model.to('xpu') does not terminate

[BiaBibii]

Describe the issue

When trying to upload a simple model to 'xpu' device, the script is taking a lot of time, and also doesn't finish.
Firstly tried with a resnet50, but after that with the simplest tensor (got the same problem):

import torch
import intel_extension_for_pytorch as ipex

device = torch.device('xpu')  
print(ipex.xpu.is_available())
print('uploading model to device...')
torch.randn(1).to(device)
print('model was uploaded to device.')

and got the same issue:

Collecting environment information...
PyTorch version: 2.1.0.post0+cxx11.abi
PyTorch CXX11 ABI: Yes
IPEX version: 2.1.20+xpu
IPEX commit: b78b4d97e
Build type: Release

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (conda-forge gcc 12.3.0-5) 12.3.0
Clang version: N/A
IGC version: N/A
CMake version: version 3.26.4
Libc version: glibc-2.35

Python version: 3.11.7 (main, Dec 15 2023, 18:12:31) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.5.0-28-generic-x86_64-with-glibc2.35
Is XPU available: True
DPCPP runtime version: N/A
MKL version: N/A
GPU models and configuration: 
[0] _DeviceProperties(name='Intel(R) Graphics [0x7d55]', platform_name='Intel(R) Level-Zero', dev_type='gpu, support_fp64=1, total_memory=29338MB, max_compute_units=128, gpu_eu_count=128)
Intel OpenCL ICD version: 23.43.27642.40-803~22.04
Level Zero version: 1.3.27642.40-803~22.04

CPU:
Architecture:                       x86_64
CPU op-mode(s):                     32-bit, 64-bit
Address sizes:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             22
On-line CPU(s) list:                0-21
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Core(TM) Ultra 7 155H
CPU family:                         6
Model:                              170
Thread(s) per core:                 2
Core(s) per socket:                 16
Socket(s):                          1
Stepping:                           4
CPU max MHz:                        4700.0000
CPU min MHz:                        400.0000
BogoMIPS:                           5990.40
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 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb invpcid_single intel_ppin ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid bus_lock_detect movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities
Virtualization:                     VT-x
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-21
Vulnerability Gather data sampling: 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 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, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] intel-extension-for-pytorch==2.1.20+xpu
[pip3] mypy==1.8.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.4
[pip3] numpydoc==1.5.0
[pip3] torch==2.1.0.post0+cxx11.abi
[pip3] torchaudio==2.1.0.post0+cxx11.abi
[pip3] torchvision==0.16.0.post0+cxx11.abi
[conda] _anaconda_depends         2024.02             py311_mkl_1  
[conda] blas                      1.0                         mkl  
[conda] intel-extension-for-pytorch 2.1.20+xpu               pypi_0    pypi
[conda] mkl                       2023.2.0         h84fe81f_50496    conda-forge
[conda] mkl-include               2024.1.0              intel_691    intel
[conda] mkl-service               2.4.0           py311h5eee18b_1  
[conda] mkl-static                2024.1.0              intel_691    intel
[conda] mkl_fft                   1.3.8           py311h5eee18b_0  
[conda] mkl_random                1.2.4           py311hdb19cb5_0  
[conda] numpy                     1.26.4          py311h08b1b3b_0  
[conda] numpy-base                1.26.4          py311hf175353_0  
[conda] numpydoc                  1.5.0           py311h06a4308_0  
[conda] torch                     2.1.0.post0+cxx11.abi          pypi_0    pypi
[conda] torchaudio                2.1.0.post0+cxx11.abi          pypi_0    pypi
[conda] torchvision               0.16.0.post0+cxx11.abi          pypi_0    pypi

[ZailiWang]

Hi, I'm afraid the support for iGPU is in the roadmap of IPEX evolution, but so far this is not the case, so it's possible to get stability or performance issues. Please keep tuned for this support, thanks.

[airMeng]

Hi, this might because the official release doesn't include iGPU AOT, you can try the community version at least for MTL

https://github.com/Nuullll/intel-extension-for-pytorch/releases

@tye1 @ashokei FYI

[ZailiWang]

Yeah, I communicated offline with the reporter that we could try source code build with AOT code "0x7d55". Of course the community version is worth to try.