ExecuTorch runner of Qnn backend can't run the pte model by following the tutorial.

🐛 Describe the bug

I follow the tutorial to build the runner of Qnn backend and run it:
https://pytorch.org/executorch/main/build-run-qualcomm-ai-engine-direct-backend.html

But that the run model step:

adb shell "cd ${DEVICE_DIR} \
           && export LD_LIBRARY_PATH=${DEVICE_DIR} \
           && export ADSP_LIBRARY_PATH=${DEVICE_DIR} \
           && ./qnn_executor_runner --model_path ./dlv3_qnn.pte"

I found the error & warning message:

I 00:00:00.000852 executorch:qnn_executor_runner.cpp:160] Model file ./dl3_qnn_q8.pte is loaded.
I 00:00:00.000883 executorch:qnn_executor_runner.cpp:170] Using method forward
I 00:00:00.000896 executorch:qnn_executor_runner.cpp:217] Setting up planned buffer 0, size 9031680.
[INFO] [Qnn ExecuTorch]: Deserializing processed data using QnnContextCustomProtocol
[INFO] [Qnn ExecuTorch]: create QNN Logger with log_level 2
[WARNING] [Qnn ExecuTorch]:  <W> Initializing HtpProvider

[ERROR] [Qnn ExecuTorch]:  <E> Stub lib id mismatch: expected (v2.28.2.241116104011_103376), detected (v2.25.17.241017130936_18858)

[ERROR] [Qnn ExecuTorch]:  <E> Unable to load Remote symbols 1008

[ERROR] [Qnn ExecuTorch]:  <E> Unable to load Remote symbols 1008

[WARNING] [Qnn ExecuTorch]:  <W> Function not called, PrepareLib isn't loaded!

[INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
[INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
[INFO] [Qnn ExecuTorch]: QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000

I ensure I only install (v2.28.2.241116104011_103376) HTP SDK, do you know why detected stub is v2.25.17.241017130936_18858?
[ERROR] [Qnn ExecuTorch]: <E> Stub lib id mismatch: expected (v2.28.2.241116104011_103376), detected (v2.25.17.241017130936_18858)

And please note the message:
QnnContextCustomProtocol expected magic number: 0x5678abcd but get: 0x2000000

Thanks.

Versions

Versions
Collecting environment information...
PyTorch version: 2.6.0+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.31.4
Libc version: glibc-2.35

Python version: 3.10.12 (main, Feb 4 2025, 14:57:36) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-5.15.167.4-microsoft-standard-WSL2-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: N/A
Nvidia driver version: 560.94
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_adv.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_cnn.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_precompiled.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_engines_runtime_compiled.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_graph.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_heuristic.so.9.7.1
/usr/lib/x86_64-linux-gnu/libcudnn_ops.so.9.7.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

Versions of relevant libraries:
[pip3] executorch==0.6.0a0+791472d
[pip3] numpy==2.0.0
[pip3] nvidia-cublas-cu12==12.4.5.8
[pip3] nvidia-cuda-cupti-cu12==12.4.127
[pip3] nvidia-cuda-nvrtc-cu12==12.4.127
[pip3] nvidia-cuda-runtime-cu12==12.4.127
[pip3] nvidia-cudnn-cu12==9.1.0.70
[pip3] nvidia-cufft-cu12==11.2.1.3
[pip3] nvidia-curand-cu12==10.3.5.147
[pip3] nvidia-cusolver-cu12==11.6.1.9
[pip3] nvidia-cusparse-cu12==12.3.1.170
[pip3] nvidia-cusparselt-cu12==0.6.2
[pip3] nvidia-nccl-cu12==2.21.5
[pip3] nvidia-nvjitlink-cu12==12.4.127
[pip3] nvidia-nvtx-cu12==12.4.127
[pip3] pytorch-triton==3.2.0+gitb2684bf3
[pip3] torch==2.6.0+cpu
[pip3] torchao==0.8.0+git11333ba2
[pip3] torchaudio==2.6.0+cpu
[pip3] torchsr==1.0.4
[pip3] torchtune==0.6.0.dev20250131+cu124
[pip3] torchvision==0.21.0+cpu
[conda] Could not collect

cc @cccclai @winskuo-quic @shewu-quic @cbilgin @mergennachin @byjlw