Building and Installing Tensorflow on AArch64

This post concentrates on building Tensorflow on AArch64.

About Tensorflow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API. TensorFlow is one of the best libraries to implement deep learning. TensorFlow is a software library for numerical computation of mathematical expressional, using data flow graphs.

It’s best to run TensorFlow on machines equipped with GPUs

A common workflow of TensorFlow (And this is common for any supervised machine learning platform) is like this:

  1. Training cluster reads from input dataset, uses algorithms to build a data model. For example, see Google’s cat recognition learning.
  2. Serving cluster serves the data model, so that any client can connect to the serving cluster to predict new samples, for example, ask “Is this a cat?”
  3. Training cluster can periodically update data model when new data available, so clients can get prediction results from the up-to-date model.

Tensorflow models can be found here.

Main Use Cases of TensorFlow

  1. Voice/Sound Recognition
  2. Text Based Applications
  3. Image Recognition
  4. Time Series
  5. Video Detection


  • Java 8 (e.g. openjdk-8-jre) installed  
  • Python

  • Pip
  • NumPy
  • python-virtualenv

  • Bazel 0.5.4

Build Instructions

Install OpenJDK 8

$ wget 
$ tar xvf jdk8u-server-release-1708.tar.xz 
$ cd jdk8u-server-release-1708 
$ export JAVA_HOME=$PWD 
$ cd jre/lib/security/ 
$ rm cacerts 

(for CentOS 7) $ ln --symbolic /etc/pki/java/cacerts . 
(for Debian Jessie) $ ln --symbolic /etc/ssl/certs/java/cacerts .  

$ cd jdk8u-server-release-1708/bin 
$ export PATH=$PWD:$PATH  

Install Python dependencies

To install TensorFlow, you must install the following packages:

  • numpy, which is a numerical processing package that TensorFlow requires.
  • dev, which enables adding extensions to Python.
  • pip, which enables you to install and manage certain Python packages.
  • wheel, which enables you to manage Python compressed packages in the wheel (.whl) format.

$ sudo apt update
$ sudo apt install python-pip
$ pip install --upgrade pip

Install NumPy

$ python -m pip install --user numpy

Install other dependencies

$ sudo apt-get install python-numpy python-dev python-pip python-wheel python-virtualenv

Build Bazel

# Pre-requisites for Bazel
$ sudo apt-get install pkg-config zip g++ zlib1g-dev unzip

$ wget
$ mkdir bazel-0.5.4
$ unzip -d bazel-0.5.4
$ cd bazel-0.5.4

Modify bazel source file to make it compatible with aarch64.
diff --git a/scripts/bootstrap/ b/scripts/bootstrap/
index 502f2c1..a2ab4dc 100755
--- a/scripts/bootstrap/
+++ b/scripts/bootstrap/
@@ -40,7 +40,7 @@ PLATFORM="$(uname -s | tr 'A-Z' 'a-z')"

 MACHINE_TYPE="$(uname -m)"
-if [ "${MACHINE_TYPE}" = 'amd64' -o "${MACHINE_TYPE}" = 'x86_64' -o "${MACHINE_TYPE}" = 's390x' ]; then
+if [ "${MACHINE_TYPE}" = 'amd64' -o "${MACHINE_TYPE}" = 'x86_64' -o "${MACHINE_TYPE}" = 's390x'  -o "${MACHINE_TYPE}" = 'aarch64' ]; then

diff --git a/src/main/java/com/google/devtools/build/lib/util/ b/src/main/java/com/google/devtools/build/lib/util/
index 7a85c29..e5f3eae 100755
--- a/src/main/java/com/google/devtools/build/lib/util/
+++ b/src/main/java/com/google/devtools/build/lib/util/
@@ -26,6 +26,7 @@ public enum CPU {
   X86_64("x86_64", ImmutableSet.of("amd64", "x86_64", "x64")),
   PPC("ppc", ImmutableSet.of("ppc", "ppc64", "ppc64le")),
   ARM("arm", ImmutableSet.of("arm", "armv7l")),
+  AARCH64("aarch64", ImmutableSet.of("aarch64")),
   S390X("s390x", ImmutableSet.of("s390x", "s390")),
   UNKNOWN("unknown", ImmutableSet.<String>of());
diff --git a/third_party/BUILD b/third_party/BUILD
index 9cd2fac..f1cd14c 100755
--- a/third_party/BUILD
+++ b/third_party/BUILD
@@ -583,6 +583,11 @@ config_setting(

+    name = "aarch64",
+    values = {"host_cpu": "aarch64"},
     name = "freebsd",
     values = {"host_cpu": "freebsd"},

Compile Bazel
$ ./
#Copy bazel to $PATH
$ sudo cp output/bazel /usr/local/bin/

Build Tensorflow

$ git clone
$ ./configure
# Please specify the location of python. [Default is /usr/bin/python]:
# Please specify optimization flags to use during compilation [Default is -march=native]: 
# Do you wish to use jemalloc as the malloc implementation? (Linux only) [Y/n]
jemalloc enabled on Linux
# Do you wish to build TensorFlow with Google Cloud Platform support? [y/N]
No Google Cloud Platform support will be enabled for TensorFlow
# Do you wish to build TensorFlow with Hadoop File System support? [y/N]
No Hadoop File System support will be enabled for TensorFlow
# Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N]
No XLA support will be enabled for TensorFlow
Found possible Python library paths:
# Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]

Using python library path: /usr/local/lib/python2.7/dist-packages
# Do you wish to build TensorFlow with OpenCL support? [y/N]
No OpenCL support will be enabled for TensorFlow
# Do you wish to build TensorFlow with CUDA support? [y/N]
No CUDA support will be enabled for TensorFlow
Configuration finished
Extracting Bazel installation...
INFO: Starting clean (this may take a while). Consider using --expunge_async if the clean takes more than several minutes.
INFO: Downloading 297,424 bytes

$ bazel build -c opt --copt="-funsafe-math-optimizations" --copt="-ftree-vectorize" --copt="-fomit-frame-pointer" --verbose_failures tensorflow/tools/pip_package:build_pip_package

#Build pip package
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

Install Tensorflow

$ sudo pip install /tmp/tensorflow_pkg/tensorflow-1.5.0rc0-cp27-cp27mu-linux_aarch64.whl

Create a virtualenv environment

Create a virtualenv environment by issuing one of the following commands:

$ sudo mkdir /tensorflow
$ sudo virtualenv --system-site-packages /tensorflow

Activate the virtualenv environment 

Activate the virtualenv environment by issuing one of the following commands:

$ source /tensorflow/bin/activate bash

The preceding source command should change your prompt to the following:


Running Tensorflow on Hadoop