pytorch/ios/TestApp

TestApp

The TestApp is currently being used as a dummy app by Circle CI for nightly jobs. The challenge comes when testing the arm64 build as we don't have a way to code-sign our TestApp. This is where Fastlane came to rescue. Fastlane is a trendy automation tool for building and managing iOS applications. It also works seamlessly with Circle CI. We are going to leverage the import_certificate action, which can install developer certificates on CI machines. See Fastfile for more details.

For simulator build, we run unit tests as the last step of our CI workflow. Those unit tests can also be run manually via the fastlane scan command.

Run Simulator Test Locally

Follow these steps if you want to run the test locally.

1. Checkout PyTorch repo including all submodules

2. Build PyTorch for ios

USE_COREML_DELEGATE=1 IOS_PLATFORM=SIMULATOR ./scripts/build_ios.sh

3. Generate on-the-fly test models

python test/mobile/model_test/gen_test_model.py ios-test

You need to install regular PyTorch on your local machine to run this script. Check https://github.com/pytorch/pytorch/tree/master/test/mobile/model_test#diagnose-failed-test to learn more.

4. Create XCode project (for lite interpreter)

cd ios/TestApp/benchmark
ruby setup.rb --lite 1

5. Open the generated TestApp/TestApp.xcodeproj in XCode and run simulator test.

Re-generate All Test Models

1. Make sure PyTorch (not PyTorch for iOS) is installed See https://pytorch.org/get-started/locally/

2. Re-generate models for operator test

python test/mobile/model_test/gen_test_model.py ios
python test/mobile/model_test/gen_test_model.py ios-test

3. Re-generate Core ML model

cd ios/TestApp/benchmark; python coreml_backend.py

Debug Test Failures

Make sure all models are generated. See https://github.com/pytorch/pytorch/tree/master/test/mobile/model_test to learn more.

There's no debug information in simulator test (project TestAppTests). You can copy the failed test code to TestApp/TestApp/ViewController.mm and debug in the main TestApp.

Benchmark

The benchmark folder contains two scripts that help you setup the benchmark project. The setup.rb does the heavy-lifting jobs of setting up the XCode project, whereas the trace_model.py is a Python script that you can tweak to generate your model for benchmarking. Simply follow the steps below to setup the project

1. In the PyTorch root directory, run IOS_ARCH=arm64 ./scripts/build_ios.sh to generate the custom build from Master branch
2. Navigate to the benchmark folder, run python trace_model.py to generate your model.
3. In the same directory, open config.json. Those are the input parameters you can tweak.
4. Again, in the same directory, run ruby setup.rb to setup the XCode project.
5. Open the TestApp.xcodeproj, you're ready to go.

The benchmark code is written in C++, you can use UI_LOG to visualize the log. See benchmark.mm for more details.