🐛 Describe the bug

• op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_upsampling_64bit_indexing_channels_last_xpu_bfloat16

_______________________________________________________________________________________________________ TestNNDeviceTypeXPU.test_upsampling_64bit_indexing_channels_last_xpu_bfloat16 ________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10415, in test_upsampling_64bit_indexing_channels_last
    out = torch.nn.functional.interpolate(x.to(memory_format=torch.channels_last), scale_factor=2, mode='nearest')
  File "/home/gta/.conda/envs/mengfeil/lib/python3.10/site-packages/torch/nn/functional.py", line 4803, in interpolate
    return torch._C._nn.upsample_nearest2d(input, output_size, scale_factors)
RuntimeError: Non-uniform work-groups are not supported by the target device

To execute this test, run the following from the base repo dir:
    python ../../test/test_nn.py TestNNDeviceTypeXPU.test_upsampling_64bit_indexing_channels_last_xpu_bfloat16

• op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_upsampling_64bit_indexing_channels_last_xpu_float16

________________________________________________________________________________________________________ TestNNDeviceTypeXPU.test_upsampling_64bit_indexing_channels_last_xpu_float16 ________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10415, in test_upsampling_64bit_indexing_channels_last
    out = torch.nn.functional.interpolate(x.to(memory_format=torch.channels_last), scale_factor=2, mode='nearest')
  File "/home/gta/.conda/envs/mengfeil/lib/python3.10/site-packages/torch/nn/functional.py", line 4803, in interpolate
    return torch._C._nn.upsample_nearest2d(input, output_size, scale_factors)
RuntimeError: Non-uniform work-groups are not supported by the target device

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_SLOW=1 python ../../test/test_nn.py TestNNDeviceTypeXPU.test_upsampling_64bit_indexing_channels_last_xpu_float16

• op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_softmax_backward_64bit_indexing_xpu

________________________________________________________________________________________________________________ TestNNDeviceTypeXPU.test_softmax_backward_64bit_indexing_xpu ________________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 13502, in test_softmax_backward_64bit_indexing
    out = torch._softmax_backward_data(x, x, 2, x.dtype)
RuntimeError: The number of work-items in each dimension of a work-group cannot exceed {1024, 1024, 1024} for this device

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_SLOW=1 python ../../test/test_nn.py TestNNDeviceTypeXPU.test_softmax_backward_64bit_indexing_xpu

• op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_warp_softmax_64bit_indexing_xpu_float16

______________________________________________________________________________________________________________ TestNNDeviceTypeXPU.test_warp_softmax_64bit_indexing_xpu_float16 ______________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10777, in test_warp_softmax_64bit_indexing
    run_test(1100000000, 2)  # Illegal memory access https://github.com/pytorch/pytorch/issues/52715
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10763, in run_test
    x = torch.randn(shape, device="cuda", dtype=torch.float16, requires_grad=True)
  File "/home/gta/.conda/envs/mengfeil/lib/python3.10/site-packages/torch/cuda/__init__.py", line 404, in _lazy_init
    raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_SLOW=1 python ../../test/test_nn.py TestNNDeviceTypeXPU.test_warp_softmax_64bit_indexing_xpu_float16

• op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_warp_softmax_64bit_indexing_xpu_float32

______________________________________________________________________________________________________________ TestNNDeviceTypeXPU.test_warp_softmax_64bit_indexing_xpu_float32 ______________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10777, in test_warp_softmax_64bit_indexing
    run_test(1100000000, 2)  # Illegal memory access https://github.com/pytorch/pytorch/issues/52715
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_nn.py", line 10763, in run_test
    x = torch.randn(shape, device="cuda", dtype=torch.float16, requires_grad=True)
  File "/home/gta/.conda/envs/mengfeil/lib/python3.10/site-packages/torch/cuda/__init__.py", line 404, in _lazy_init
    raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_SLOW=1 python ../../test/test_nn.py TestNNDeviceTypeXPU.test_warp_softmax_64bit_indexing_xpu_float32

• op_ut,third_party.torch-xpu-ops.test.xpu.test_unary_ufuncs_xpu.TestUnaryUfuncsXPU,test_nonzero_large_xpu_int8

_______________________________________________________________________________________________________________________ TestUnaryUfuncsXPU.test_nonzero_large_xpu_int8 _______________________________________________________________________________________________________________________
Traceback (most recent call last):
  File "/home/gta/mengfeil/pytorch/third_party/torch-xpu-ops/test/xpu/../../../../test/test_unary_ufuncs.py", line 1583, in test_nonzero_large
    y = torch.nonzero(x, as_tuple=True)
RuntimeError: nonzero is not supported for tensors with more than INT_MAX elements,       See https://github.com/pytorch/pytorch/issues/51871

To execute this test, run the following from the base repo dir:
    PYTORCH_TEST_WITH_SLOW=1 python ../../test/test_unary_ufuncs.py TestUnaryUfuncsXPU.test_nonzero_large_xpu_int8

