[examples] update loss computation (#1861)

update loss computation

examples/dreambooth/train_dreambooth.py

@@ -732,7 +732,7 @@ def main(args):
                     target, target_prior = torch.chunk(target, 2, dim=0)
 
                     # Compute instance loss
-                    loss = F.mse_loss(model_pred.float(), target.float(), reduction="none").mean([1, 2, 3]).mean()
+                    loss = F.mse_loss(model_pred.float(), target.float(), reduction="mean")
 
                     # Compute prior loss
                     prior_loss = F.mse_loss(model_pred_prior.float(), target_prior.float(), reduction="mean")

examples/textual_inversion/textual_inversion.py

@@ -634,7 +634,8 @@ def main():
                 else:
                     raise ValueError(f"Unknown prediction type {noise_scheduler.config.prediction_type}")
 
-                loss = F.mse_loss(model_pred.float(), target.float(), reduction="none").mean([1, 2, 3]).mean()
+                loss = F.mse_loss(model_pred.float(), target.float(), reduction="mean")
+
                 accelerator.backward(loss)
 
                 optimizer.step()