Merge pull request #38666 from marcin-sielski:master

PiperOrigin-RevId: 312420674 Change-Id: Ia8cde2c26dbb2bc56ff28dcb549d94ce4fd6d647
2020-05-19 22:23:24 -07:00 · 2020-05-19 22:23:24 -07:00 · e3eb5101bb
commit e3eb5101bb
parent ff99778343 4541955925
2 changed files with 68 additions and 57 deletions
--- a/tensorflow/lite/g3doc/guide/build_rpi.md
+++ b/tensorflow/lite/g3doc/guide/build_rpi.md
@ -5,87 +5,98 @@ 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
 shown in the [Python quickstart](python.md).

-Note: This page shows how to compile only the C++ static library for
-TensorFlow Lite. Alternative install options include: [install just the Python
-interpreter API](python.md) (for inferencing only); [install the full
-TensorFlow package from pip](https://www.tensorflow.org/install/pip);
-or [build the full TensorFlow package](
-https://www.tensorflow.org/install/source_rpi).
-
+**Note:** This page shows how to compile only the C++ static library for
+TensorFlow Lite. Alternative install options include:
+[install just the Python interpreter API](python.md) (for inferencing only);
+[install the full TensorFlow package from pip](https://www.tensorflow.org/install/pip);
+or
+[build the full TensorFlow package](https://www.tensorflow.org/install/source_rpi).

 ## 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/).

-To cross compile TensorFlow Lite, first install the toolchain and libs:
+To cross compile TensorFlow Lite follow the steps:

-```bash
-sudo apt-get update
-sudo apt-get install crossbuild-essential-armhf
-# The following is only needed for Pi Zero build.
-sudo apt-get install crossbuild-essential-armel
-```
+1.  Clone official Raspberry Pi cross-compilation toolchain:

-If you are using Docker, you may not use `sudo`.
+    ```bash
+    git clone https://github.com/raspberrypi/tools.git rpi_tools
+    ```

-Now git-clone the TensorFlow repository
-(`https://github.com/tensorflow/tensorflow`)—if you're using the TensorFlow
-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
-build dependencies:
+2.  Clone TensorFlow repository:

-```bash
-./tensorflow/lite/tools/make/download_dependencies.sh
-```
+    ```bash
+    git clone https://github.com/tensorflow/tensorflow.git tensorflow_src

-Note that you only need to do this once.
+    ```

-You should then be able to compile:
+    **Note:** If you're using the TensorFlow Docker image, the repo is already
+    provided in `/tensorflow_src/`.

-To build ARMv7 binary for Raspberry Pi 2, 3 and 4:
+3.  Run following script at the root of the TensorFlow repository to download
+    all the build dependencies:

-```bash
-./tensorflow/lite/tools/make/build_rpi_lib.sh
-```
+    ```bash
+    cd tensorflow_src && ./tensorflow/lite/tools/make/download_dependencies.sh
+    ```

-This should compile a static library in:
-`tensorflow/lite/tools/make/gen/rpi_armv7l/lib/libtensorflow-lite.a`.
+    **Note:** You only need to do this once.

-To build ARMv6 binary for Raspberry Pi Zero:
+4.  To build ARMv7 binary for Raspberry Pi 2, 3 and 4 execute:

-```bash
-./tensorflow/lite/tools/make/build_rpi_lib.sh TARGET_ARCH=armv6
-```
+    ```bash
+    PATH=../rpi_tools/arm-bcm2708/arm-rpi-4.9.3-linux-gnueabihf/bin:$PATH ./tensorflow/lite/tools/make/build_rpi_lib.sh
+    ```

-This should compile a static library in:
-`tensorflow/lite/tools/make/gen/rpi_armv6/lib/libtensorflow-lite.a`.
+    **Note:** This should compile a static library in:
+    `tensorflow/lite/tools/make/gen/rpi_armv7l/lib/libtensorflow-lite.a`.
+
+5.  To build ARMv6 binary for Raspberry Pi Zero execute:
+
+    ```bash
+    PATH=../rpi_tools/arm-bcm2708/arm-rpi-4.9.3-linux-gnueabihf/bin:$PATH ./tensorflow/lite/tools/make/build_rpi_lib.sh TARGET_ARCH=armv6
+    ```
+
+    **Note:** This should compile a static library in:
+    `tensorflow/lite/tools/make/gen/rpi_armv6/lib/libtensorflow-lite.a`.

 ## 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 Zero, Raspbian GNU/Linux 10
+(buster), gcc version 8.3.0 (Raspbian 8.3.0-6+rpi1):

-Log in to your Raspberry Pi and install the toolchain:
+To natively compile TensorFlow Lite follow the steps:

-```bash
-sudo apt-get install build-essential
-```
+1.  Log in to your Raspberry Pi and install the toolchain:

-Now git-clone the TensorFlow repository
-(`https://github.com/tensorflow/tensorflow`) and run this at the root of
-the repository:
+    ```bash
+    sudo apt-get install build-essential
+    ```

-```bash
-./tensorflow/lite/tools/make/download_dependencies.sh
-```
+2.  Clone TensorFlow repository:

-Note that you only need to do this once.
+    ```bash
+    git clone https://github.com/tensorflow/tensorflow.git tensorflow_src

-You should then be able to compile:
+    ```

-```bash
-./tensorflow/lite/tools/make/build_rpi_lib.sh
-```
+3.  Run following script at the root of the TensorFlow repository to download
+    all the build dependencies:

-This should compile a static library in:
-`tensorflow/lite/tools/make/gen/lib/rpi_armv7/libtensorflow-lite.a`.
+    ```bash
+    cd tensorflow_src && ./tensorflow/lite/tools/make/download_dependencies.sh
+    ```
+
+    **Note:** You only need to do this once.
+
+4.  You should then be able to compile TensorFlow Lite with:
+
+    ```bash
+    ./tensorflow/lite/tools/make/build_rpi_lib.sh
+    ```
+
+    **Note:** This should compile a static library in:
+    `tensorflow/lite/tools/make/gen/lib/rpi_armv6/libtensorflow-lite.a`.
--- a/tensorflow/lite/tools/make/targets/rpi_makefile.inc
+++ b/tensorflow/lite/tools/make/targets/rpi_makefile.inc
@ -32,7 +32,7 @@ ifeq ($(TARGET),rpi)
  # TODO(petewarden) In the future, we'll want to use OpenBLAS as a faster
  # alternative to Eigen on non-NEON ARM hardware like armv6.
  ifeq ($(TARGET_ARCH), armv6)
-    TARGET_TOOLCHAIN_PREFIX := arm-linux-gnueabi-
+    TARGET_TOOLCHAIN_PREFIX := arm-linux-gnueabihf-
    CXXFLAGS += \
      -march=armv6 \
      -mfpu=vfp \