Clarify return type in training_step docs in case of manual optimization (#19327)

Co-authored-by: Julien Hauret <53187038+jhauret@users.noreply.github.com>
Co-authored-by: Jirka Borovec <6035284+Borda@users.noreply.github.com>

Author: 3 people

src/lightning/pytorch/core/module.py

@@ -689,9 +689,11 @@ def training_step(self, *args: Any, **kwargs: Any) -> STEP_OUTPUT:
 
         Return:
             - :class:`~torch.Tensor` - The loss tensor
-            - ``dict`` - A dictionary. Can include any keys, but must include the key ``'loss'``.
-            - ``None`` - Skip to the next batch. This is only supported for automatic optimization.
-                This is not supported for multi-GPU, TPU, IPU, or DeepSpeed.
+            - ``dict`` - A dictionary which can include any keys, but must include the key ``'loss'`` in the case of
+              automatic optimization.
+            - ``None`` - In automatic optimization, this will skip to the next batch (but is not supported for
+              multi-GPU, TPU, or DeepSpeed). For manual optimization, this has no special meaning, as returning
+              the loss is not required.
 
         In this step you'd normally do the forward pass and calculate the loss for a batch.
         You can also do fancier things like multiple forward passes or something model specific.