test_fx_xpu.py::TestFX::test_profiler_stack_trace_augmentation AssertionError

### 🐛 Describe the bug

There is `test_fx_xpu.py::TestFX::test_profiler_stack_trace_augmentation` AssertionError on BMG B580 Windows. Test passed PyTorch fddcbe3 (Jul 28) and torch-xpu-ops https://github.com/intel/torch-xpu-ops/commit/298168d88308a8039c654f9a64b10782e30c4384 (Jul 24).

Error:
```
________________ TestFX.test_profiler_stack_trace_augmentation ________________
[gw0] win32 -- Python 3.12.14 C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\python.exe
Traceback (most recent call last):
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\unittest\case.py", line 58, in testPartExecutor
yield
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\unittest\case.py", line 634, in run
self._callTestMethod(testMethod)
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\unittest\case.py", line 589, in _callTestMethod
if method() is not None:
^^^^^^^^
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\site-packages\torch\testing\_internal\common_utils.py", line 3886, in wrapper
method(*args, **kwargs)
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\contextlib.py", line 81, in inner
return func(*args, **kwds)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\gta\repositories\pytorch\pytorch\third_party\torch-xpu-ops\test\xpu\test_fx_xpu.py", line 280, in _test_profiler_stack_trace_augmentation
self.assertExpectedInline(actual_traces, expected)
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\site-packages\torch\testing\_internal\common_utils.py", line 3829, in assertExpectedInline
return super().assertExpectedInline(actual if isinstance(actual, str) else str(actual), expect, skip + 1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\site-packages\expecttest\__init__.py", line 413, in assertExpectedInline
assert_expected_inline(
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\site-packages\expecttest\__init__.py", line 378, in assert_expected_inline
assert_eq(expect, actual, msg=help_text)
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\site-packages\expecttest\__init__.py", line 450, in assertMultiLineEqualMaybeCppStack
self.assertMultiLineEqual(expect, actual, *args, **kwargs)
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\unittest\case.py", line 1251, in assertMultiLineEqual
self.fail(self._formatMessage(msg, standardMsg))
File "C:\Users\gta\miniforge3\envs\202608272250_fbcf2af8_32.0.101.8991_2026.1.3.20\Lib\unittest\case.py", line 715, in fail
raise self.failureException(msg)
AssertionError: 'even[809 chars]vent=aten::relu node=relu stack_trace=return F[1042 chars]ias)' != 'even[809 chars]vent=Instrumentation node=addmm stack_trace=re[2791 chars]ias)'
event=aten::t node=t stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::transpose node=t stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::as_strided node=t stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::addmm node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::resize_ node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::expand node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::as_strided node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::empty node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=urEnqueueKernelLaunch node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::relu node=relu stack_trace=return F.relu(input, inplace=self.inplace)
event=aten::clamp_min node=relu stack_trace=return F.relu(input, inplace=self.inplace)
event=urEnqueueKernelLaunch node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
+ event=Instrumentation node=relu stack_trace=return F.relu(input, inplace=self.inplace)
event=aten::t node=t_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::transpose node=t_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::as_strided node=t_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::addmm node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::resize_ node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::expand node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::as_strided node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=aten::empty node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
event=urEnqueueKernelLaunch node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
+ event=Instrumentation node=addmm_1 stack_trace=return F.linear(input, self.weight, self.bias)
: To accept the new output, re-run test with envvar EXPECTTEST_ACCEPT=1 (we recommend staging/committing your changes before doing this)

```

### Versions

Click to expand
PyTorch version: 2.15.0a0+gitfbcf2af
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Microsoft Windows 11 Pro (10.0.26200 64-bit)
GCC version: Could not collect
Clang version: Could not collect
CMake version: version 3.31.6
Libc version: N/A

