Improve callback documentation for `outputs` and `accumulate_grad_batches` (Resolves #15315) (#15327)

Co-authored-by: Rohit Gupta <rohitgr1998@gmail.com>
Co-authored-by: awaelchli <aedu.waelchli@gmail.com>

src/pytorch_lightning/callbacks/callback.py

@@ -82,7 +82,12 @@ class Callback:
     def on_train_batch_end(
         self, trainer: "pl.Trainer", pl_module: "pl.LightningModule", outputs: STEP_OUTPUT, batch: Any, batch_idx: int
     ) -> None:
-        """Called when the train batch ends."""
+        """Called when the train batch ends.
+
+        Note:
+            The value ``outputs["loss"]`` here will be the normalized value w.r.t ``accumulate_grad_batches`` of the
+            loss returned from ``training_step``.
+        """
 
     def on_train_epoch_start(self, trainer: "pl.Trainer", pl_module: "pl.LightningModule") -> None:
         """Called when the train epoch begins."""

src/pytorch_lightning/core/module.py

@@ -661,6 +661,10 @@ class LightningModule(
         Note:
             The loss value shown in the progress bar is smoothed (averaged) over the last values,
             so it differs from the actual loss returned in train/validation step.
+
+        Note:
+            When ``accumulate_grad_batches`` > 1, the loss returned here will be automatically
+            normalized by ``accumulate_grad_batches`` internally.
         """
         rank_zero_warn("`training_step` must be implemented to be used with the Lightning Trainer")