TensorFlow wheels for Raspberry Pi
Find your operating system and TensorFlow version in the table below. Follow the instructions in the provided guide.
Roadmap.
| Operating system | TF 2.8.0 | TF 2.7.0 | TF 2.6.0 | TF 2.5.1 | TF 2.5.0 | TF 2.4.1 | TF 2.4.0 | TF 2.3.1 | TF 2.3.0 | TF 2.2.0 | TF 2.1.0 | TF 1.15.2 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Raspberry Pi 32-bit Buster | Wheel C API Guide |
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| Raspberry Pi 64-bit Buster | Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
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| Raspberry Pi 64-bit Bullseye | Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
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| Raspberry Pi Ubuntu 18.04 | Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
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| Raspberry Pi Ubuntu 20.04 | Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
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Wheel C API Guide |
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| Jetson Nano JetPack 4.6 | Wheel C API Guide |
Wheel C API Guide |
Wheel C API Guide |
Buster 32-bit OS
As the massive TensorFlow evolves, building it on a simple 32-bit machine is getting more and more difficult. Many tricks and workarounds are now required to compile bazel and TensorFlow. That's why the last version of TensorFlow for a 32-bit OS, is the 2.2.0 release.
Buster 64-bit OS
TensorFlow 2.7 and higher relies on libclang 9.0.1. There is no distribution available for Debian 10. That's why there is only a TensorFlow 2.7+ installation for Debian 11, Bullseye. You could probably install libclang 9.0.1 on your Buster RPi from scratch so that you can then install TensorFlow. Be aware, the clang build takes huge resources, over 5 GB. It's better to switch to Bullseye and have TensorFlow up and running in half an hour.
Ubuntu 18.04
TensorFlow 2.5.0 depends on h5py version 3.1.0. Unfortunately, the h5py version 3.1.0 cannot be easily installed on Ubuntu 18.04, or to be more precise, on an aarch64 with Python 3.6. See #1760. That's why we don't have a wheel for Ubuntu 18.04. Use TensorFlow 2.4.1 or switch to Ubuntu 20.04.
Jetson Nano
TensorFlow 2.5, 2.6 and 2.7 depend on CUDA 11.0 and cuDNN version 8.0.4, both not yet available for the Jetson Nano. A workaround is cumbersome and probably not very reliable. Better to wait for the new announced JetPack to be released with the required versions of CUDA and cuDNN. Continue to use TensorFlow 2.4.1 for now.
