Compile and install tensorflow on Ubuntu 16.04. You might want to create a virtual machine on GCP, AWS, then compile tensorflow there. And then download compiled `*.wheel` file for further using it. List of compiled tensorflow with different options can be found here https://github.com/yaroslavvb/tensorflow-community-wheels/issues.

tensorflow-cpu.sh

#!/bin/bash

##
## FROM https://github.com/floydhub/dl-docker
##
## Before running the script change versions and compilation flags below.
## If you're having trouble running the whole script, try running
## each command separately.
##
## List of compiled tensorflow packages https://github.com/yaroslavvb/tensorflow-community-wheels/issues

set -e

apt-get update && apt-get install -y \
    bc \
    build-essential \
    cmake \
    curl \
    g++ \
    gfortran \
    git \
    libffi-dev \
    libfreetype6-dev \
    libhdf5-dev \
    libjpeg-dev \
    liblcms2-dev \
    libopenblas-dev \
    liblapack-dev \
    libpng12-dev \
    libssl-dev \
    libtiff5-dev \
    libwebp-dev \
    libzmq3-dev \
    nano \
    pkg-config \
    python-dev \
    software-properties-common \
    unzip \
    vim \
    wget \
    zlib1g-dev \
    qt5-default \
    libvtk6-dev \
    zlib1g-dev \
    libjpeg-dev \
    libwebp-dev \
    libpng-dev \
    libtiff5-dev \
    libjasper-dev \
    libopenexr-dev \
    libgdal-dev \
    libdc1394-22-dev \
    libavcodec-dev \
    libavformat-dev \
    libswscale-dev \
    libtheora-dev \
    libvorbis-dev \
    libxvidcore-dev \
    libx264-dev \
    yasm \
    libopencore-amrnb-dev \
    libopencore-amrwb-dev \
    libv4l-dev \
    libxine2-dev \
    libtbb-dev \
    libeigen3-dev \
    python-dev \
    python-tk \
    python-numpy \
    ant \
    default-jdk \
    doxygen

# Link BLAS library to use OpenBLAS using the alternatives mechanism (https://www.scipy.org/scipylib/building/linux.html#debian-ubuntu)
update-alternatives --set libblas.so.3 /usr/lib/openblas-base/libblas.so.3

# Install pip
curl -O https://bootstrap.pypa.io/get-pip.py && \
  python get-pip.py && \
  rm get-pip.py

# Add SNI support to Python
pip --no-cache-dir install \
    pyopenssl \
    ndg-httpsclient \
    pyasn1

# Install useful Python packages using apt-get to avoid version incompatibilities with Tensorflow binary
# especially numpy, scipy, skimage and sklearn (see https://github.com/tensorflow/tensorflow/issues/2034)
apt-get install -y \
    python-numpy \
    python-scipy \
    python-nose \
    python-h5py \
    python-skimage \
    python-matplotlib \
    python-pandas \
    python-sklearn \
    python-sympy

# Install other useful Python packages using pip
pip --no-cache-dir install --upgrade ipython && \
  pip --no-cache-dir install \
    Cython \
    ipykernel \
    jupyter \
    path.py \
    Pillow \
    pygments \
    six \
    sphinx \
    wheel \
    zmq \
    && \
  python -m ipykernel.kernelspec

# # Install Theano and set up Theano config (.theanorc) OpenBLAS
# pip --no-cache-dir install git+git://github.com/Theano/Theano.git@${THEANO_VERSION} && \
#   \
#   echo "[global]\ndevice=cpu\nfloatX=float32\nmode=FAST_RUN \
#     \n[lib]\ncnmem=0.95 \
#     \n[nvcc]\nfastmath=True \
#     \n[blas]\nldflag = -L/usr/lib/openblas-base -lopenblas \
#     \n[DebugMode]\ncheck_finite=1" \
#   > /root/.theanorc

# Install bazel
echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | tee /etc/apt/sources.list.d/bazel.list \
    && curl https://bazel.build/bazel-release.pub.gpg | apt-key add - \
    && apt-get update && apt-get install -y bazel

# get tensorflow source code
git clone https://github.com/tensorflow/tensorflow ~/tensorflow \
    && cd ~/tensorflow \
    && git checkout v1.1.0

# configure it
# Say No to: GPU support
./configure

# Build with support of avx, avx2, fma, mse4.1, gmse4.2
bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-msse4.1 --copt=-msse4.2 -k //tensorflow/tools/pip_package:build_pip_package

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

# install
pip install /tmp/tensorflow/*.wheel


# # Install Keras
# RUN pip --no-cache-dir install git+git://github.com/fchollet/keras.git@${KERAS_VERSION}

# # Install other useful Python packages using pip
# RUN  pip --no-cache-dir install \
#       gensim \
#       nltk

# RUN python -m nltk.downloader stopwords