formatting

Author: loadams

deepspeed/runtime/zero/stage_1_and_2.py

@@ -1691,7 +1691,8 @@ def get_grad_norm_direct(self, gradients, params, norm_type=2):
                     continue
                 if is_model_parallel_parameter(p) or (self.model_parallel_rank == 0):
                     all_norms.append(
-                        torch.linalg.norm(g.data.double().detach(), ord=norm_type).to(get_accelerator().current_device_name()))
+                        torch.linalg.norm(g.data.double().detach(),
+                                          ord=norm_type).to(get_accelerator().current_device_name()))
             if len(all_norms) > 0:
                 total_norm = torch.stack(all_norms).square().sum().float()
             else: