Fix comment

curvlinops/kfac.py

@@ -293,11 +293,12 @@ def _compute_loss_and_backward(self, output: Tensor, y: Tensor):
             if isinstance(self._loss_func, MSELoss):
                 flat_logits = output.flatten(start_dim=1)
                 out_dims = flat_logits.shape[1]
+                # Accounts for the reduction used in the loss function.
                 scale = 1.0 / out_dims if reduction == "mean" else 1.0
                 for i in range(out_dims):
                     # Mean or sum reduction over all loss terms.
                     # Multiply by sqrt(scale * 2.0) since the MSELoss does
-                    # not include the scale / 2.0 factor.
+                    # not include the 1 / 2 factor.
                     loss_i = sqrt(scale * 2.0) * reduction_fn(flat_logits[:, i])
                     loss_i.backward(retain_graph=i < out_dims - 1)
             elif isinstance(self._loss_func, CrossEntropyLoss):