Fix lint error

Author: libohao1201

test/xpu/test_decomp.py

@@ -19,7 +19,6 @@
 from torch.testing._internal.common_device_type import (
     instantiate_device_type_tests,
     onlyCPU,
-    onlyCUDA,
     onlyNativeDeviceTypes,
     ops,
 )
@@ -45,19 +44,9 @@
 from torch.utils._python_dispatch import TorchDispatchMode
 from torch.utils._pytree import tree_flatten, tree_map, tree_unflatten
 
-
 device_type = (
     acc.type if (acc := torch.accelerator.current_accelerator(True)) else "cpu"
 )
-# # XPU 支持导入
-# try:
-#     from xpu_test_utils import XPUPatchForImport
-# except Exception as e:
-#     from .xpu_test_utils import XPUPatchForImport
-
-# with XPUPatchForImport(False):
-#     from test_decomp import DecompOneOffTests, TestDecomp
-
 
 aten = torch.ops.aten
 
@@ -194,7 +183,7 @@ def _getDefaultRtolAndAtol(dtype0, dtype1):
     return rtol, atol
 
 
-# 修改后的 op_assert_ref 函数，包含 XPU 特定的容差配置
+
 def op_assert_ref(test_case, op, test_dtype, i, orig, decomp, ref, args, kwargs):
     assert orig.dtype == decomp.dtype, f"{i} Operation:  {op}"
     if orig.numel() == 0 or decomp.numel() == 0:
@@ -240,7 +229,7 @@ def op_assert_ref(test_case, op, test_dtype, i, orig, decomp, ref, args, kwargs)
         (torch.bfloat16, torch.ops.aten.mv.default): 1e-5,
         (torch.float16, torch.ops.aten.log_sigmoid_backward.default): 2e-5,
         (torch.float16, torch.ops.aten._softmax_backward_data.default): 3e-7,
-        # XPU specific 
+        # XPU specific
         (
             torch.float16,
             torch.ops.aten._batch_norm_with_update.default,
@@ -781,7 +770,6 @@ def forward(self, x_1, start_1):
     def test_masked_fill(self, device):
         from torch.fx.experimental.proxy_tensor import make_fx
 
-        # 修改设备检查以包含 XPU
         if torch.device(device).type not in [
             "xpu",
             "cuda",
@@ -1068,7 +1056,6 @@ def run_without_python_dispatcher(mode):
                 )
 
 
-# 修改测试实例化以支持 XPU
 instantiate_device_type_tests(TestDecomp, globals(), only_for="xpu", allow_xpu=True)
 
 
@@ -1101,7 +1088,6 @@ def test_contiguous_log_softmax(self, device):
         res = torch._decomp.decompositions._log_softmax(x, -1, False)
         self.assertEqual(ref.stride(), res.stride())
 
-    # @onlyCUDA
     def test_exponential_non_inf(self, device):
         inp = torch.empty((4, 400, 256), device=device)
 
@@ -1114,7 +1100,6 @@ def test_exponential_non_inf(self, device):
 
     @unittest.skipIf(TEST_WITH_ASAN, "Skipped under ASAN")
     @skipIfCrossRef
-    # @onlyCUDA
     def test_amp_batch_norm_backward(self):
         device = device_type
         grad_out = torch.randn((1, 2, 16, 16), dtype=torch.float16, device=device)
@@ -1265,7 +1250,6 @@ def f(x, w, b):
         for o_ref, o in zip(out_ref, out):
             self.assertEqual(o_ref.dtype, o.dtype)
 
-    # @onlyCUDA
     @unittest.skipIf(not SM70OrLater, "triton")
     def test_rms_norm_decomp_accelerator(self, device):
         @torch.compile
@@ -1293,8 +1277,9 @@ def forward_pass_fn():
         )
 
 
-# 修改测试实例化以支持 XPU
-instantiate_device_type_tests(DecompOneOffTests, globals(), only_for="xpu", allow_xpu=True)
+instantiate_device_type_tests(
+    DecompOneOffTests, globals(), only_for="xpu", allow_xpu=True
+)
 
 
 class HasDecompTest(TestCase):
@@ -1376,4 +1361,4 @@ def test_aten_core_operators(self):
 
 
 if __name__ == "__main__":
-    run_tests()
+    run_tests()