saymrwulf/onnxruntime
1
0
Fork 0
mirror of https://github.com/saymrwulf/onnxruntime.git synced 2026-07-16 18:31:27 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

[QNN EP] QNN EP doc update (#18399)

Browse source 
### Description
Add more EP options enabled recently
This commit is contained in:
Hector Li 2023-11-13 14:03:29 -08:00 committed by GitHub
parent 5e25b8dc34
commit a8bce5b3bf
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 23 additions and 1 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

24
docs/execution-providers/QNN-ExecutionProvider.md
View file

@ -74,6 +74,28 @@ The QNN Execution Provider supports a number of configuration options. The `prov
|'/path/to/context/cache'|string path to context cache binary|
|`provider_options_values` for `provider_options_keys = "qnn_context_embed_mode"`|Description|
|---|---|
|'0'|generate the QNN context binary into separate file, set path in ONNX file specified by qnn_context_cache_path.|
|'1'|generate the QNN context binary into the ONNX file specified by qnn_context_cache_path (default).|
|`provider_options_values` for `provider_options_keys = "qnn_context_priority"`|[Description](https://docs.qualcomm.com/bundle/publicresource/topics/80-63442-50/htp_yielding.html)|
|---|---|
|'low'||
|'normal'|default.|
|'normal_high'||
|'high'||
|`provider_options_values` for `provider_options_keys = "htp_graph_finalization_optimization_mode"`|Description|
|---|---|
|'0'|default.|
|'1'|faster preparation time, less optimal graph.|
|'2'|longer preparation time, more optimal graph.|
|'3'|longest preparation time, most likely even more optimal graph.|
## Usage
### C++
C API details are [here](../get-started/with-c.md).
@ -94,4 +116,4 @@ sess = ort.InferenceSession(model_path, providers=['QNNExecutionProvider'], prov
### Inference example
[Image classification with Mobilenetv2 in CPP using QNN Execution Provider with QNN CPU & HTP Backend](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_cxx/QNN_EP)
[Image classification with Mobilenetv2 in CPP using QNN Execution Provider with QNN CPU & HTP Backend](https://github.com/microsoft/onnxruntime-inference-examples/tree/main/c_cxx/QNN_EP/mobilenetv2_classification)