Sonnet Installation Instructions

Wednesday. July 12, 2017 - 3 mins

Sonnet on AWS Ubuntu Server 16.04 LTS (HVM), SSD Volume Type - ami-835b4efa

The main principle of Sonnet is to first construct Python objects which represent some part of a neural network, and then separately connect these objects into the TensorFlow computation graph. The objects are subclasses of sonnet.AbstractModule and as such are referred to as Modules. Modules may be connected into the graph multiple times, and any variables declared in that module will be automatically shared on subsequent connection calls.

We start by updating the packages of Ubuntu:


$ sudo apt-get update && sudo apt-get -y upgrade

Install pip and virtualenv by issuing one of the following commands:


$ sudo apt-get install python-pip python-dev python-virtualenv python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas # for Python 2.7
$ sudo apt-get install python3-pip python3-dev python-virtualenv python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas # for Python 3.n

Update pip:
```
$ pip install --upgrade pip
```
Create a virtualenv environment by issuing one of the following commands:
```
$ virtualenv --system-site-packages ~/tensorflow # for Python 2.7
$ virtualenv --system-site-packages -p python3 ~/tensorflow # for Python 3.n
```
where ~/tensorflow is a target directory that specifies the top of the virtualenv tree. We may choose any directory.
Activate the virtualenv environment by issuing one of the following commands:
```
$ source ~/tensorflow/bin/activate # bash, sh, ksh, or zsh
$ source ~/tensorflow/bin/activate.csh  # csh or tcsh
```
The preceding source command should change your prompt to the following:
```
 (tensorflow)$ 
```

Issue one of the following commands to install TensorFlow in the active virtualenv environment:


(tensorflow)$ pip install --upgrade tensorflow      # for Python 2.7
(tensorflow)$ pip3 install --upgrade tensorflow     # for Python 3.n
(tensorflow)$ pip install --upgrade tensorflow-gpu  # for Python 2.7 and GPU
(tensorflow)$ pip3 install --upgrade tensorflow-gpu # for Python 3.n and GPU

Install JDK 8 by using:
```
$ sudo apt-get install openjdk-8-jdk
```

Add Bazel distribution URI as a package source (one time setup):


$ echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list
$ curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -

Install and update Bazel:
```
$ sudo apt-get update && sudo apt-get install bazel
```
Once installed, you can upgrade to a newer version of Bazel with:
```
$ sudo apt-get upgrade bazel
```

Activate virtualenv again:


$ source ~/tensorflow/bin/activate # bash, sh, ksh, or zsh
$ source ~/tensorflow/bin/activate.csh  # csh or tcsh

First clone the Sonnet source code with TensorFlow as a submodule:
```
$ git clone --recursive https://github.com/deepmind/sonnet
```
and then configure Tensorflow headers:
```
$ cd sonnet/tensorflow
$ ./configure
$ cd ../
```
You can choose the suggested defaults during the TensorFlow configuration. Note: This will not modify your existing installation of TensorFlow. This step is necessary so that Sonnet can build against the TensorFlow headers.

Build and run the installer:


$ mkdir /tmp/sonnet
$ bazel build --config=opt --copt="-D_GLIBCXX_USE_CXX11_ABI=0" :install
$ ./bazel-bin/install /tmp/sonnet

pip install the generated wheel file:


$ pip install /tmp/sonnet/*.whl

You can verify that Sonnet has been successfully installed by, for example, trying out the resampler op:


$ cd ~/
$ python
>>> import sonnet as snt
>>> import tensorflow as tf
>>> snt.resampler(tf.constant([0.]), tf.constant([0.]))

The expected output should be:


<tf.Tensor 'resampler/Resampler:0' shape=(1,) dtype=float32>

[1] https://www.tensorflow.org/install/install_linux#installing_with_virtualenv

[2] https://docs.bazel.build/versions/master/install-ubuntu.html

[3] https://github.com/deepmind/sonnet