[train_unconditional] fix applying clip_grad_norm_ (#721)

fix clip_grad_norm_

examples/unconditional_image_generation/train_unconditional.py

@@ -143,6 +143,7 @@ def main(args):
                 loss = F.mse_loss(noise_pred, noise)
                 accelerator.backward(loss)
 
+                if accelerator.sync_gradients:
                     accelerator.clip_grad_norm_(model.parameters(), 1.0)
                 optimizer.step()
                 lr_scheduler.step()