ExecuTorch in Portable Mode

This dir contains demos to illustrate an end-to-end workflow of using ExecuTorch in portable mode.

Directory structure

examples/portable
├── scripts                           # Python scripts to illustrate export workflow
│   ├── export.py
│   └── export_and_delegate.py
├── custom_ops                        # Contains examples to register custom operators into PyTorch as well as register its kernels into ExecuTorch runtime
├── executor_runner                   # Contains an example C++ wrapper around the ExecuTorch runtime
└── README.md                         # This file

Using portable mode

We will walk through an example model to generate a .pte file in portable mode from a python torch.nn.module from the models/ directory using scripts in the portable/scripts directory. Then we will run on the .pte model on the ExecuTorch runtime. For that we will use executor_runner.

1. Following the setup guide in Setting up ExecuTorch you should be able to get the basic development environment for ExecuTorch working.

2. Using the script portable/scripts/export.py generate a model binary file by selecting a model name from the list of available models in the models dir.

cd executorch # To the top level dir

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

# To generate a specific pte model
python3 -m examples.portable.scripts.export --model_name="mv2" # for MobileNetv2

# This should generate ./mv2.pte file, if successful.

Use -h (or --help) to see all the supported models.

3. Once we have the model binary (.pte) file, then let's run it with ExecuTorch runtime using the executor_runner.

buck2 run examples/portable/executor_runner:executor_runner -- --model_path ./mv2.pte

Custom Operator Registration

Explore the demos in the custom_ops/ directory to learn how to register custom operators into ExecuTorch as well as register its kernels into ExecuTorch runtime.