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Building on Jetson
==================
1. Install JetPack
------------------
JetPack includes the collection of CUDA-related libraries that is required to run PyTorch with CUDA.
Please refer to https://developer.nvidia.com/embedded/learn/get-started-jetson-agx-orin-devkit for the up-to-date instruction.
.. code-block::
sudo bash -c 'echo "deb https://repo.download.nvidia.com/jetson/common r34.1 main" >> /etc/apt/sources.list.d/nvidia-l4t-apt-source.list'
sudo bash -c 'echo "deb https://repo.download.nvidia.com/jetson/t234 r34.1 main" >> /etc/apt/sources.list.d/nvidia-l4t-apt-source.list'
sudo apt update
sudo apt dist-upgrade
# REBOOT
sudo apt install nvidia-jetpack
Checking the versions
~~~~~~~~~~~~~~~~~~~~~
To check the version installed you can use the following commands;
.. code-block::
# JetPack
$ apt list --installed | grep nvidia-jetpack
nvidia-jetpack-dev/stable,now 5.0.1-b118 arm64 [installed,automatic]
nvidia-jetpack-runtime/stable,now 5.0.1-b118 arm64 [installed,automatic]
nvidia-jetpack/stable,now 5.0.1-b118 arm64 [installed]
# CUDA
$ apt list --installed | grep cuda-toolkit
cuda-toolkit-11-4-config-common/stable,now 11.4.243-1 all [installed,automatic]
cuda-toolkit-11-4/stable,now 11.4.14-1 arm64 [installed,automatic]
cuda-toolkit-11-config-common/stable,now 11.4.243-1 all [installed,automatic]
cuda-toolkit-config-common/stable,now 11.4.243-1 all [installed,automatic]
# cuDNN
$ apt list --installed | grep cudnn
libcudnn8-dev/stable,now 8.3.2.49-1+cuda11.4 arm64 [installed,automatic]
libcudnn8-samples/stable,now 8.3.2.49-1+cuda11.4 arm64 [installed,automatic]
libcudnn8/stable,now 8.3.2.49-1+cuda11.4 arm64 [installed,automatic]
nvidia-cudnn8-dev/stable,now 5.0.1-b118 arm64 [installed,automatic]
nvidia-cudnn8-runtime/stable,now 5.0.1-b118 arm64 [installed,automatic]
.. image:: https://download.pytorch.org/torchaudio/doc-assets/jetson-package-versions.png
:width: 360px
2. [Optional] Install jtop
--------------------------
Since Tegra GPUs are not supported by ``nvidia-smi`` command, it is recommended to isntall ``jtop``.
Only super-use can install ``jtop``. So make sure to add ``-U``, so that running ``jtop`` won't require super-user priviledge.
3. Install ``pip`` in user env
------------------------------
By default, ``pip`` / ``pip3`` commands use the ones from system directory ``/usr/bin/``, and its ``site-packages`` directory is protected and cannot be modified without ``sudo``.
One way to workaround this is to install ``pip`` in user directory.
https://forums.developer.nvidia.com/t/python-3-module-install-folder/181321
.. code-block::
wget https://bootstrap.pypa.io/get-pip.py
python get-pip.py --user
After this verify that ``pip`` command is pointing the one in user directory.
.. code-block::
$ which pip
/home/USER/.local/bin/pip
4. Install PyTorch
------------------
As of PyTorch 1.13 and torchaudio 0.13, there is no official pre-built binaries for Linux ARM64. Nidia provides custom pre-built binaries for PyTorch, which works with specific JetPack.
Please refer to https://docs.nvidia.com/deeplearning/frameworks/install-pytorch-jetson-platform/index.html for up-to-date instruction on how to install PyTorch.
.. code-block::
$ package=torch-1.13.0a0+340c4120.nv22.06-cp38-cp38-linux_aarch64.whl
$ wget "https://developer.download.nvidia.com/compute/redist/jp/v50/pytorch/${package}"
$ pip install --no-cache "${package}"
Verify the installation by checking the version and CUDA device accessibility.
.. code-block::
$ python -c '
import torch
print(torch.__version__)
print(torch.cuda.is_available())
print(torch.empty((1, 2), device=torch.device("cuda")))
'
1.13.0a0+410ce96a.nv22.12
True
tensor([[0., 0.]], device='cuda:0')
.. image:: https://download.pytorch.org/torchaudio/doc-assets/jetson-torch.png
:width: 360px
5. Build TorchAudio
-------------------
1. Install build tools
~~~~~~~~~~~~~~~~~~~~~~
.. code-block::
pip install cmake ninja
2. Install dependencies
~~~~~~~~~~~~~~~~~~~~~~~
.. code-block::
sudo apt install ffmpeg libavformat-dev libavcodec-dev libavutil-dev libavdevice-dev libavfilter-dev
3. Build TorchAudio
~~~~~~~~~~~~~~~~~~~
.. code-block::
git clone https://github.com/pytorch/audio
cd audio
USE_CUDA=1 pip install -v -e . --no-use-pep517
4. Check the installation
~~~~~~~~~~~~~~~~~~~~~~~~~
.. code-block::
import torchaudio
print(torchaudio.__version__)
torchaudio.utils.ffmpeg_utils.get_build_config()
.. code-block::
2.0.0a0+2ead941
--prefix=/usr --extra-version=0ubuntu0.1 --toolchain=hardened --libdir=/usr/lib/aarch64-linux-gnu --incdir=/usr/include/aarch64-linux-gnu --arch=arm64 --enable-gpl --disable-stripping --enable-avresample --disable-filter=resample --enable-avisynth --enable-gnutls --enable-ladspa --enable-libaom --enable-libass --enable-libbluray --enable-libbs2b --enable-libcaca --enable-libcdio --enable-libcodec2 --enable-libflite --enable-libfontconfig --enable-libfreetype --enable-libfribidi --enable-libgme --enable-libgsm --enable-libjack --enable-libmp3lame --enable-libmysofa --enable-libopenjpeg --enable-libopenmpt --enable-libopus --enable-libpulse --enable-librsvg --enable-librubberband --enable-libshine --enable-libsnappy --enable-libsoxr --enable-libspeex --enable-libssh --enable-libtheora --enable-libtwolame --enable-libvidstab --enable-libvorbis --enable-libvpx --enable-libwavpack --enable-libwebp --enable-libx265 --enable-libxml2 --enable-libxvid --enable-libzmq --enable-libzvbi --enable-lv2 --enable-omx --enable-openal --enable-opencl --enable-opengl --enable-sdl2 --enable-libdc1394 --enable-libdrm --enable-libiec61883 --enable-chromaprint --enable-frei0r --enable-libx264 --enable-shared
.. image:: https://download.pytorch.org/torchaudio/doc-assets/jetson-verify-build.png
:width: 360px
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