ExecuTorch Setup

Set up ExecuTorch

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices; including wearables, embedded devices, and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of PyTorch models to edge devices. You can learn more by reading the ExecuTorch Overview .

The best practice is to generate an isolated Python environment in which to install your ExecuTorch dependencies. We provide instructions for both a Python virtual environment and a Conda virtual environment, but you only need one.

Option 1: Create a Python virtual environment

    

        
        
            python3.10 -m venv executorch
source executorch/bin/activate
        
    

The prompt of your terminal has (executorch) as a prefix to indicate the virtual environment is active.

Option 2: Create a Conda virtual environment

Install Miniconda on your development machine by following the Installing conda instructions.

Once conda is installed create the environment:

    

        
        
            conda create -yn executorch python=3.10.0
conda activate executorch
        
    

Clone ExecuTorch and install the required dependencies

From within the conda environment, run the commands below to download the ExecuTorch repository and install the required packages:

    

        
        
            # Clone the ExecuTorch repo from GitHub
git clone https://github.com/pytorch/executorch.git
cd executorch

# Update and pull submodules
git submodule sync
git submodule update --init

# Install ExecuTorch pip package and its dependencies, as well as
# development tools like CMake.
./install_requirements.sh --pybind xnnpack

# Install a few more dependencies
./examples/models/llama2/install_requirements.sh
        
    

You are now ready to start building the application.