• op_ut,third_party.torch-xpu-ops.test.xpu.test_ops_xpu.TestMathBitsXPU,test_neg_view_to_sparse_xpu_float64

Cases:
op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_upsampling_64bit_indexing_channels_last_xpu_bfloat16
op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_upsampling_64bit_indexing_channels_last_xpu_float16
op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_softmax_backward_64bit_indexing_xpu
op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_warp_softmax_64bit_indexing_xpu_float16
op_ut,third_party.torch-xpu-ops.test.xpu.test_nn_xpu.TestNNDeviceTypeXPU,test_warp_softmax_64bit_indexing_xpu_float32
op_ut,third_party.torch-xpu-ops.test.xpu.test_unary_ufuncs_xpu.TestUnaryUfuncsXPU,test_nonzero_large_xpu_int8

Versions

Collecting environment information...
PyTorch version: 2.10.0a0+gitc43ccfb
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 4.0.0
Libc version: glibc-2.35

Python version: 3.10.18 (main, Jun 4 2025, 04:05:45) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.0-153-generic-x86_64-with-glibc2.35
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: 20250201
Intel GPU driver version:

• intel-opencl-icd: 25.18.33578.15-1146~22.04
• libze1: 1.21.9.0-1136~22.04
  Intel GPU models onboard:
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
• Intel(R) Data Center GPU Max 1100
  Intel GPU models detected:
• [0] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-0f00-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [1] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-1600-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [2] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-1a00-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [3] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-1e00-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [4] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-af00-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [5] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-b300-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [6] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-bf00-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
• [7] _XpuDeviceProperties(name='Intel(R) Data Center GPU Max 1100', platform_name='Intel(R) oneAPI Unified Runtime over Level-Zero', type='gpu', device_id=0xBDA, uuid=8680da0b-2f00-0000-c300-000000000000, driver_version='1.6.33578+15', total_memory=49136MB, max_compute_units=448, gpu_eu_count=448, gpu_subslice_count=56, max_work_group_size=1024, max_num_sub_groups=64, sub_group_sizes=[16 32], has_fp16=1, has_fp64=1, has_atomic64=1)
  HIP runtime version: N/A
  MIOpen runtime version: N/A
  Is XNNPACK available: True

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 46 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 192
On-line CPU(s) list: 0-191
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Platinum 8468V
CPU family: 6
Model: 143
Thread(s) per core: 2
Core(s) per socket: 48
Socket(s): 2
Stepping: 8
Frequency boost: enabled
CPU max MHz: 2401.0000
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 invpcid_single intel_ppin cdp_l2 ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi 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 avx_vnni avx512_bf16 wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq la57 rdpid bus_lock_detect cldemote movdiri movdir64b enqcmd fsrm md_clear serialize tsxldtrk pconfig arch_lbr amx_bf16 avx512_fp16 amx_tile amx_int8 flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 4.5 MiB (96 instances)
L1i cache: 3 MiB (96 instances)
L2 cache: 192 MiB (96 instances)
L3 cache: 195 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-47,96-143
NUMA node1 CPU(s): 48-95,144-191
Vulnerability Gather data sampling: 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 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 and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB disabled; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] dpcpp-cpp-rt==2025.2.1
[pip3] impi-rt==2021.16.1
[pip3] intel-cmplr-lib-rt==2025.2.1
[pip3] intel-cmplr-lib-ur==2025.2.1
[pip3] intel-cmplr-lic-rt==2025.2.1
[pip3] intel-opencl-rt==2025.2.1
[pip3] intel-openmp==2025.2.1
[pip3] intel-pti==0.13.1
[pip3] intel-sycl-rt==2025.2.1
[pip3] mkl==2025.2.0
[pip3] mypy==1.16.0
[pip3] mypy_extensions==1.1.0
[pip3] numpy==1.22.4
[pip3] oneccl==2021.16.1
[pip3] oneccl-devel==2021.16.1
[pip3] onemkl-sycl-blas==2025.2.0
[pip3] onemkl-sycl-dft==2025.2.0
[pip3] onemkl-sycl-lapack==2025.2.0
[pip3] onemkl-sycl-rng==2025.2.0
[pip3] onemkl-sycl-sparse==2025.2.0
[pip3] onnx==1.18.0
[pip3] onnx-ir==0.1.9
[pip3] onnxscript==0.4.0
[pip3] optree==0.13.0
[pip3] pytorch-triton-xpu==3.5.0+git1b0418a9
[pip3] tbb==2022.2.0
[pip3] tcmlib==1.4.0
[pip3] torch==2.10.0a0+gitc43ccfb
[pip3] torchao==0.14.0.dev20250918+xpu
[pip3] torchaudio==2.8.0a0+87ff22e
[pip3] torchvision==0.22.0a0+966da7e
[pip3] umf==0.11.0
[conda] Could not collect