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 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 --model_name add

Run the binary file using the coreml_executor_runner.

cd executorch

# Install requirements needed to run the example runner
./backends/apple/coreml/scripts/install_requirements.sh

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

# Run the delegated model.
./coreml_executor_runner --model_path add_coreml_all.pte

Frequently encountered errors and resolution.

The examples.apple.coreml.scripts.export 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
dl3
edsr
emformer_join
emformer_predict
emformer_transcribe
ic3
ic4
linear
llama2
llava_encoder
mobilebert
mul
mv2
mv2_untrained
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.