test_meta_xpu.py::TestMetaXPU::test_dispatch_symbolic_meta_outplace_all_strides_native_group_norm_xpu_float32 - Failed: Unexpected success

### 🐛 Describe the bug

1 UTs passes insted of exected fail on Windows with Intel XPU (Arc B580)

pytorch commit hash | pytorch commit date | torch-xpu commit hash | torch-xpu commit date | status
-- | -- | -- | -- | --
2a8ba15 | Jul 22 | 68ac53ad | Jul 23| xfail
fddcbe3 | Jul 28 | 298168d8 | JUL 24 | passed

## Affected Test Cases

```
test_dispatch_symbolic_meta_outplace_all_strides_native_group_norm_xpu_float32
```

### Error Message

Click to expand traceback

```
_ TestMetaXPU.test_dispatch_symbolic_meta_outplace_all_strides_native_group_norm_xpu_float32 _
[gw1] win32 -- Python 3.12.13 C:\Users\gta\miniforge3\envs\202607280406_fddcbe34_32.0.101.8864_2026.1.2.44\python.exe
Unexpected success
```

### Versions

Click to expand traceback

PyTorch version: 2.14.0a0+gitfddcbe3 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: 3.12.13 | packaged by conda-forge | (main, Mar 5 2026, 16:36:12) [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:

32.0.101.8864 (20260717000000.***+)
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='1.15.38308', 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) i9-13900
Manufacturer: GenuineIntel
Family: 207
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 2000
MaxClockSpeed: 2000
L2CacheSize: 32768
L2CacheSpeed: None
Revision: None

Versions of relevant libraries:
[pip3] bert_pytorch==0.0.1a4
[pip3] functorch==1.14.0a0+b71aa0b
[pip3] intel-openmp==2026.1.0
[pip3] mkl-include==2026.1.0
[pip3] mkl-static==2026.1.0
[pip3] mypy==2.3.0
[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==2.14.0a0+gitfddcbe3
[pip3] torch_geometric==2.4.0
[pip3] torchao==0.17.0
[pip3] torchaudio==2.11.0a0+c0cbdb9
[pip3] torchbench==0.1
[pip3] torchmetrics==1.9.0
[pip3] torchmultimodal==0.1.0b0
[pip3] torchrec-nightly==2022.4.26
[pip3] torchvision==0.29.0a0+3f87802
[pip3] torchx-nightly==2026.7.28
[pip3] triton-xpu==3.7.2+git5fcc14d9
[conda] bert-pytorch 0.0.1a4 dev_0
[conda] functorch 1.14.0a0+b71aa0b pypi_0 pypi
[conda] intel-openmp 2026.1.0 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 2.14.0a0+gitfddcbe3 pypi_0 pypi
[conda] torch-geometric 2.4.0 pypi_0 pypi
[conda] torchao 0.17.0 pypi_0 pypi
[conda] torchaudio 2.11.0a0+c0cbdb9 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 0.29.0a0+3f87802 pypi_0 pypi
[conda] torchx-nightly 2026.7.28 pypi_0 pypi
[conda] triton-xpu 3.7.2+git5fcc14d9 pypi_0 pypi

Start by locating and running test_meta_xpu.py::TestMetaXPU::test_dispatch_symbolic_meta_outplace_all_strides_native_group_norm_xpu_float32 on Windows with Intel XPU, using the environment and versions reported here. Trace why the xfail is now an unexpected success, then make the test's expected status match the supported behavior and verify the focused test passes.

Written by the indexing model from the issue text.