TLDR: 🔗

We used the raspbian image available here to compile a version of Pytorch for the Raspberry Pi. This is an armv7l image that has been compiled with NEON optimisations and NNPACK / QNNPACK, allowing it to run decently fast on the resource constrained RPi.

The compiled pytorch / torchvision wheels can be found here.

More information about the QEMU user-mode emulation used in the docker image can be found [here] ( )

Build Process: 🔗

1. Install required dependencies on the host:

   sudo apt-get update && sudo apt-get install qemu qemu-user-static binfmt-support

2. Run the docker container:

   $ docker run -it --name pytorch_builder choonkiatlee/raspbian:build

3. Install dependencies in the container and collect pytorch sources

   
   ####################### In Docker Container #######################
   root@b0571199906e:/# apt-get update && apt-get install -y python3-cffi python3-numpy libatlas-base-dev
   
   root@b0571199906e:/# echo "[global]
   root@b0571199906e:/# extra-index-url=https://www.piwheels.org/simple" >> /etc/pip.conf
   
   root@b0571199906e:/# pip3 install cython wheel pyyaml pillow
   
   root@b0571199906e:/# git clone --recursive https://github.com/pytorch/pytorch
   
   root@b0571199906e:/# cd pytorch
   
   root@b0571199906e:/# git checkout v1.4.0
   
   root@b0571199906e:/# git submodule sync --recursive
   root@b0571199906e:/# git submodule update --init --recursive
   
   # Fix from: https://github.com/pytorch/pytorch/issues/22564
   root@b0571199906e:/# git submodule update --remote third_party/protobuf
   

4. Configure build options and build pytorch from source:

   root@b0571199906e:/# export USE_CUDA=0
   root@b0571199906e:/# export USE_CUDNN=0
   root@b0571199906e:/# export USE_MKLDNN=0
   
   root@b0571199906e:/# export USE_METAL=0
   root@b0571199906e:/# export USE_NCCL=OFF
   
   root@b0571199906e:/# export USE_NNPACK=1
   root@b0571199906e:/# export USE_QNNPACK=1
   root@b0571199906e:/# export USE_DISTRIBUTED=0
   root@b0571199906e:/# export BUILD_TEST=0
   
   # Use the number of CPUs that you have available on the host machine
   root@b0571199906e:/# export MAX_JOBS=2 
   
   # Enable NEON optimisations
   root@b0571199906e:/# export CFLAGS="-mfpu=neon -D__NEON__" 
   
   root@b0571199906e:/# python3 setup.py bdist_wheel
   

5. Copy out the built wheel

   ####################### In Host #######################
   $ docker cp pytorch_builder:/pytorch/dist/. .

6. Optional: Build torchvision

   $ docker run -it --name pytorch_builder choonkiatlee/raspbian:latest
   
   ####################### In Docker Container #######################
   root@b0571199906e:/# git clone https://github.com/pytorch/vision.git
   root@b0571199906e:/# cd vision
   
   # Remember to install the built pytorch wheel from before
   root@b0571199906e:/# pip3 install /pytorch/dist/.
   root@b0571199906e:/# python3 setup.py bdist_wheel
   
   ####################### In Host #######################
   $ docker cp pytorch_builder:/vision/dist/. .

7. Bonus! Easier method:

   sudo apt-get update && sudo apt-get install qemu-user-static qemu binfmt-support
   
   # Clone the repo to get the above commands as a single script
   git clone https://github.com/choonkiatlee/pi-torch.git
   
   # Override the entrypoint
   docker create --name pytorch_builder choonkiatlee/raspbian:build qemu-arm-static /bin/bash install_pytorch.sh
   
   # Copy the build script onto the docker container and run the container
   docker cp pi-torch/install_pytorch.sh pytorch_builder:/install_pytorch.sh
   docker start pytorch_builder
   
   # Attach to the container to see the output
   docker attach pytorch_builder