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Cross and native compilation of TFLite for RPI

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Why:

* Describe correct cross and native compilation process for RPI.

This change addresses the need by:

* Updates in instruction for cross compilation.
* Alignement text style across whole instruction.
This commit is contained in:
Marcin Sielski 2020-05-03 13:31:57 +02:00
parent 9c4a71c85c
commit 74b9f9dcc9
1 changed files with 53 additions and 51 deletions
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66
tensorflow/lite/g3doc/guide/build_rpi.md
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@ -5,87 +5,89 @@ Raspberry Pi. If you just want to start using TensorFlow Lite to execute your
models, the fastest option is to install the TensorFlow Lite runtime package as models, the fastest option is to install the TensorFlow Lite runtime package as
shown in the [Python quickstart](python.md). shown in the [Python quickstart](python.md).
Note: This page shows how to compile only the C++ static library for **Note:** This page shows how to compile only the C++ static library for
TensorFlow Lite. Alternative install options include: [install just the Python TensorFlow Lite. Alternative install options include: [install just the Python
interpreter API](python.md) (for inferencing only); [install the full interpreter API](python.md) (for inferencing only); [install the full
TensorFlow package from pip](https://www.tensorflow.org/install/pip); TensorFlow package from pip](https://www.tensorflow.org/install/pip);
or [build the full TensorFlow package]( or [build the full TensorFlow package](
https://www.tensorflow.org/install/source_rpi). https://www.tensorflow.org/install/source_rpi).
## Cross-compile for Raspberry Pi ## Cross-compile for Raspberry Pi
This has been tested on Ubuntu 16.04.3 64bit and TensorFlow devel docker image Instruction has been tested on Ubuntu 16.04.3 64-bit PC (AMD64) and TensorFlow devel
docker image
[tensorflow/tensorflow:nightly-devel](https://hub.docker.com/r/tensorflow/tensorflow/tags/). [tensorflow/tensorflow:nightly-devel](https://hub.docker.com/r/tensorflow/tensorflow/tags/).
To cross compile TensorFlow Lite, first install the toolchain and libs: To cross compile TensorFlow Lite follow the steps:
1. Clone official Raspberry Pi cross-compilation toolchain:
```bash ```bash
sudo apt-get update git clone --depth 1 https://github.com/raspberrypi/tools.git rpi_tools
sudo apt-get install crossbuild-essential-armhf
# The following is only needed for Pi Zero build.
sudo apt-get install crossbuild-essential-armel
``` ```
If you are using Docker, you may not use `sudo`. 2. Clone TensorFlow repository:
Now git-clone the TensorFlow repository ```bash
(`https://github.com/tensorflow/tensorflow`)—if you're using the TensorFlow git clone --depth 1 https://github.com/tensorflow/tensorflow.git tensorflow_src
Docker image, the repo is already provided in `/tensorflow_src/`—and then run
this script at the root of the TensorFlow repository to download all the ```
**Note:** If you're using the TensorFlow Docker image, the repo is already provided in `/tensorflow_src/`.
3. Run following script at the root of the TensorFlow repository to download all the
build dependencies: build dependencies:
```bash ```bash
./tensorflow/lite/tools/make/download_dependencies.sh cd tensor_src && ./tensorflow/lite/tools/make/download_dependencies.sh
``` ```
Note that you only need to do this once. **Note:** You only need to do this once.
You should then be able to compile: 4. To build ARMv7 binary for Raspberry Pi 2, 3 and 4 execute:
To build ARMv7 binary for Raspberry Pi 2, 3 and 4:
```bash ```bash
./tensorflow/lite/tools/make/build_rpi_lib.sh PATH=$PATH:../rpi_tools/arm-bcm2708/arm-rpi-4.9.3-linux-gnueabihf/bin/ ./tensorflow/lite/tools/make/build_rpi_lib.sh
``` ```
This should compile a static library in: **Note:** This should compile a static library in:
`tensorflow/lite/tools/make/gen/rpi_armv7l/lib/libtensorflow-lite.a`. `tensorflow/lite/tools/make/gen/rpi_armv7l/lib/libtensorflow-lite.a`.
To build ARMv6 binary for Raspberry Pi Zero: 5. To build ARMv6 binary for Raspberry Pi Zero execute:
```bash ```bash
./tensorflow/lite/tools/make/build_rpi_lib.sh TARGET_ARCH=armv6 PATH=$PATH:../rpi_tools/arm-bcm2708/arm-rpi-4.9.3-linux-gnueabihf/bin/ ./tensorflow/lite/tools/make/build_rpi_lib.sh TARGET_ARCH=armv6
``` ```
This should compile a static library in: **Note:** This should compile a static library in:
`tensorflow/lite/tools/make/gen/rpi_armv6/lib/libtensorflow-lite.a`. `tensorflow/lite/tools/make/gen/rpi_armv6/lib/libtensorflow-lite.a`.
## Compile natively on Raspberry Pi ## Compile natively on Raspberry Pi
This has been tested on Raspberry Pi 3b, Raspbian GNU/Linux 9.1 (stretch), gcc version 6.3.0 20170516 (Raspbian 6.3.0-18+rpi1). Instruction has been tested on Raspberry Pi 3b, Raspbian GNU/Linux 9.1 (stretch), gcc version 6.3.0 20170516 (Raspbian 6.3.0-18+rpi1):
Log in to your Raspberry Pi and install the toolchain: To natively compile TensorFlow Lite follow the steps:
1. Log in to your Raspberry Pi and install the toolchain:
```bash ```bash
sudo apt-get install build-essential sudo apt-get install build-essential
``` ```
Now git-clone the TensorFlow repository 2. Run following script at the root of the TensorFlow repository to download all the
(`https://github.com/tensorflow/tensorflow`) and run this at the root of build dependencies:
the repository:
```bash ```bash
./tensorflow/lite/tools/make/download_dependencies.sh cd tensor_src && ./tensorflow/lite/tools/make/download_dependencies.sh
``` ```
Note that you only need to do this once. **Note:** You only need to do this once.
You should then be able to compile: 3. You should then be able to compile TensorFlow Lite with:
```bash ```bash
./tensorflow/lite/tools/make/build_rpi_lib.sh ./tensorflow/lite/tools/make/build_rpi_lib.sh
``` ```
This should compile a static library in: **Note:** This should compile a static library in:
`tensorflow/lite/tools/make/gen/lib/rpi_armv7/libtensorflow-lite.a`. `tensorflow/lite/tools/make/gen/lib/rpi_armv7/libtensorflow-lite.a`.