Dockerfile tensorflow built from source cuda:7.5-cudnn5

Dockerfile

FROM nvidia/cuda:7.5-cudnn5-devel

MAINTAINER Craig Citro <[email protected]>, Morgan Giraud <[email protected]>

RUN apt-get update && apt-get install -y --no-install-recommends \
        build-essential \
        curl \
        git \
        libfreetype6-dev \
        libpng12-dev \
        libzmq3-dev \
        pkg-config \
        python \
        python-dev \
        python-numpy \
        python-pip \
        rsync \
        software-properties-common \
        swig \
        unzip \
        zip \
        zlib1g-dev \
        && \
    apt-get clean && \
    rm -rf /var/lib/apt/lists/*

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

RUN pip --no-cache-dir install \
        ipykernel \
        jupyter \
        matplotlib \
        && \
    python -m ipykernel.kernelspec

# 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 0.3.0
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 v0.9.0 --recursive --recurse-submodules https://github.com/tensorflow/tensorflow.git && \
    cd tensorflow && \
    git checkout v0.9.0
WORKDIR /tensorflow

# Configure the build for our CUDA configuration.
ENV CUDA_TOOLKIT_PATH /usr/local/cuda
ENV CUDNN_INSTALL_PATH /usr/local/cuda
ENV TF_NEED_CUDA 1

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

WORKDIR /root

# Set up CUDA variables
ENV CUDA_PATH /usr/local/cuda

# TensorBoard
EXPOSE 6006

RUN ["/bin/bash"]