[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

tests/pytorch/test_cuda_graphs.py

@@ -141,6 +141,7 @@ def forward(self, input_: torch.Tensor, **kwargs) -> torch.Tensor:
     "linear_op",
 ]
 
+
 def _test_cuda_graphs(
     *,
     graph_mode: str,
@@ -331,6 +332,7 @@ def test_make_graphed_callables(
     "mha",
 ]
 
+
 @pytest.mark.skipif(not fp8_available, reason=reason_for_no_fp8)
 @pytest.mark.parametrize(
     "module",
@@ -478,7 +480,12 @@ def _test_cuda_graphs_with_kwargs(
             grad_output = generate_data(model_config, dtype, requires_grad=False)
             attn_mask = torch.randint(
                 2,
-                (model_config.batch_size, 1, model_config.sequence_length, model_config.sequence_length),
+                (
+                    model_config.batch_size,
+                    1,
+                    model_config.sequence_length,
+                    model_config.sequence_length,
+                ),
                 dtype=torch.bool,
                 device="cuda",
             )

transformer_engine/pytorch/graph.py

@@ -492,6 +492,7 @@ def save_fp8_tensors(
     with adjusted amax history sizes.
     """
     from .ops import Sequential, FusibleOperation  # Avoid circular import
+
     fp8_tensors = []
     for module in modules:
         for m in module.modules():
@@ -521,6 +522,7 @@ def restore_fp8_tensors(
 ) -> None:
     """Restore FP8 tensors."""
     from .ops import Sequential, FusibleOperation  # Avoid circular import
+
     for module in modules:
         for m in module.modules():
             module_tensors = fp8_tensors.pop(0)

transformer_engine/pytorch/ops/op.py

@@ -286,9 +286,9 @@ def _maybe_update_fp8_meta(
                     FP8GlobalStateManager.global_amax_buffer[buffer_key][pos] = fp8_meta[
                         fp8_meta_key
                     ].amax_history[0]
-                    FP8GlobalStateManager.global_amax_history_buffer[buffer_key][pos] = (
-                        fp8_meta[fp8_meta_key].amax_history
-                    )
+                    FP8GlobalStateManager.global_amax_history_buffer[buffer_key][pos] = fp8_meta[
+                        fp8_meta_key
+                    ].amax_history
 
     def get_fp8_meta(self, mode: str) -> Optional[dict[str, Any]]:
         """FP8 metadata
@@ -335,16 +335,19 @@ def _load_fp8_metas(self, fp8_metas: Optional[dict[str, Any]]) -> None:
         Tensor copies should be generated with _save_fp8_metas.
 
         """
-        assert (self._fp8_metas is None) == (fp8_metas is None), \
-            "Saved FP8 metadata does not match operation's FP8 metadata"
+        assert (self._fp8_metas is None) == (
+            fp8_metas is None
+        ), "Saved FP8 metadata does not match operation's FP8 metadata"
         if fp8_metas is None:
             return
         for mode, fp8_meta in fp8_metas.items():
-            assert mode in self._fp8_metas, \
-                f"Found an unexpected key ({mode=}) in saved FP8 metadata"
+            assert (
+                mode in self._fp8_metas
+            ), f"Found an unexpected key ({mode=}) in saved FP8 metadata"
             for fp8_meta_key, tensors in fp8_meta.items():
-                assert fp8_meta_key in self._fp8_metas[mode], \
-                    f"Found an unexpected key ({mode=}, {fp8_meta_key=}) in saved FP8 metadata"
+                assert (
+                    fp8_meta_key in self._fp8_metas[mode]
+                ), f"Found an unexpected key ({mode=}, {fp8_meta_key=}) in saved FP8 metadata"
                 scale, scale_inv, amax_history = tensors
                 self._fp8_metas[mode][fp8_meta_key].scale.copy_(scale)
                 self._fp8_metas[mode][fp8_meta_key].scale_inv.copy_(scale_inv)