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TensorFlow for Arm
| Date | Stars |
|---|---|
| 2026-07-24 | 1053 |
| 2026-07-25 | 1053 |
| 2026-07-28 | 1053 |
| 2026-07-30 | 1053 |
| 2026-08-06 | 1053 |
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# Tensorflow-on-arm Inspired by [tensorflow-on-raspberry-pi](https://github.com/samjabrahams/tensorflow-on-raspberry-pi). Tool to compile tensorflow for ARM. ## Dependencies ```shell apt-get install openjdk-8-jdk automake autoconf apt-get install curl zip unzip libtool swig libpng-dev zlib1g-dev pkg-config git g++ wget xz-utils # For python2.7 apt-get install python-numpy python-dev python-pip python-mock # If using a virtual environment, omit the --user argument pip install -U --user keras_applications==1.0.8 --no-deps pip install -U --user keras_preprocessing==1.1.0 --no-deps # For python3 apt-get install python3-numpy python3-dev python3-pip python3-mock # If using a virtual environment, omit the --user argument pip3 install -U --user keras_applications==1.0.8 --no-deps pip3 install -U --user keras_preprocessing==1.1.0 --no-deps pip3 install portpicker ``` ## TensorFlow on Raspberry Pi ### It's officially supported! Python wheels for TensorFlow are [officially supported](https://medium.com/tensorflow/tensorflow-1-9-officially-supports-the-raspberry-pi-b91669b0aa0). This repository also maintains up-to-date TensorFlow wheels for Raspberry Pi. ### Installation [Check out the official TensorFlow website for more information.](https://www.tensorflow.org/install/install_raspbian) ## Cross-compilation Make you sure add the ARM architecture to your package manager, see how to add it in Debian flavors: ```shell dpkg --add-architecture armhf echo "deb [arch=armhf] http://httpredir.debian.org/debian/ buster main contrib non-free" >> /etc/apt/sources.list ``` If you want compile Python support: ```shell # For python2.7 apt-get install libpython-all-dev:armhf # For python3 apt-get install libpython3-all-dev:armhf ``` ### Using Docker #### Python 3.7 ```shell cd build_tensorflow/ docker build -t tf-arm -f Dockerfile . docker run -it -v /tmp/tensorflow_pkg/:/tmp/tensorflow_pkg/ --env TF_PYTHON_VERSION=3.7 tf-arm ./build_tensorflow.sh configs/<conf-name> # rpi.conf, rk3399.conf ... ``` #### Python 3.8 ```shell cd build_tensorflow/ docker build -t tf-arm -f Dockerfile.bullseye . docker run -it -v /tmp/tensorflow_pkg/:/tmp/tensorflow_pkg/ --env TF_PYTHON_VERSION=3.8 tf-arm ./build_tensorflow.sh configs/<conf-name> # rpi.conf, rk3399.conf ... ``` ## Edit tweaks like Bazel resources, board model, and others. See configuration file examples in: build_tensorflow/configs/ ## Finally, compile TensorFlow. ```shell cd build_tensorflow/ chmod +x build_tensorflow.sh TF_PYTHON_VERSION=3.5 ./build_tensorflow.sh <path-of-config> [noclean] # The optional [noclean] argument omits 'bazel clean' before building for debugging purposes. # If no output errors, the pip package will be in the directory: /tmp/tensorflow_pkg/ ```
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1a9dbb991ef2c520, topic:tensorflow