QNN EP Sample - Fresh build with latest official QNN package produces errors on ARM64 Snapdragon QC PC
Nobody has claimed this yet.
Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 25/100
- Issue type
- Bug
- Clarity
- Needs clarification
- Activity status
- Stale
- Tech stack
- cpp
- Domain
- machine-learning, operating-systems
Research direction
Start with run_qnn_ep_sample.bat and qnn_ep_sample.exe, reproducing the two reported failures on the ARM64 Snapdragon system. Read arm/windows/init.c alongside the QNN sample paths and the reported EpContext errors. Done means the affected executions no longer error or crash while the combinations already reported as working remain successful.
Written by the indexing model from the issue text.
Description
I used official latest ORT 1.20 pre-built package per https://onnxruntime.ai/docs/execution-providers/QNN-ExecutionProvider.html#pre-built-packages-windows-only
It looks to use QNN_2.27.0.240926142112_100894
After build and execute, some of the executions will produce error messages or crash
run_qnn_ep_sample.bat C:\Users\ivberg\Downloads\microsoft.ml.onnxruntime.qnn.1.20.0\build\native C:\Users\ivberg\Downloads\microsoft.ml.onnxruntime.qnn.1.20.0\runtimes\win-arm64\native
// Error 1
REM TODO Check for mobilenetv2-12_quant_shape.onnx_ctx.onnx
Error in cpuinfo: Unknown chip model name 'snapdragon (tm) 8cx gen 3 @ 3.40 GHz'.
Please add new Windows on Arm SoC/chip support to arm/windows/init.c!
unknown Qualcomm CPU part 0x1 ignored
...
2024-11-08 13:02:36.8328541 [E:onnxruntime:, onnx_ctx_model_helper.cc:162 onnxruntime::qnn::LoadQnnCtxFromOnnxGraph] Failed to load from EpContext model. qnn_backend_manager.cc:636 onnxruntime::qnn::QnnBackendManager::LoadCachedQnnContextFromBuffer Failed to get context binary info.
Exception in run_ort_qnn_ep: Failed to load from EpContext model. qnn_backend_manager.cc:636 onnxruntime::qnn::QnnBackendManager::LoadCachedQnnContextFromBuffer Failed to get context binary info.
// Error 2
REM run mobilenetv2-12_net_qnn_ctx.onnx (generated from native QNN) with QNN HTP backend
s:\src\onnxruntime-inference-examples\c_cxx\QNN_EP\mobilenetv2_classification\build\Release>qnn_ep_sample.exe --qnn mobilenetv2-12_net_qnn_ctx.onnx kitten_input_nhwc.raw
Exception in run_ort_qnn_ep:
The other combo of runs work fine
- Dominant language
- C++
- Stars
- 1.7k
- Forks
- 418
- PR merge metrics
- No merged PRs in 30d
Getting set up
Starts the project's dev container in your browser, under your own GitHub account.
- No Dockerfile or Docker Compose file
- No pull request template
- No contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
More from microsoft/onnxruntime-inference-examples
-
Replace deprecated light-server with lite-server for onnxruntime-webPossibly taken A pull request linked to this issue is open or already merged. Open
Difficulty 2/5 1-3 hours Newbie friendliness 68/100
-
Minor: typoPossibly taken @Hashim1999164 claimed this 77 days ago. Open
Difficulty 1/5 Under an hour Newbie friendliness 72/100
microsoft/onnxruntime-inference-examples#124 · 1 reaction ·
-
Difficulty 2/5 1-3 hours Newbie friendliness 38/100
-
Package "onnxruntime-react-native" does not contain a valid config pluginPossibly taken @reginaldalfret claimed this 35 days ago. Open
Difficulty 3/5 1-2 days Newbie friendliness 42/100
-
Difficulty 3/5 1-2 days Newbie friendliness 45/100
All issues in microsoft/onnxruntime-inference-examples
Similar issues
-
Difficulty 2/5 1-3 hours Newbie friendliness 86/100
chipsalliance/verible#2644 ·
-
Difficulty 2/5 1-3 hours Newbie friendliness 74/100
grafana/pyroscope-dotnet#470 ·
Maintainers usually reply within 1 day
-
documentation P5 XS
Difficulty 2/5 1-3 hours Newbie friendliness 72/100
open-astro/AlpacaBridge#1848 ·
Maintainers usually reply within 1 day
-
ai
Difficulty 1/5 Under an hour Newbie friendliness 78/100
Maintainers usually reply within 1 day
-
Difficulty 1/5 1-3 hours Newbie friendliness 76/100
Maintainers usually reply within 3 days