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### Description Add test project that will perform an automated UI test that runs the unit tests on Android. ### Motivation - Enables end-to-end on-device MAUI unit testing which we want to add to the packaging pipelines ### Context Microsoft.ML.OnnxRuntime.Tests.MAUI uses DeviceRunners.VisualRunners to allow running the unit tests (found in Microsoft.ML.OnnxRuntime.Tests.Common) across multiple devices. DeviceRunners.VisualRunners provides a simple UI with a button that will run the unit tests and a panel with the unit test results. In order to automate the process of running the unit tests across mobile devices, Appium is used for UI testing orchestration (it provides a way to interact with the UI), and BrowserStack automatically runs these Appium tests across different mobile devices. This project does not include the capability to start an Appium server locally or attach to a local emulator or device. ## Build & run instructions ### Requirements * A BrowserStack account with access to App Automate * You can set BrowserStack credentials as environment variables as shown [here](https://www.browserstack.com/docs/app-automate/appium/getting-started/c-sharp/nunit/integrate-your-tests#CLI) * ONNXRuntime NuGet package 1. You can either download the [stable NuGet package](https://www.nuget.org/packages/Microsoft.ML.OnnxRuntime) then follow the instructions from [NativeLibraryInclude.props file](../Microsoft.ML.OnnxRuntime.Tests.Common/NativeLibraryInclude.props) to use the downloaded .nupkg file 2. Or follow the [build instructions](https://onnxruntime.ai/docs/build/android.html) to build the Android package locally * The dotnet workloads for maui and maui-android, which will not always automatically install correctly 1. `dotnet workload install maui` 2. `dotnet workload install maui-android` * [Appium](https://appium.io/docs/en/latest/quickstart/) and the [UiAutomator2 driver](https://appium.io/docs/en/latest/quickstart/uiauto2-driver/) ### Run instructions 1. Build the Microsoft.ML.OnnxRuntime.Tests.MAUI project into a signed APK. 1. Run the following: `dotnet publish -c Release -f net8.0-android` in the Microsoft.ML.OnnxRuntime.Tests.MAUI directory. 2. Search for the APK files generated. They should be located in `bin\Release\net8.0-android\publish`. 3. If they're in a different location, edit the `browserstack.yml` file to target the path to the signed APK. 2. Ensure you've set the BrowserStack credentials as environment variables. 3. Run the following in the Microsoft.ML.OnnxRuntime.Tests.Android.BrowserStack directory: `dotnet test` 4. Navigate to the [BrowserStack App Automate dashboard](https://app-automate.browserstack.com/dashboard/v2/builds) to see your test running! |
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ONNX Runtime is a cross-platform inference and training machine-learning accelerator.
ONNX Runtime inference can enable faster customer experiences and lower costs, supporting models from deep learning frameworks such as PyTorch and TensorFlow/Keras as well as classical machine learning libraries such as scikit-learn, LightGBM, XGBoost, etc. ONNX Runtime is compatible with different hardware, drivers, and operating systems, and provides optimal performance by leveraging hardware accelerators where applicable alongside graph optimizations and transforms. Learn more →
ONNX Runtime training can accelerate the model training time on multi-node NVIDIA GPUs for transformer models with a one-line addition for existing PyTorch training scripts. Learn more →
Get Started & Resources
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General Information: onnxruntime.ai
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Usage documentation and tutorials: onnxruntime.ai/docs
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YouTube video tutorials: youtube.com/@ONNXRuntime
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Companion sample repositories:
- ONNX Runtime Inferencing: microsoft/onnxruntime-inference-examples
- ONNX Runtime Training: microsoft/onnxruntime-training-examples
Builtin Pipeline Status
| System | Inference | Training |
|---|---|---|
| Windows | ||
| Linux | ||
| Mac | ||
| Android | ||
| iOS | ||
| Web | ||
| Other |
This project is tested with BrowserStack.
Third-party Pipeline Status
| System | Inference | Training |
|---|---|---|
| Linux |  |
Releases
The current release and past releases can be found here: https://github.com/microsoft/onnxruntime/releases.
For details on the upcoming release, including release dates, announcements, features, and guidance on submitting feature requests, please visit the release roadmap: https://onnxruntime.ai/roadmap.
Data/Telemetry
Windows distributions of this project may collect usage data and send it to Microsoft to help improve our products and services. See the privacy statement for more details.
Contributions and Feedback
We welcome contributions! Please see the contribution guidelines.
For feature requests or bug reports, please file a GitHub Issue.
For general discussion or questions, please use GitHub Discussions.
Code of Conduct
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
License
This project is licensed under the MIT License.