Merge pull request #38666 from marcin-sielski:master

PiperOrigin-RevId: 312420674
Change-Id: Ia8cde2c26dbb2bc56ff28dcb549d94ce4fd6d647

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
+**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:
-interpreter API](python.md) (for inferencing only); [install the full
+[install just the Python interpreter API](python.md) (for inferencing only);
-TensorFlow package from pip](https://www.tensorflow.org/install/pip);
+[install the full TensorFlow package from pip](https://www.tensorflow.org/install/pip);
-or [build the full TensorFlow package](
+or
-https://www.tensorflow.org/install/source_rpi).
+[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:
+
+1.  Clone official Raspberry Pi cross-compilation toolchain:
 
     ```bash
-sudo apt-get update
+    git clone 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
-(`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:
 
     ```bash
-./tensorflow/lite/tools/make/download_dependencies.sh
+    git clone https://github.com/tensorflow/tensorflow.git tensorflow_src
+
     ```
 
-Note that you only need to do this once.
+    **Note:** If you're using the TensorFlow Docker image, the repo is already
+    provided in `/tensorflow_src/`.
 
-You should then be able to compile:
+3.  Run following script at the root of the TensorFlow repository to download
-
+    all the build dependencies:
-To build ARMv7 binary for Raspberry Pi 2, 3 and 4:
 
     ```bash
-./tensorflow/lite/tools/make/build_rpi_lib.sh
+    cd tensorflow_src && ./tensorflow/lite/tools/make/download_dependencies.sh
     ```
 
-This should compile a static library in:
+    **Note:** You only need to do this once.
+
+4.  To build ARMv7 binary for Raspberry Pi 2, 3 and 4 execute:
+
+    ```bash
+    PATH=../rpi_tools/arm-bcm2708/arm-rpi-4.9.3-linux-gnueabihf/bin:$PATH ./tensorflow/lite/tools/make/build_rpi_lib.sh
+    ```
+
+    **Note:** This should compile a static library in:
     `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
-./tensorflow/lite/tools/make/build_rpi_lib.sh TARGET_ARCH=armv6
+    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
     ```
 
-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`.
 
 ## 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:
+
+1.  Log in to your Raspberry Pi and install the toolchain:
 
     ```bash
     sudo apt-get install build-essential
     ```
 
-Now git-clone the TensorFlow repository
+2.  Clone TensorFlow repository:
-(`https://github.com/tensorflow/tensorflow`) and run this at the root of
-the repository:
 
     ```bash
-./tensorflow/lite/tools/make/download_dependencies.sh
+    git clone https://github.com/tensorflow/tensorflow.git tensorflow_src
+
     ```
 
-Note that you only need to do this once.
+3.  Run following script at the root of the TensorFlow repository to download
+    all the build dependencies:
 
-You should then be able to compile:
+    ```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
     ```
 
-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_armv6/libtensorflow-lite.a`.

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 \