From 5fcfced23f3b460f04ba533d9e13a4b220d74a96 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Sat, 30 Nov 2024 07:02:49 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 thunder/tests/test_tensor_subclass.py   |  6 +++--
 thunder/transforms/tensor_subclasses.py | 33 ++++++++++++++-----------
 2 files changed, 23 insertions(+), 16 deletions(-)

diff --git a/thunder/tests/test_tensor_subclass.py b/thunder/tests/test_tensor_subclass.py
index 85618ba3e..e63630a30 100644
--- a/thunder/tests/test_tensor_subclass.py
+++ b/thunder/tests/test_tensor_subclass.py
@@ -253,7 +253,7 @@ def g(x: ScaleTensorSubclass, data: torch.Tensor, scale: torch.Tensor) -> torch.
             not (TORCHAO_AVAILABLE and torch.cuda.get_device_capability() >= (8, 9)),
             reason="Requires capability >= 8.9 and torchao",
         ),
-        pytest.mark.parametrize("bias", (True, False))
+        pytest.mark.parametrize("bias", (True, False)),
     ),
 )
 def test_torchao_float8_linear(executor, device, dtype, bias):
@@ -294,7 +294,9 @@ def test_torchao_float8_linear(executor, device, dtype, bias):
             torch.testing.assert_close(actual, expected)
         return
 
-    if (dtype == thunder.core.dtypes.bfloat16 and executor != DynamoThunderExecutor) or (not bias and dtype == thunder.core.dtypes.bfloat16 and executor == DynamoThunderExecutor):
+    if (dtype == thunder.core.dtypes.bfloat16 and executor != DynamoThunderExecutor) or (
+        not bias and dtype == thunder.core.dtypes.bfloat16 and executor == DynamoThunderExecutor
+    ):
         pytest.xfail("numerical error")
     torch.testing.assert_close(actual, expected)
 
diff --git a/thunder/transforms/tensor_subclasses.py b/thunder/transforms/tensor_subclasses.py
index 5eb2e2411..677dbc60e 100644
--- a/thunder/transforms/tensor_subclasses.py
+++ b/thunder/transforms/tensor_subclasses.py
@@ -254,23 +254,26 @@ def __post_init__(self) -> None:
         if len(self.computation_trace.bound_symbols) > 6:
             maybe_unpack_C0_bsym = self.computation_trace.bound_symbols[4]
             maybe_unpack_C1_bsym = self.computation_trace.bound_symbols[5]
-            is_backward_trace = maybe_unpack_C0_bsym.args and maybe_unpack_C1_bsym.args and (
-                maybe_unpack_C0_bsym.sym.id,
-                maybe_unpack_C1_bsym.sym.id,
-                getattr(maybe_unpack_C0_bsym.args[0], "name", ""),
-                getattr(maybe_unpack_C1_bsym.args[0], "name", ""),
-            ) == (
-                prims.PrimIDs.UNPACK_SEQUENCE,
-                prims.PrimIDs.UNPACK_SEQUENCE,
-                "C0",
-                "C1",
+            is_backward_trace = (
+                maybe_unpack_C0_bsym.args
+                and maybe_unpack_C1_bsym.args
+                and (
+                    maybe_unpack_C0_bsym.sym.id,
+                    maybe_unpack_C1_bsym.sym.id,
+                    getattr(maybe_unpack_C0_bsym.args[0], "name", ""),
+                    getattr(maybe_unpack_C1_bsym.args[0], "name", ""),
+                )
+                == (
+                    prims.PrimIDs.UNPACK_SEQUENCE,
+                    prims.PrimIDs.UNPACK_SEQUENCE,
+                    "C0",
+                    "C1",
+                )
             )
             if is_backward_trace:
                 self.flat_trace_args, _ = tree_flatten((maybe_unpack_C0_bsym.output, maybe_unpack_C1_bsym.output))
         if not is_backward_trace:
-            self.flat_trace_args, _ = tree_flatten(
-                (self.computation_trace.args, self.computation_trace.kwargs)
-            )
+            self.flat_trace_args, _ = tree_flatten((self.computation_trace.args, self.computation_trace.kwargs))
         for arg in self.flat_trace_args:
             if isinstance(arg, SubclassTensorProxy):
                 self.subclass_proxy_to_flatten.add(variableify(arg))
@@ -679,6 +682,8 @@ def flatten_tensor_subclasses(trace: TraceCtx) -> TraceCtx:
 
     computation_trace_with_subclass_tensor_proxy_output = from_trace(trace)
     computation_trace_with_subclass_tensor_proxy_output.bound_symbols.extend(updated_bsyms)
-    computation_trace_with_subclass_tensor_proxy_output.set_provenance(TraceProvenance(f"tensor subclasses desugared (took {elapsed_time_millis} milliseconds)"))
+    computation_trace_with_subclass_tensor_proxy_output.set_provenance(
+        TraceProvenance(f"tensor subclasses desugared (took {elapsed_time_millis} milliseconds)")
+    )
     warn_tensor_subclass_support()
     return computation_trace_with_subclass_tensor_proxy_output