Dockerfile7.5.gpu

FROM nvidia/cuda:7.5-cudnn5-devel

ARG TENSORFLOW_VERSION=0.10
ARG TENSORFLOW_ARCH=gpu

RUN apt-get update && apt-get install -y --no-install-recommends \
        bc \
        build-essential \
        cmake \
        curl \
        g++ \
        gfortran \
        git \
        libhdf5-dev \
        libjpeg-dev \
        liblcms2-dev \
        libopenblas-dev \
        liblapack-dev \
        libopenjpeg2 \
        libpng12-dev \
        libssl-dev \
        libtiff5-dev \
        libwebp-dev \
        libzmq3-dev \
        nano \
        pkg-config \
        python \
        python-dev \
        rsync \
        software-properties-common \
        swig \
        unzip \
        vim \
        wget \
        zip \
        zlib1g-dev \
        && \
    apt-get clean && \
    apt-get autoremove && \
    rm -rf /var/lib/apt/lists/* && \
# 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
RUN curl -fSsL -O https://bootstrap.pypa.io/get-pip.py && \
    python get-pip.py && \
    rm get-pip.py

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


RUN apt-get update && apt-get install -y \
        python-pip \
        python-setuptools \
        && \
    apt-get clean && \
    apt-get autoremove && \
    rm -rf /var/lib/apt/lists/*


# Install other useful Python packages using pip
RUN pip --no-cache-dir install --upgrade ipython && \
    pip --no-cache-dir install \
        Cython \
        numpy \
        scipy \
        nose \
        h5py \
        scikit-image \
        matplotlib \
        pandas \
        scikit-learn \
        sympy \
        ipykernel \
        jupyter \
        path.py \
        Pillow \
        plotly \
        pygments \
        seaborn \
        six \
        sphinx \
        wheel \
        zmq \
        && \
    python -m ipykernel.kernelspec

# Set up our notebook config.
COPY jupyter_notebook_config.py /root/.jupyter/

# Jupyter has issues with being run directly:
#   https://github.com/ipython/ipython/issues/7062
# We just add a little wrapper script.
COPY run_jupyter.sh /

# Set up Bazel.

# We need to add a custom PPA to pick up JDK8, since trusty doesn't
# have an openjdk8 backport.  openjdk-r is maintained by a reliable contributor:
# Matthias Klose (https://launchpad.net/~doko).  It will do until
# we either update the base image beyond 14.04 or openjdk-8 is
# finally backported to trusty; see e.g.
#   https://bugs.launchpad.net/trusty-backports/+bug/1368094
RUN add-apt-repository -y ppa:openjdk-r/ppa && \
    apt-get update && \
    apt-get install -y --no-install-recommends openjdk-8-jdk openjdk-8-jre-headless && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

# Running bazel inside a `docker build` command causes trouble, cf:
#   https://github.com/bazelbuild/bazel/issues/134
# The easiest solution is to set up a bazelrc file forcing --batch.
RUN echo "startup --batch" >>/root/.bazelrc
# Similarly, we need to workaround sandboxing issues:
#   https://github.com/bazelbuild/bazel/issues/418
RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \
    >>/root/.bazelrc
ENV BAZELRC /root/.bazelrc
# Install the most recent bazel release.
ENV BAZEL_VERSION 0.3.1
WORKDIR /
RUN mkdir /bazel && \
    cd /bazel && \
    curl -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    curl -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE.txt && \
    chmod +x bazel-*.sh && \
    ./bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
    cd / && \
    rm -f /bazel/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh

# Download and build TensorFlow.

RUN git clone -b r${TENSORFLOW_VERSION} --recursive --recurse-submodules https://github.com/tensorflow/tensorflow.git && \
    cd tensorflow && \
    git checkout r${TENSORFLOW_VERSION}
WORKDIR /tensorflow

# Configure the build for our CUDA configuration.
ENV CUDA_PATH /usr/local/cuda
ENV CUDA_TOOLKIT_PATH /usr/local/cuda
#ENV CUDNN_INSTALL_PATH /usr/local/cuda
ENV CUDNN_INSTALL_PATH /usr/lib/x86_64-linux-gnu
ENV LD_LIBRARY_PATH /usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/nvidia/lib64
ENV TF_NEED_CUDA 1
ENV TF_CUDA_COMPUTE_CAPABILITIES=3.0,3.5,5.2

RUN ./configure && \
    bazel build -c opt --config=cuda tensorflow/tools/pip_package:build_pip_package && \
    bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip && \
    pip install --upgrade /tmp/pip/tensorflow-*.whl

# Install Keras
ARG KERAS_VERSION=1.1.0
ENV KERAS_BACKEND=tensorflow
RUN pip --no-cache-dir install git+git://github.com/fchollet/keras.git@${KERAS_VERSION}

WORKDIR /root

# Uncomment the following two lines if you're using windows
# COPY run_jupyter.sh /root/
# COPY demo/ /root/demo/

# TensorBoard
EXPOSE 6006
# IPython
EXPOSE 8888

RUN ["/bin/bash"]