Set up the ExecuTorch build environment

For macOS: build ExecuTorch in a Docker container

On macOS, it’s easiest to build ExecuTorch in an Ubuntu container. This keeps your toolchain consistent with the rest of the Learning Path and avoids gaps in macOS-native cross-compilers (for example, the Arm GNU Toolchain doesn’t provide an “AArch64 GNU/Linux target” for macOS).

This container isn’t part of the runtime deployment. It’s a build environment that produces the artifacts you later move onto the FRDM i.MX 93:

• Prebuilt ExecuTorch libraries you link into Cortex-M33 firmware
• .pte model files compiled for Ethos-U65

Keeping this step reproducible helps you focus on the actual bring-up milestone: booting custom firmware on Cortex-M33 and using Ethos-U65 for inference.

Start by installing and launching Docker Desktop .

Next, create a working directory for your container build:

    

        
        
mkdir ubuntu-24-container

    

Now create a Dockerfile and switch into the directory:

    

        
        
cd ubuntu-24-container
touch Dockerfile

    

Add the following content to your Dockerfile to install a few basic tools in the image:

    

        
        
FROM ubuntu:24.04

ENV DEBIAN_FRONTEND=noninteractive

RUN apt update -y && \
    apt install -y \
    software-properties-common \
    curl vim git

    

The ubuntu:24.04 container image includes Python 3.12, which you use later in this Learning Path.

Build the container image:

    

        
        
docker build -t ubuntu-24-container .

    

Run the container and open an interactive shell:

    

        
        docker run -it ubuntu-24-container /bin/bash
__output__# Output will be the Docker container prompt
__output__root@<CONTAINER ID>:/#

        
    

If you already created a container before, reuse it instead of creating a new one.

First, list your containers to find the container ID:

    

        
        docker ps -a
__output__# Output
__output__CONTAINER ID  IMAGE                    COMMAND      CREATED        STATUS                       PORTS  NAMES
__output__0123456789ab  ubuntu-24-container  "/bin/bash"  27 hours ago   Exited (255) 59 minutes ago.        container_name

        
    

Then start the container and attach a shell:

    

        
        
docker start 0123456789ab
docker exec -it 0123456789ab /bin/bash

    

Once you’re inside the container, move to your home directory:

    

        
        
cd /root

    

Install dependencies

Install the packages ExecuTorch needs to build. If you’re not running as root, prefix the commands with sudo.

    

        
        
apt update
apt install -y \
  python-is-python3 python3.12-dev python3.12-venv python3-pip \
  gcc g++ \
  make cmake \
  build-essential \
  ninja-build \
  libboost-all-dev

    

Create a Python virtual environment

Create and activate a virtual environment so your Python packages stay scoped to this project:

    

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

        
    

Get the ExecuTorch source code

Clone ExecuTorch and initialize its submodules:

    

        
        
git clone https://github.com/pytorch/executorch.git
cd executorch
git fetch --tags
git checkout c70a742344e30158dc370d7d35d60ed07660fee0
git submodule sync
git submodule update --init --recursive

    

What you’ve learned and what’s next

In this section you’ve:

• Set up an Ubuntu 24.04 Docker container for building ExecuTorch (macOS users)
• Installed required dependencies and created a Python virtual environment
• Cloned the ExecuTorch repository and checked out the correct version

With your build environment configured and the ExecuTorch source checked out, the next step is building and installing the ExecuTorch package.