test_mem_leak_guards_xpu - AssertionError: False is not true

### 🐛 Describe the bug

1 UT fails on Windows LNL with "AssertionError: False is not true"
Version | Status |
-- | -- |
pytorch_2.15_nightly_20260903 | Passed |
pytorch_2.15_nightly_20260907 | Failed |

### Affected Test Cases

```
..\..\..\..\test\dynamo\test_repros.py::ReproTestsDeviceXPU::test_mem_leak_guards_xpu
```

Error log

```
________________ ReproTestsDeviceXPU.test_mem_leak_guards_xpu _________________
[gw1] win32 -- Python 3.12.14 C:\Users\gta\miniforge3\envs\pytorch_2.15_nightly_20260907\python.exe
Traceback (most recent call last):
File "C:\Users\gta\repositories\pytorch\pytorch\test\dynamo\test_repros.py", line 8914, in test_mem_leak_guards
self.assertTrue(peak_mem1 == peak_mem2)
File "C:\Users\gta\miniforge3\envs\pytorch_2.15_nightly_20260907\Lib\unittest\case.py", line 727, in assertTrue
raise self.failureException(msg)
AssertionError: False is not true
```

### Versions

Click to expand traceback
PyTorch version: 2.15.0.dev20260907+xpu
Is debug build: False
CUDA used to build PyTorch: None
ROCm SDK used to build PyTorch: N/A
HIP 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, Sep 2 2026, 23:18:20) [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: 20260100
Intel GPU driver version:
* 32.0.101.8992 (20260831000000.******+***)
Intel GPU models onboard:
* Intel(R) Arc(TM) 140V GPU (16GB)
Intel GPU models detected:
* [0] _XpuDeviceProperties(name='Intel(R) Arc(TM) 140V GPU (16GB)', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero V2', type='gpu', device_id=0x64A0, uuid=8680a064-0400-0000-0002-000000000000, driver_version='1.15.39183+4', total_memory=16870MB, local_mem_size=128KB, last_level_cache_size=8192KB, max_compute_units=64, memory_clock_rate=0MHz, memory_bus_width=64-bit, gpu_eu_count=64, gpu_subslice_count=8, 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=1)
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: False
Caching allocator config: N/A

CPU:
Name: Intel(R) Core(TM) Ultra 7 258V
Manufacturer: GenuineIntel
Family: 774
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 2200
MaxClockSpeed: 2200
L2CacheSize: 14336
L2CacheSpeed: None
Revision: None

Versions of relevant libraries:
[pip3] dpcpp-cpp-rt==2026.1.0
[pip3] intel-cmplr-lib-rt==2026.1.0
[pip3] intel-cmplr-lib-ur==2026.1.0
[pip3] intel-cmplr-lic-rt==2026.1.0
[pip3] intel-opencl-rt==2026.1.0
[pip3] intel-openmp==2026.1.0
[pip3] intel-pti==1.0.1
[pip3] intel-sycl-rt==2026.1.0
[pip3] mkl==2026.1.0
[pip3] mkl-include==2024.2.0
[pip3] mkl-static==2024.2.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.26.4
[pip3] onemkl-license==2026.1.0
[pip3] onemkl-sycl-blas==2026.1.0
[pip3] onemkl-sycl-dft==2026.1.0
[pip3] onemkl-sycl-lapack==2026.1.0
[pip3] onemkl-sycl-rng==2026.1.0
[pip3] onemkl-sycl-sparse==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] tbb==2023.1.0
[pip3] tbb-devel==2021.13.1
[pip3] tcmlib==1.5.0
[pip3] torch==2.15.0.dev20260907+xpu
[pip3] torchaudio==2.11.0.dev20260907+xpu
[pip3] torchvision==0.30.0.dev20260907+xpu
[pip3] triton-xpu==3.8.0+git1e2d42a0
[pip3] umf==1.1.0
[conda] dpcpp-cpp-rt 2026.1.0 pypi_0 pypi
[conda] intel-cmplr-lib-rt 2026.1.0 pypi_0 pypi
[conda] intel-cmplr-lib-ur 2026.1.0 pypi_0 pypi
[conda] intel-cmplr-lic-rt 2026.1.0 pypi_0 pypi
[conda] intel-opencl-rt 2026.1.0 pypi_0 pypi
[conda] intel-openmp 2026.1.0 pypi_0 pypi
[conda] intel-pti 1.0.1 pypi_0 pypi
[conda] intel-sycl-rt 2026.1.0 pypi_0 pypi
[conda] mkl 2026.1.0 pypi_0 pypi
[conda] mkl-include 2024.2.0 pypi_0 pypi
[conda] mkl-static 2024.2.0 pypi_0 pypi
[conda] numpy 1.26.4 pypi_0 pypi
[conda] onemkl-license 2026.1.0 pypi_0 pypi
[conda] onemkl-sycl-blas 2026.1.0 pypi_0 pypi
[conda] onemkl-sycl-dft 2026.1.0 pypi_0 pypi
[conda] onemkl-sycl-lapack 2026.1.0 pypi_0 pypi
[conda] onemkl-sycl-rng 2026.1.0 pypi_0 pypi
[conda] onemkl-sycl-sparse 2026.1.0 pypi_0 pypi
[conda] optree 0.13.0 pypi_0 pypi
[conda] tbb 2023.1.0 pypi_0 pypi
[conda] tbb-devel 2021.13.1 pypi_0 pypi
[conda] tcmlib 1.5.0 pypi_0 pypi
[conda] torch 2.15.0.dev20260907+xpu pypi_0 pypi
[conda] torchaudio 2.11.0.dev20260907+xpu pypi_0 pypi
[conda] torchvision 0.30.0.dev20260907+xpu pypi_0 pypi
[conda] triton-xpu 3.8.0+git1e2d42a0 pypi_0 pypi
[conda] umf 1.1.0 pypi_0 pypi

Start with test/dynamo/test_repros.py around line 8914 and run ReproTestsDeviceXPU.test_mem_leak_guards_xpu on the reported Windows LNL XPU environment. Compare the passing and failing nightly versions and inspect how peak_mem1 and peak_mem2 are obtained; done means the test reliably passes while retaining its memory-leak guard.

Written by the indexing model from the issue text.