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Errors when running setup script for QNN #4655

@guangy10

Description

@guangy10

🐛 Describe the bug

Follow up guide here: https://pytorch.org/executorch/main/build-run-qualcomm-ai-engine-direct-backend.html#setting-up-your-developer-environment

Then run ./backends/qualcomm/scripts/build.sh --release, will hit the error:

~/executorch/examples/qualcomm/llama2/qaihub_runner/runner.cpp:21:10: fatal error: 'executorch/examples/models/llama2/runner/util.h' file not found
   21 | #include <executorch/examples/models/llama2/runner/util.h>
      |          ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
1 error generated.
gmake[2]: *** [CMakeFiles/qnn_qaihub_llama_runner.dir/build.make:90: CMakeFiles/qnn_qaihub_llama_runner.dir/llama2/qaihub_runner/runner.cpp.o] Error 1
gmake[2]: *** Waiting for unfinished jobs....
[ 39%] Building CXX object CMakeFiles/full_portable_ops_lib.dir/full_portable_ops_lib/RegisterCodegenUnboxedKernelsEverything.cpp.o
gmake[1]: *** [CMakeFiles/Makefile2:167: CMakeFiles/qnn_qaihub_llama_runner.dir/all] Error 2
gmake[1]: *** Waiting for unfinished jobs....
[ 42%] Linking CXX static library libfull_portable_ops_lib.a
[ 42%] Built target full_portable_ops_lib
gmake: *** [Makefile:91: all] Error 2

Versions

Collecting environment information...
PyTorch version: 2.5.0.dev20240716+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: CentOS Stream 9 (x86_64)
GCC version: (GCC) 11.4.1 20231218 (Red Hat 11.4.1-3)
Clang version: Could not collect
CMake version: version 3.29.0
Libc version: glibc-2.34

Python version: 3.10.0 | packaged by conda-forge | (default, Nov 20 2021, 02:24:10) [GCC 9.4.0] (64-bit runtime)
Python platform: Linux-5.19.0-0_fbk21_hardened_12633_g4db063a1bcb5-x86_64-with-glibc2.34
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
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: 40 bits physical, 48 bits virtual
Byte Order: Little Endian
CPU(s): 72
On-line CPU(s) list: 0-71
Vendor ID: GenuineIntel
Model name: Intel Core Processor (Broadwell)
CPU family: 6
Model: 61
Thread(s) per core: 1
Core(s) per socket: 36
Socket(s): 2
Stepping: 2
BogoMIPS: 3990.62
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 rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 2.3 MiB (72 instances)
L1i cache: 2.3 MiB (72 instances)
L2 cache: 288 MiB (72 instances)
L3 cache: 32 MiB (2 instances)
NUMA node(s): 1
NUMA node0 CPU(s): 0-71
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Mitigation; PTE Inversion; VMX vulnerable, SMT disabled
Vulnerability Mds: Vulnerable; SMT Host state unknown
Vulnerability Meltdown: Vulnerable
Vulnerability Mmio stale data: Not affected
Vulnerability Retbleed: Not affected
Vulnerability Spec store bypass: Vulnerable
Vulnerability Spectre v1: Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2: Vulnerable, STIBP: disabled
Vulnerability Srbds: Unknown: Dependent on hypervisor status
Vulnerability Tsx async abort: Vulnerable

Versions of relevant libraries:
[pip3] executorch==0.4.0a0+79c15ef
[pip3] flake8==6.1.0
[pip3] flake8-breakpoint==1.1.0
[pip3] flake8-bugbear==23.9.16
[pip3] flake8-comprehensions==3.14.0
[pip3] flake8-executable==2.1.3
[pip3] flake8-logging-format==0.9.0
[pip3] flake8-plugin-utils==1.3.3
[pip3] flake8-pyi==23.5.0
[pip3] flake8-simplify==0.19.3
[pip3] mypy==1.8.0
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.21.3
[pip3] optree==0.10.0
[pip3] torch==2.5.0.dev20240716+cpu
[pip3] torchao==0.1
[pip3] torchaudio==2.4.0.dev20240716+cpu
[pip3] torchsr==1.0.4
[pip3] torchvision==0.20.0.dev20240716+cpu
[pip3] triton==3.0.0
[conda] executorch 0.4.0a0+79c15ef pypi_0 pypi
[conda] numpy 1.21.3 pypi_0 pypi
[conda] optree 0.10.0 pypi_0 pypi
[conda] torch 2.5.0.dev20240716+cpu pypi_0 pypi
[conda] torchao 0.1 pypi_0 pypi
[conda] torchaudio 2.4.0.dev20240716+cpu pypi_0 pypi
[conda] torchfix 0.5.0 pypi_0 pypi
[conda] torchsr 1.0.4 pypi_0 pypi
[conda] torchvision 0.20.0.dev20240716+cpu pypi_0 pypi
[conda] triton 3.0.0 pypi_0 pypi

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module: qnnIssues related to Qualcomm's QNN delegate and code under backends/qualcomm/partner: qualcommFor backend delegation, kernels, demo, etc. from the 3rd-party partner, QualcommtriagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate module

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