Native API returns: 29 (UR_RESULT_ERROR_INVALID_KERNEL_NAME) when sampling from

[Nehereus]

Describe the bug

Native API returns 29 when trying to sample from a bernoulli distribution. Though the current torch version is 2.9.1 without IPEX installed, the issue can be replicated using torch 2.8 with IPEX.
Sample code to replicate the issue:

def test_bernoulli_sample_properties(self):
        """
        Tests properties of samples from a Bernoulli distribution on XPU.
        """
        # --- Test 1: Check for XPU availability ---
        if not torch.xpu.is_available():
            self.skipTest("XPU device not available")
            
        device = 'xpu'

        # Define the probabilities for the Bernoulli distribution
        # Use a tensor with multiple probabilities to test batch sampling
        # Move the tensor to the XPU device
        probs = torch.tensor([0.1, 0.5, 0.9], device=device)
        
        # Create the Bernoulli distribution
        try:
            bernoulli_dist = dist.Bernoulli(probs=probs)
        except Exception as e:
            self.fail(f"Failed to create Bernoulli distribution: {e}")

        # --- Test 1: Sample values are valid (0 or 1) ---
        
        # Draw a single sample
        sample_single = bernoulli_dist.sample()
        
        # Check that all sampled values are either 0 or 1
        is_zero_or_one = (sample_single == 0) | (sample_single == 1)
        self.assertTrue(torch.all(is_zero_or_one), 
                        "Sampled values are not all 0 or 1.")
        
        # Check output shape
        self.assertEqual(sample_single.shape, probs.shape,
                         "Single sample shape does not match probs shape.")

        # Check that the sample is on the correct device
        self.assertEqual(sample_single.device.type, device,
                         "Sample is not on the XPU device.")

Versions

ollecting environment information...

PyTorch version: 2.9.1+xpu
PyTorch CXX11 ABI: Yes
IPEX version: N/A
IPEX commit: N/A
Build type: N/A

OS: Ubuntu 24.04.3 LTS (x86_64)
GCC version: (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0
Clang version: N/A
IGC version: N/A
CMake version: N/A
Libc version: glibc-2.39

Python version: 3.12.3 (main, Aug 14 2025, 17:47:21) [GCC 13.3.0] (64-bit runtime)
Python platform: Linux-6.14.8-3-bpo12-pve-x86_64-with-glibc2.39
Is XPU available: N/A
DPCPP runtime: 2025.1
MKL version: 2025.1

GPU models and configuration onboard:
N/A

GPU models and configuration detected:
N/A

Driver version:

• intel_opencl: 25.35.35096.9-124.04ppa3
• level_zero: N/A

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 43 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 24
On-line CPU(s) list: 0-23
Vendor ID: AuthenticAMD
Model name: AMD Ryzen 9 3900X 12-Core Processor
CPU family: 23
Model: 113
Thread(s) per core: 2
Core(s) per socket: 12
Socket(s): 1
Stepping: 0
Frequency boost: enabled
CPU(s) scaling MHz: 79%
CPU max MHz: 4673.0000
CPU min MHz: 550.0000
BogoMIPS: 7586.51
Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sev sev_es
Virtualization: AMD-V
L1d cache: 384 KiB (12 instances)
L1i cache: 384 KiB (12 instances)
L2 cache: 6 MiB (12 instances)
L3 cache: 64 MiB (4 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-23
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 Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow: Mitigation; Safe RET
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; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
Vulnerability Vmscape: Mitigation; IBPB before exit to userspace

Versions of relevant libraries:
[pip] dpcpp-cpp-rt==2025.2.1
[pip] impi-rt==2021.16.1
[pip] intel-cmplr-lib-rt==2025.2.1
[pip] intel-cmplr-lib-ur==2025.2.1
[pip] intel-cmplr-lic-rt==2025.2.1
[pip] intel-opencl-rt==2025.2.1
[pip] intel-openmp==2025.2.1
[pip] intel-pti==0.13.1
[pip] intel-sycl-rt==2025.2.1
[pip] mkl==2025.2.0
[pip] numpy==2.3.3
[pip] oneccl==2021.16.1
[pip] oneccl-devel==2021.16.1
[pip] onemkl-sycl-blas==2025.2.0
[pip] onemkl-sycl-dft==2025.2.0
[pip] onemkl-sycl-lapack==2025.2.0
[pip] onemkl-sycl-rng==2025.2.0
[pip] onemkl-sycl-sparse==2025.2.0
[pip] pytorch-triton-xpu==3.5.0
[pip] torch==2.9.1+xpu
[pip] torchaudio==2.9.1+xpu
[pip] torchvision==0.24.1+xpu
[pip] transformers==4.57.1

[tye1]

@Nehereus Since you are able to reproduce this issue only with PyTorch 2.9.1, it is not related to IPEX. Could you please open an issue in https://github.com/intel/torch-xpu-ops/ for awareness?