I was wondering if its possible to test the QNN delegate on Android Studio emulator by building an .aar file for x86_64 ABI. I am guessing that it might not work because emulators are not equipped for QNN backend, but wanted to double check.
Versions
PyTorch version: 2.6.0.dev20241101+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A
Python version: 3.10.15 (main, Oct 3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.8.0-39-generic-x86_64-with-glibc2.39
Is CUDA available: False
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1080 Ti
Nvidia driver version: 550.90.07
cuDNN version: Could not collect
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, 48 bits virtual
Byte Order: Little Endian
CPU(s): 48
On-line CPU(s) list: 0-23
Off-line CPU(s) list: 24-47
Vendor ID: GenuineIntel
Model name: Intel(R) Xeon(R) Silver 4116 CPU @ 2.10GHz
CPU family: 6
Model: 85
Thread(s) per core: 1
Core(s) per socket: 12
Socket(s): 2
Stepping: 4
CPU(s) scaling MHz: 34%
CPU max MHz: 3000.0000
CPU min MHz: 0.0000
BogoMIPS: 4200.00
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 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 cdp_l3 pti ssbd mba ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi pku ospke md_clear flush_l1d arch_capabilities
Virtualization: VT-x
L1d cache: 768 KiB (24 instances)
L1i cache: 768 KiB (24 instances)
L2 cache: 24 MiB (24 instances)
L3 cache: 33 MiB (2 instances)
NUMA node(s): 2
NUMA node0 CPU(s): 0-11
NUMA node1 CPU(s): 12-23
Vulnerability Gather data sampling: Vulnerable
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT disabled
Vulnerability Mds: Mitigation; Clear CPU buffers; SMT disabled
Vulnerability Meltdown: Mitigation; PTI
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT disabled
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed: Mitigation; IBRS
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; IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT disabled
metascroy
commented
33 minutes ago
🐛 Describe the bug
Hello,
I was wondering if its possible to test the QNN delegate on Android Studio emulator by building an
.aarfile forx86_64ABI. I am guessing that it might not work because emulators are not equipped for QNN backend, but wanted to double check.Versions
PyTorch version: 2.6.0.dev20241101+cpu Is debug build: False CUDA used to build PyTorch: Could not collect ROCM used to build PyTorch: N/A
OS: Ubuntu 24.04 LTS (x86_64) GCC version: (Ubuntu 13.2.0-23ubuntu4) 13.2.0 Clang version: 18.1.3 (1ubuntu1) CMake version: version 3.30.5 Libc version: glibc-2.39
Python version: 3.10.15 (main, Oct 3 2024, 07:27:34) [GCC 11.2.0] (64-bit runtime) Python platform: Linux-6.8.0-39-generic-x86_64-with-glibc2.39 Is CUDA available: False CUDA runtime version: Could not collect CUDA_MODULE_LOADING set to: N/A GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1080 Ti Nvidia driver version: 550.90.07 cuDNN version: Could not collect 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, 48 bits virtual Byte Order: Little Endian CPU(s): 48 On-line CPU(s) list: 0-23 Off-line CPU(s) list: 24-47 Vendor ID: GenuineIntel Model name: Intel(R) Xeon(R) Silver 4116 CPU @ 2.10GHz CPU family: 6 Model: 85 Thread(s) per core: 1 Core(s) per socket: 12 Socket(s): 2 Stepping: 4 CPU(s) scaling MHz: 34% CPU max MHz: 3000.0000 CPU min MHz: 0.0000 BogoMIPS: 4200.00 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 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 cdp_l3 pti ssbd mba ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req vnmi pku ospke md_clear flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 768 KiB (24 instances) L1i cache: 768 KiB (24 instances) L2 cache: 24 MiB (24 instances) L3 cache: 33 MiB (2 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-11 NUMA node1 CPU(s): 12-23 Vulnerability Gather data sampling: Vulnerable Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled Vulnerability L1tf: Mitigation; PTE Inversion; VMX conditional cache flushes, SMT disabled Vulnerability Mds: Mitigation; Clear CPU buffers; SMT disabled Vulnerability Meltdown: Mitigation; PTI Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT disabled Vulnerability Reg file data sampling: Not affected Vulnerability Retbleed: Mitigation; IBRS 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; IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Mitigation; Clear CPU buffers; SMT disabled
Versions of relevant libraries: [pip3] executorch==0.5.0a0+026fe0b [pip3] numpy==1.26.4 [pip3] torch==2.6.0.dev20241101+cpu [pip3] torchao==0.5.0+git0916b5b2 [pip3] torchaudio==2.5.0.dev20241101+cpu [pip3] torchsr==1.0.4 [pip3] torchvision==0.20.0.dev20241101+cpu [conda] executorch 0.5.0a0+026fe0b pypi_0 pypi [conda] numpy 1.26.4 pypi_0 pypi [conda] torch 2.6.0.dev20241101+cpu pypi_0 pypi [conda] torchao 0.5.0 pypi_0 pypi [conda] torchaudio 2.5.0.dev20241101+cpu pypi_0 pypi [conda] torchsr 1.0.4 pypi_0 pypi [conda] torchvision 0.20.0.dev20241101+cpu pypi_0 pypi