[upstream] New failing test case `TestMultiGPUDeviceXPU::test_caching_pinned_memory_multi_gpu`

### 🐛 Describe the bug

During upstream tests generalization a new failing test case has been discovered. It needs further investigation.

Test case:
`test_cuda_multigpu.py::TestMultiGPUDeviceXPU::test_caching_pinned_memory_multi_gpu`

Error log

```text
________ TestMultiGPUDeviceXPU.test_caching_pinned_memory_multi_gpu_xpu ________
Traceback (most recent call last):
File "/usr/lib/python3.12/unittest/case.py", line 58, in testPartExecutor
yield
File "/usr/lib/python3.12/unittest/case.py", line 634, in run
self._callTestMethod(testMethod)
File "/usr/lib/python3.12/unittest/case.py", line 589, in _callTestMethod
if method() is not None:
^^^^^^^^
File "/home/kdrozd/dev-reproducer/pytorch/.venv/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py", line 3905, in wrapper
method(*args, **kwargs)
File "/home/kdrozd/dev-reproducer/pytorch/.venv/lib/python3.12/site-packages/torch/testing/_internal/common_device_type.py", line 672, in instantiated_test
result = test(self, **param_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kdrozd/dev-reproducer/pytorch/.venv/lib/python3.12/site-packages/torch/testing/_internal/common_device_type.py", line 1965, in multi_fn
return fn(slf, devices, *args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/kdrozd/dev-reproducer/pytorch/test/test_cuda_multigpu.py", line 689, in test_caching_pinned_memory_multi_gpu
self.assertNotEqual(t.data_ptr(), ptr, msg="allocation reused too soon")
File "/home/kdrozd/dev-reproducer/pytorch/.venv/lib/python3.12/site-packages/torch/testing/_internal/common_utils.py", line 4964, in assertNotEqual
with self.assertRaises(AssertionError, msg=msg):
File "/usr/lib/python3.12/unittest/case.py", line 263, in __exit__
self._raiseFailure("{} not raised".format(exc_name))
File "/usr/lib/python3.12/unittest/case.py", line 200, in _raiseFailure
raise self.test_case.failureException(msg)
AssertionError: AssertionError not raised : allocation reused too soon

To execute this test, run the following from the base repo dir:
python test/test_cuda_multigpu.py TestMultiGPUDeviceXPU.test_caching_pinned_memory_multi_gpu_xpu

This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
```

### Versions

Versions

```text
Collecting environment information...
PyTorch version: 2.15.0.dev20260915+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: Ubuntu 24.04.4 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04.1) 13.3.0
Clang version: 18.1.3 (1ubuntu1)
CMake version: version 3.28.3
Libc version: glibc-2.39

Python version: 3.12.3 (main, Jul 15 2026, 23:46:41) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-7.0.0-30-generic-x86_64-with-glibc2.39
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:
* libze1: 1.32.0-1~24.04~ppa1
* intel-opencl-icd: 26.27.39122.14-1~24.04~ppa1
Intel GPU models onboard:
* Intel(R) Arc(TM) Pro B70 Graphics
* Intel(R) Arc(TM) Pro B70 Graphics
Intel GPU models detected:
* [0] _XpuDeviceProperties(name='Intel(R) Arc(TM) Pro B70 Graphics', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero V2', type='gpu', device_id=0xE223, uuid=868023e2-0000-0000-6200-000000000000, driver_version='1.15.39122+14', total_memory=32656MB, local_mem_size=128KB, last_level_cache_size=24576KB, max_compute_units=256, memory_clock_rate=2800MHz, memory_bus_width=64-bit, gpu_eu_count=256, gpu_subslice_count=32, 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)
* [1] _XpuDeviceProperties(name='Intel(R) Arc(TM) Pro B70 Graphics', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero V2', type='gpu', device_id=0xE223, uuid=868023e2-0000-0000-b000-000000000000, driver_version='1.15.39122+14', total_memory=32656MB, local_mem_size=128KB, last_level_cache_size=24576KB, max_compute_units=256, memory_clock_rate=2800MHz, memory_bus_width=64-bit, gpu_eu_count=256, gpu_subslice_count=32, 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:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 52 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 128
On-line CPU(s) list: 0-127
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) 696X
CPU family: 6
Model: 173
Thread(s) per core: 2
Core(s) per socket: 64
Socket(s): 1
Stepping: 1
CPU(s) scaling MHz: 18%
CPU max MHz: 4800.0000
CPU min MHz: 800.0000
BogoMIPS: 4800.00
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cat_l2 cdp_l3 intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local split_lock_detect user_shstk avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr ibt amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 3 MiB (64 instances)
L1i cache: 4 MiB (64 instances)
L2 cache: 128 MiB (64 instances)
L3 cache: 336 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-127
Vulnerability Gather data sampling: Not affected
Vulnerability Ghostwrite: Not affected
Vulnerability Indirect target selection: Not affected
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Not affected
Vulnerability Old microcode: Not affected
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec rstack overflow: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; PBRSB-eIBRS Not affected; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsa: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

Versions of relevant libraries:
[pip3] dpcpp-cpp-rt==2026.1.0
[pip3] impi-rt==2021.18.1
[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] numpy==2.5.3
[pip3] oneccl==2022.1.1
[pip3] oneccl-devel==2022.1.1
[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] tbb==2023.1.0
[pip3] tcmlib==1.5.0
[pip3] torch==2.15.0.dev20260915+xpu
[pip3] torchaudio==2.11.0.dev20260915+xpu
[pip3] torchvision==0.30.0.dev20260915+xpu
[pip3] triton-xpu==3.8.0+git1e2d42a0
[pip3] umf==1.1.0
[conda] Could not collect
```

Run `python test/test_cuda_multigpu.py TestMultiGPUDeviceXPU.test_caching_pinned_memory_multi_gpu_xpu` on the reported two-XPU setup and inspect `test/test_cuda_multigpu.py`, especially the test and assertion at line 689. Trace why the allocation is reused too soon; done means the failure is understood and the targeted test passes while retaining its intended check.

Written by the indexing model from the issue text.