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Last active Apr 1, 2019

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How to compile TensorFlow 1.12 on Ubuntu 16.04 using Docker
FROM nvidia/cuda:9.0-base-ubuntu16.04
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
cuda-command-line-tools-9-0 \
cuda-cublas-dev-9-0 \
cuda-cudart-dev-9-0 \
cuda-cufft-dev-9-0 \
cuda-curand-dev-9-0 \
cuda-cusolver-dev-9-0 \
cuda-cusparse-dev-9-0 \
curl \
git \
libcudnn7=7.2.1.38-1+cuda9.0 \
libcudnn7-dev=7.2.1.38-1+cuda9.0 \
libnccl2=2.4.2-1+cuda9.0 \
libnccl-dev=2.4.2-1+cuda9.0 \
libcurl3-dev \
libfreetype6-dev \
libhdf5-serial-dev \
libpng12-dev \
libzmq3-dev \
pkg-config \
rsync \
software-properties-common \
unzip \
zip \
zlib1g-dev \
wget \
&& \
rm -rf /var/lib/apt/lists/* && \
find /usr/local/cuda-9.0/lib64/ -type f -name 'lib*_static.a' -not -name 'libcudart_static.a' -delete && \
rm /usr/lib/x86_64-linux-gnu/libcudnn_static_v7.a
# install python 3.6 and pip
RUN apt-get update
RUN apt-get install -y software-properties-common vim
RUN add-apt-repository ppa:jonathonf/python-3.6
RUN apt-get update
RUN apt-get install -y build-essential python3.6 python3.6-dev python3-pip python3.6-venv
RUN apt-get install -y git
RUN apt-get update && \
apt-get install nvinfer-runtime-trt-repo-ubuntu1604-4.0.1-ga-cuda9.0 && \
apt-get update && \
apt-get install libnvinfer4=4.1.2-1+cuda9.0 && \
apt-get install libnvinfer-dev=4.1.2-1+cuda9.0
RUN python3.6 -m pip install pip --upgrade
RUN python3.6 -m pip install wheel
RUN python3.6 -m pip install six numpy wheel mock
RUN python3.6 -m pip install keras_applications
RUN python3.6 -m pip install keras_preprocessing
RUN ln -s /usr/bin/python3.6 /usr/bin/python
# 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 0.15.0
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.
WORKDIR /tensorflow
RUN git clone --branch=r1.12 --depth=1 https://github.com/tensorflow/tensorflow.git .
# Configure the build for our CUDA configuration.
ENV CI_BUILD_PYTHON python3.6
ENV LD_LIBRARY_PATH /usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH
ENV TF_NEED_CUDA 1
ENV TF_NEED_TENSORRT 1
ENV TF_CUDA_COMPUTE_CAPABILITIES=3.5,5.2,6.0,6.1,7.0
ENV TF_CUDA_VERSION=9.0
ENV TF_CUDNN_VERSION=7
RUN ln -s /usr/local/cuda/lib64/stubs/libcuda.so /usr/local/cuda/lib64/stubs/libcuda.so.1 && \
LD_LIBRARY_PATH=/usr/local/cuda/lib64/stubs:${LD_LIBRARY_PATH} \
tensorflow/tools/ci_build/builds/configured GPU \
bazel build -c opt --copt=-mavx --config=cuda \
--cxxopt="-D_GLIBCXX_USE_CXX11_ABI=0" \
tensorflow/tools/pip_package:build_pip_package && \
rm /usr/local/cuda/lib64/stubs/libcuda.so.1 && \
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.
WORKDIR /root
# TensorBoard
EXPOSE 6006
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