diff --git a/transformer_engine/pytorch/fp8.py b/transformer_engine/pytorch/fp8.py
index f54cda6429..bb799ef8e5 100644
--- a/transformer_engine/pytorch/fp8.py
+++ b/transformer_engine/pytorch/fp8.py
@@ -485,9 +485,9 @@ def restore_fp8_meta_tensors(fp8_meta: Dict[str, Any]) -> None:
 
 @contextmanager
 def fp8_model_init(
-        enabled: bool = True,
-        preserve_high_precision_init_val: bool = False,
-    ) -> None:
+    enabled: bool = True,
+    preserve_high_precision_init_val: bool = False,
+) -> None:
     """
     Context manager for FP8 initialization of parameters.
 
diff --git a/transformer_engine/pytorch/module/base.py b/transformer_engine/pytorch/module/base.py
index ceb4a286e4..3aebc1729b 100644
--- a/transformer_engine/pytorch/module/base.py
+++ b/transformer_engine/pytorch/module/base.py
@@ -883,6 +883,7 @@ def reset_parameters(self, defer_init: Optional[bool] = False) -> None:
             #       a parameter so we always re-apply it just for extra safety.
             param = torch.nn.Parameter(param)
             if high_precision_init_val is not None:
+
                 def get(self):
                     if hasattr(self, "_high_precision_init_val"):
                         return self._high_precision_init_val