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Dockerfile_TF_compile_CPU
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FROM ubuntu:16.04
LABEL maintainer="Craig Citro <[email protected]>"
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
curl \
git \
libcurl3-dev \
libfreetype6-dev \
libpng12-dev \
libzmq3-dev \
pkg-config \
python-dev \
rsync \
software-properties-common \
unzip \
zip \
zlib1g-dev \
openjdk-8-jdk \
openjdk-8-jre-headless \
ffmpeg \
libcupti-dev \
vim \
wget \
&& \
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 \
matplotlib \
numpy \
scipy \
sklearn \
Pillow \
h5py
# Set up Bazel.
# 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" >>/etc/bazel.bazelrc
# Similarly, we need to workaround sandboxing issues:
# https://github.com/bazelbuild/bazel/issues/418
RUN echo "build --spawn_strategy=standalone --genrule_strategy=standalone" \
>>/etc/bazel.bazelrc
# Install the most recent bazel release.
ENV BAZEL_VERSION 0.5.4
WORKDIR /
RUN mkdir /bazel && \
cd /bazel && \
curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -O https://github.com/bazelbuild/bazel/releases/download/$BAZEL_VERSION/bazel-$BAZEL_VERSION-installer-linux-x86_64.sh && \
curl -H "User-Agent: Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2987.133 Safari/537.36" -fSsL -o /bazel/LICENSE.txt https://raw.githubusercontent.com/bazelbuild/bazel/master/LICENSE && \
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 https://github.com/tensorflow/tensorflow.git && \
cd tensorflow && \
git checkout r1.4
WORKDIR /tensorflow
# TODO(craigcitro): Don't install the pip package, since it makes it
# more difficult to experiment with local changes. Instead, just add
# the built directory to the path.
ENV CI_BUILD_PYTHON python
RUN tensorflow/tools/ci_build/builds/configured CPU \
bazel build -c opt --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" \
# For optimized builds appropriate for the hardware platform of your choosing, uncomment below...
# For ivy-bridge or sandy-bridge
# --copt=-march="ivybridge" \
# for haswell, broadwell, or skylake
# --copt=-march="haswell" \
--copt=-march="native" \
tensorflow/tools/pip_package:build_pip_package && \
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/pip && \
pip --no-cache-dir install --upgrade /tmp/pip/tensorflow-*.whl && \
rm -rf /tmp/pip && \
rm -rf /root/.cache
# Clean up pip wheel and Bazel cache when done.
RUN git clone https://github.com/lengstrom/fast-style-transfer && \
cd fast-style-transfer && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/587d1865_rain-princess/rain-princess.ckpt && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/588aa800_la-muse/la-muse.ckpt && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/588aa846_udnie/udnie.ckpt && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/588aa883_scream/scream.ckpt && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/588aa89d_wave/wave.ckpt && \
wget -c https://d17h27t6h515a5.cloudfront.net/topher/2017/January/588aa8b6_wreck/wreck.ckpt && \
sed -i "s/DEVICE =*/DEVICE = '\/cpu:0'/" evaluate.py && \
sed -i "s/\/gpu:0/\/cpu:0/" evaluate.py
# For CUDA profiling, TensorFlow requires CUPTI.
ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
# TensorBoard
EXPOSE 6006
WORKDIR "/notebooks/fast-style-transfer"
ENTRYPOINT ["python", "./evaluate.py"]
CMD ["--checkpoint", "./la-muse.ckpt", "--in-path", "/input/", "--out-path", "/output/", "--allow-different-dimensions"]