diff --git a/pytorch_lightning/loops/epoch/training_epoch_loop.py b/pytorch_lightning/loops/epoch/training_epoch_loop.py
index 340c1711b40f7..dbe163aa33cae 100644
--- a/pytorch_lightning/loops/epoch/training_epoch_loop.py
+++ b/pytorch_lightning/loops/epoch/training_epoch_loop.py
@@ -476,7 +476,7 @@ def _update_learning_rates(
             if update_plateau_schedulers ^ lr_scheduler["reduce_on_plateau"]:
                 continue
 
-            current_idx = self.trainer.fit_loop.batch_idx if interval == "step" else self.trainer.current_epoch
+            current_idx = self.batch_idx if interval == "step" else self.trainer.current_epoch
             current_idx += 1  # account for both batch and epoch starts from 0
             # Take step if call to update_learning_rates matches the interval key and
             # the current step modulo the schedulers frequency is zero
@@ -502,7 +502,7 @@ def _update_learning_rates(
                         )
                         continue
 
-                self.trainer.fit_loop.epoch_loop.scheduler_progress.increment_ready()
+                self.scheduler_progress.increment_ready()
 
                 # update LR
                 if lr_scheduler["reduce_on_plateau"]:
@@ -510,7 +510,7 @@ def _update_learning_rates(
                 else:
                     lr_scheduler["scheduler"].step()
 
-                self.trainer.fit_loop.epoch_loop.scheduler_progress.increment_completed()
+                self.scheduler_progress.increment_completed()
 
     def _get_monitor_value(self, key: str) -> Any:
         # this is a separate method to aid in testing