Python version: 3.12.14 | packaged by conda-forge | (main, Aug 21 2026, 22:37:19) [MSC v.1944 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-11-10.0.26200-SP0
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
Is XPU available: True
XPU used to build PyTorch: 20260101
Intel GPU driver version:
* 32.0.101.8991 (20260824000000.******+***)
Intel GPU models onboard:
* Intel(R) Arc(TM) B580 Graphics
Intel GPU models detected:
* [0] _XpuDeviceProperties(name='Intel(R) Arc(TM) B580 Graphics', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero V2', type='gpu', device_id=0xE20B, uuid=86800be2-0000-0000-0300-000000000000, driver_version='1.15.39183+3', total_memory=11875MB, local_mem_size=128KB, last_level_cache_size=18432KB, max_compute_units=160, memory_clock_rate=0MHz, memory_bus_width=64-bit, gpu_eu_count=160, gpu_subslice_count=20, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1, is_integrated_gpu=0)
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: False
Caching allocator config: N/A

CPU:
Name: 13th Gen Intel(R) Core(TM) i5-13400
Manufacturer: GenuineIntel
Family: 205
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 2500
MaxClockSpeed: 2500
L2CacheSize: 9728
L2CacheSpeed: None
Revision: None

Versions of relevant libraries:
[pip3] bert_pytorch==0.0.1a4
[pip3] functorch==1.14.0a0+b71aa0b
[pip3] intel-openmp==2026.1.1
[pip3] mkl-include==2026.1.0
[pip3] mkl-static==2026.1.0
[pip3] mypy==2.3.1
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.26.4
[pip3] onemkl-license==2026.1.0
[pip3] onnx==1.21.0
[pip3] onnx-ir==0.1.16
[pip3] onnxscript==0.6.2
[pip3] optree==0.13.0
[pip3] pytorch-labs-segment-anything-fast==0.2
[pip3] tbb==2023.1.0
[pip3] tbb-devel==2023.1.0
[pip3] tcmlib==1.5.0
[pip3] torch==2.15.0a0+gitfbcf2af
[pip3] torch_geometric==2.4.0
[pip3] torchao==0.18.0
[pip3] torchaudio==2.11.0a0+4e3e282
[pip3] torchbench==0.1
[pip3] torchmetrics==1.9.0
[pip3] torchmultimodal==0.1.0b0
[pip3] torchrec-nightly==2022.4.26
[pip3] torchvision==0.30.0a0+541c083
[pip3] torchx-nightly==2026.8.27
[pip3] triton-xpu==3.8.0+git1e2d42a0
[conda] bert-pytorch 0.0.1a4 dev_0
[conda] functorch 1.14.0a0+b71aa0b pypi_0 pypi
[conda] intel-openmp 2026.1.1 pypi_0 pypi
[conda] mkl-include 2026.1.0 pypi_0 pypi
[conda] mkl-static 2026.1.0 pypi_0 pypi
[conda] numpy 1.26.4 pypi_0 pypi
[conda] onemkl-license 2026.1.0 pypi_0 pypi
[conda] optree 0.13.0 pypi_0 pypi
[conda] pytorch-labs-segment-anything-fast 0.2 pypi_0 pypi
[conda] tbb 2023.1.0 pypi_0 pypi
[conda] tbb-devel 2023.1.0 pypi_0 pypi
[conda] tcmlib 1.5.0 pypi_0 pypi
[conda] torch 2.15.0a0+gitfbcf2af pypi_0 pypi
[conda] torch-geometric 2.4.0 pypi_0 pypi
[conda] torchao 0.18.0 pypi_0 pypi
[conda] torchaudio 2.11.0a0+4e3e282 pypi_0 pypi
[conda] torchbench 0.1 pypi_0 pypi
[conda] torchmetrics 1.9.0 pypi_0 pypi
[conda] torchmultimodal 0.1.0b0 pypi_0 pypi
[conda] torchrec-nightly 2022.4.26 pypi_0 pypi
[conda] torchvision 0.30.0a0+541c083 pypi_0 pypi
[conda] torchx-nightly 2026.8.27 pypi_0 pypi
[conda] triton-xpu 3.8.0+git1e2d42a0 pypi_0 pypi

Start with third_party/torch-xpu-ops/test/xpu/test_fx_xpu.py at line 280 and run TestFX.test_profiler_stack_trace_augmentation on the reported Windows XPU setup. Compare the actual and expected profiler traces, then identify the cause of the added Instrumentation events; done means the test reflects correct behavior and passes without unexpectedly changing other trace entries.

Written by the indexing model from the issue text.