +122,23 @@ def configure_schedulers(
         lr_schedulers = []
         default_config = _get_default_scheduler_config()
         for scheduler in schedulers:
-            if isinstance(scheduler, dict):
+            if is_manual_optimization:
+                if isinstance(scheduler, dict):
+                    invalid_keys = {'interval', 'frequency', 'reduce_on_plateau', 'monitor', 'strict'}
+                    keys_to_warn = [k for k in scheduler.keys() if k in invalid_keys]
+
+                    if keys_to_warn:
+                        rank_zero_warn(
+                            f'The lr scheduler dict contains the key(s) {keys_to_warn}, but the keys will be ignored.'
+                            ' You need to call `lr_scheduler.step()` manually in manual optimization.',
+                            RuntimeWarning,
+                        )
+
+                    scheduler = {key: scheduler[key] for key in scheduler if key not in invalid_keys}
+                    lr_schedulers.append({**default_config, **scheduler})
+                else:
+                    lr_schedulers.append({**default_config, 'scheduler': scheduler})
+            elif isinstance(scheduler, dict):
                 # check provided keys
                 extra_keys = [k for k in scheduler.keys() if k not in default_config.keys()]
                 if extra_keys:
@@ -136,17 +152,6 @@ def configure_schedulers(
                         f'The "interval" key in lr scheduler dict must be "step" or "epoch"'
                         f' but is "{scheduler["interval"]}"'
                     )
-                if is_manual_optimization:
-                    invalid_keys = {'interval', 'frequency', 'reduce_on_plateau', 'monitor', 'strict'}
-                    keys_to_warn = [k for k in scheduler.keys() if k in invalid_keys]
-
-                    if keys_to_warn:
-                        rank_zero_warn(
-                            f'The lr scheduler dict contains the key(s) {keys_to_warn}, but the keys will be ignored.'
-                            ' You need to call `lr_scheduler.step()` manually in manual optimization.',
-                            RuntimeWarning,
-                        )
-
                 scheduler['reduce_on_plateau'] = isinstance(
                     scheduler['scheduler'], optim.lr_scheduler.ReduceLROnPlateau
                 )