Examples

This directory contains scripts and other helper utilities to illustrate an end-to-end workflow to run a Core ML delegated torch.nn.module with the ExecuTorch runtime.

Directory structure

coreml
├── scripts             # Scripts to build the runner.
├── executor_runner     # The runner implementation.
└── README.md           # This file.

Using the examples

We will walk through an example model to generate a Core ML delegated binary file from a python torch.nn.module then we will use the coreml/executor_runner to run the exported binary file.

Following the setup guide in Setting Up ExecuTorch you should be able to get the basic development environment for ExecuTorch working.
Run install_requirements.sh to install dependencies required by the Core ML backend.

cd executorch

./backends/apple/coreml/scripts/install_requirements.sh

Run the export script to generate a Core ML delegated binary file.

cd executorch

# To get a list of example models
python3 -m examples.portable.scripts.export -h

# Generates ./add_coreml_all.pte file if successful.
python3 -m examples.apple.coreml.scripts.export_and_delegate --model_name add

Once we have the Core ML delegated model binary (pte) file, then let's run it with the ExecuTorch runtime using the coreml_executor_runner.

cd executorch

# Builds the Core ML executor runner. Generates ./coreml_executor_runner if successful.
./examples/apple/coreml/scripts/build_executor_runner.sh

# Run the Core ML delegate model.
./coreml_executor_runner --model_path add_coreml_all.pte

Frequently encountered errors and resolution.

The examples.apple.coreml.scripts.export_and_delegate could fail if the model is not supported by the Core ML backend. The following models from the examples models list ( python3 -m examples.portable.scripts.export -h)are currently supported by the Core ML backend.

add
add_mul
ic4
linear
mul
mv2
mv3
resnet18
resnet50
softmax
vit
w2l

If you encountered any bugs or issues following this tutorial please file a bug/issue here with tag #coreml.