Facing Segmentation Fault on MaskedMHA Test

[Alok-Ranjan23]

Describe the bug

I am running following test.
python tests/cpu/test_masked_mha.py -k MaskedMHATest
But If I set head_size = x s.t x%16!=0, then it results in Segmentation fault (core dumped).

Is there any restriction on head_size ? I understand that head_num should be the multiple of kv_num.
But There is only condition for head_size i.e. head_size*head_num=hidden_size
Should head_size always be a multiple of 16? If yes, Why?

Versions

Collecting environment information...
PyTorch version: 2.4.0+cpu
PyTorch CXX11 ABI: No
IPEX version: N/A
IPEX commit: N/A
Build type: N/A

OS: Ubuntu 22.04.2 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: N/A
IGC version: N/A
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.10.14 (main, May 6 2024, 19:42:50) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.5.0-15-generic-x86_64-with-glibc2.35
Is XPU available: N/A
DPCPP runtime version: N/A
MKL version: N/A
GPU models and configuration:
N/A
Intel OpenCL ICD version: N/A
Level Zero version: N/A

CPU:
Architecture: x86_64
CPU op-mode(s): 32-bit, 64-bit
Address sizes: 48 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 32
On-line CPU(s) list: 0-31
Vendor ID: AuthenticAMD
Model name: AMD Ryzen 9 7950X 16-Core Processor
CPU family: 25
Model: 97
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 1
Stepping: 2
CPU max MHz: 5881.0000
CPU min MHz: 400.0000
BogoMIPS: 8983.47
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 amd_lbr_v2 nopl nonstop_tsc cpuid extd_apicid aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 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 perfmon_v2 ibrs ibpb stibp ibrs_enhanced vmmcall fsgsbase bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local avx512_bf16 clzero irperf xsaveerptr rdpru wbnoinvd cppc arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif x2avic v_spec_ctrl vnmi avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid overflow_recov succor smca fsrm flush_l1d
Virtualization: AMD-V
L1d cache: 512 KiB (16 instances)
L1i cache: 512 KiB (16 instances)
L2 cache: 16 MiB (16 instances)
L3 cache: 64 MiB (2 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-31
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: 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; Enhanced / Automatic IBRS, IBPB conditional, STIBP always-on, 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==2.4.0+git5d871a0
[pip3] numpy==2.1.1
[pip3] torch==2.4.0+cpu
[conda] intel-extension-for-pytorch 2.4.0+git5d871a0 pypi_0 pypi
[conda] mkl-include 2024.2.1 pypi_0 pypi
[conda] mkl-static 2024.2.1 pypi_0 pypi
[conda] numpy 2.1.1 pypi_0 pypi
[conda] torch 2.4.0+cpu pypi_0 pypi

[devpramod]

Hi @Alok-Ranjan23
We are looking into this issue internally

[devpramod]

Hi @Alok-Ranjan23 This issue has been resolved in ipex v2.5.0+cpu
https://intel.github.io/intel-extension-for-pytorch/#installation?platform=cpu&version=v2.5.0%2bcpu&os=linux%2fwsl2&package=pip