Clone RPI docs from the TF official documentation (#20)

README.md

@@ -47,6 +47,9 @@ Want to add your own project to this list? It's easy: check out
 
 * [**ppc64le Builds**](ppc64le_builds): Dockerfiles and wheel build scripts for
   building TF on ppc64le.
+* [**Raspberry Pi Builds**](raspberry_pi_builds): TensorFlow's old official docs
+  for building on Raspberry Pi. Needs an owner.
+
 
 ### WIP / Other
 

raspberry_pi_builds/README.md

+# Raspberry Pi Builds
+
+TensorFlow's old official docs for building on Raspberry Pi. Needs an owner.
+
+Maintainer: @angerson (TensorFlow, SIG Build)
+
+* * *
+
+**Important: TensorFlow for the Raspberry Pi is no longer supported by the
+TensorFlow team. (last tested on 2.3.0rc2). See the [Build TensorFlow Lite for
+Raspberry Pi](https://www.tensorflow.org/lite/guide/build_rpi) guide.**
+
+**This guide is a mirror of the old official documentation and may not work. If
+you'd like to own this and keep it up-to-date, please file a PR!**
+
+# Build from source for the Raspberry Pi
+
+This guide builds a TensorFlow package for a
+[Raspberry Pi](https://www.raspberrypi.org/) device running
+[Raspbian 9.0](https://www.raspberrypi.org/downloads/raspbian/).
+While the instructions might work for other Raspberry Pi variants, it is only
+tested and supported for this configuration.
+
+We recommend *cross-compiling* the TensorFlow Raspbian package.
+Cross-compilation is using a different platform to build the package than deploy
+to. Instead of using the Raspberry Pi's limited RAM and comparatively slow
+processor, it's easier to build TensorFlow on a more powerful host machine
+running Linux, macOS, or Windows.
+
+## Setup for host
+
+### Install Docker
+
+To simplify dependency management, the build script uses
+[Docker](https://docs.docker.com/install/) to create a virtual Linux development
+environment for compilation. Verify your Docker install by executing: `docker
+run --rm hello-world`
+
+### Download the TensorFlow source code
+
+Use [Git](https://git-scm.com/) to clone the
+[TensorFlow repository](https://github.com/tensorflow/tensorflow):
+
+```
+git clone https://github.com/tensorflow/tensorflow.git
+cd tensorflow
+```
+
+The repo defaults to the `master` development branch. You can also checkout a
+[release branch](https://github.com/tensorflow/tensorflow/releases)
+to build:
+
+```
+git checkout <branch_name>  # r1.9, r1.10, etc.
+```
+
+Key Point: If you're having build problems on the latest development branch, try
+a release branch that is known to work.
+
+
+## Build from source
+
+Cross-compile the TensorFlow source code to build a Python *pip* package with
+ARMv7 [NEON instructions](https://developer.arm.com/technologies/neon) that
+works on Raspberry Pi 2, 3 and 4 devices. The build script launches a Docker
+container for compilation. You can also build ARM 64-bit binary (aarch64) by
+providing `AARCH64` parameter to the `build_raspberry_pi.sh` script. Choose
+among Python 3.8, Python 3.7, Python 3.5 and Python 2.7 for the target package:
+
+### Python 3.5
+
+```
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON3 \
+    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh
+```
+
+### Python 3.7
+
+```
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON37 \
+    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh
+```
+
+### Python 3.8 (64bit)
+
+```
+tensorflow/tools/ci_build/ci_build.sh PI-PYTHON38 \
+    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh AARCH64
+```
+
+### Python 2.7
+
+```
+tensorflow/tools/ci_build/ci_build.sh PI \
+    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh
+```
+
+To build a package that supports all Raspberry Pi devices—including the Pi 1 and
+Zero—pass the `PI_ONE` argument, for example:
+
+```
+tensorflow/tools/ci_build/ci_build.sh PI \
+    tensorflow/tools/ci_build/pi/build_raspberry_pi.sh PI_ONE
+```
+
+When the build finishes (~30 minutes), a `.whl` package file is created in the
+output-artifacts directory of the host's source tree. Copy the wheel file to the
+Raspberry Pi and install with `pip`:
+
+```
+pip install tensorflow-<version>-cp35-none-linux_armv7l.whl
+```
+
+Success: TensorFlow is now installed on Raspbian.