C4 Instance, Tensorflow r1.1

Installing TensorFlow r1.1 on an AWS C4 instance.

Following this with a few modifications

Built using Ubuntu 16.04 with c4.2xlarge instance and 25GB of standard ssd storage.

# Update and upgrade installed packages
sudo apt-get update
sudo apt-get upgrade

############################################
# Install basic packages needed for TensorFlow and generally needed
########################
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual unzip python-numpy swig python-pandas python-sklearn unzip wget pkg-config zip g++ zlib1g-dev libcurl3-dev
sudo apt-get install bc

# AWS EFS Driver (to mount drives from EFS)
sudo apt-get -y install nfs-common

# Install Python package manager
sudo pip install -U pip
sudo pip install --upgrade pip
sudo pip install wheel numpy

############################################
# Install Bazel
########################
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 -
sudo apt-get update && sudo apt-get install bazel
sudo apt-get upgrade bazel

############################################
# Install TensorFlow
########################
git clone https://github.com/tensorflow/tensorflow

cd tensorflow
git checkout r1.1

./configure
# Used all of the default options

# Compiles in AVX2 optimizations.
bazel build -c opt --copt=-march="haswell" //tensorflow/tools/pip_package:build_pip_package

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

# Install
sudo pip install --upgrade --force-reinstall /tmp/tensorflow_pkg/tensorflow-1.1.0rc2-cp27-cp27mu-linux_x86_64.whl

# Install any additional packages that you want the image to have
sudo pip install pyyaml
sudo pip install keras
sudo pip install ipython jupyter

You should now have a fully functional python environment and all of these should work:

import tensorflow as tf
import keras
import sklearn
from PIL import Image
import numpy as np
import scipy
from matplotlib import pyplot as plt

gvanhorn38/aws_c4_tensorflow_r1_1_install.md