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Dockerfile_GPU
executable file
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Dockerfile_GPU
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# Generated by Neurodocker version 0.4.0
# Timestamp: 2018-06-22 09:08:27 UTC
#
# Thank you for using Neurodocker. If you discover any issues
# or ways to improve this software, please submit an issue or
# pull request on our GitHub repository:
#
# https://github.com/kaczmarj/neurodocker
FROM neurodebian:stretch-non-free
ARG DEBIAN_FRONTEND="noninteractive"
ENV LANG="en_US.UTF-8" \
LC_ALL="en_US.UTF-8" \
ND_ENTRYPOINT="/neurodocker/startup.sh"
RUN export ND_ENTRYPOINT="/neurodocker/startup.sh" \
&& apt-get update -qq \
&& apt-get install -y -q --no-install-recommends \
apt-utils \
bzip2 \
ca-certificates \
curl \
locales \
unzip \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* \
&& sed -i -e 's/# en_US.UTF-8 UTF-8/en_US.UTF-8 UTF-8/' /etc/locale.gen \
&& dpkg-reconfigure --frontend=noninteractive locales \
&& update-locale LANG="en_US.UTF-8" \
&& chmod 777 /opt && chmod a+s /opt \
&& mkdir -p /neurodocker \
&& if [ ! -f "$ND_ENTRYPOINT" ]; then \
echo '#!/usr/bin/env bash' >> "$ND_ENTRYPOINT" \
&& echo 'set -e' >> "$ND_ENTRYPOINT" \
&& echo 'if [ -n "$1" ]; then "$@"; else /usr/bin/env bash; fi' >> "$ND_ENTRYPOINT"; \
fi \
&& chmod -R 777 /neurodocker && chmod a+s /neurodocker
ENTRYPOINT ["/neurodocker/startup.sh"]
RUN apt-get update -qq \
&& apt-get install -y -q --no-install-recommends \
fsl-core \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
RUN sed -i '$isource /etc/fsl/fsl.sh' $ND_ENTRYPOINT
RUN echo '{ \
\n "pkg_manager": "apt", \
\n "instructions": [ \
\n [ \
\n "base", \
\n "neurodebian:stretch-non-free" \
\n ], \
\n [ \
\n "install", \
\n [ \
\n "fsl-core" \
\n ] \
\n ], \
\n [ \
\n "add_to_entrypoint", \
\n "source /etc/fsl/fsl.sh" \
\n ] \
\n ] \
\n}' > /neurodocker/neurodocker_specs.json
RUN apt-get update \
&& apt-get -y install git g++ python3 libeigen3-dev zlib1g-dev libqt4-opengl-dev \
&& apt-get -y install libgl1-mesa-dev libfftw3-dev libtiff5-dev curl \
&& apt-get -y install git-core python3-pip python3-dev build-essential \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
## NVIDIA CUDA Installation
###########################
# LICENSE:
##########
# Copyright (c) 2017, NVIDIA CORPORATION. All rights reserved.
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
# BASE INSTALLATION
###################
RUN apt-get update && apt-get install -y --no-install-recommends ca-certificates apt-transport-https && \
rm -rf /var/lib/apt/lists/* && \
NVIDIA_GPGKEY_SUM=d1be581509378368edeec8c1eb2958702feedf3bc3d17011adbf24efacce4ab5 && \
NVIDIA_GPGKEY_FPR=ae09fe4bbd223a84b2ccfce3f60f4b3d7fa2af80 && \
apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub && \
apt-key adv --export --no-emit-version -a $NVIDIA_GPGKEY_FPR | tail -n +2 > cudasign.pub && \
echo "$NVIDIA_GPGKEY_SUM cudasign.pub" | sha256sum -c --strict - && rm cudasign.pub && \
echo "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/cuda.list && \
echo "deb https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list
ENV CUDA_VERSION 9.1.85
ENV CUDA_PKG_VERSION 9-1=$CUDA_VERSION-1
RUN apt-get update && apt-get install -y --no-install-recommends \
cuda-cudart-$CUDA_PKG_VERSION && \
ln -s cuda-9.1 /usr/local/cuda && \
rm -rf /var/lib/apt/lists/*
# nvidia-docker 1.0
LABEL com.nvidia.volumes.needed="nvidia_driver"
LABEL com.nvidia.cuda.version="${CUDA_VERSION}"
RUN echo "/usr/local/nvidia/lib" >> /etc/ld.so.conf.d/nvidia.conf && \
echo "/usr/local/nvidia/lib64" >> /etc/ld.so.conf.d/nvidia.conf
ENV PATH /usr/local/nvidia/bin:/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64
# nvidia-container-runtime
ENV NVIDIA_VISIBLE_DEVICES all
ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
ENV NVIDIA_REQUIRE_CUDA "cuda>=9.1"
# RUNTIME INSTALLATION
######################
ENV NCCL_VERSION 2.2.12
RUN apt-get update && apt-get install -y --no-install-recommends \
cuda-libraries-$CUDA_PKG_VERSION \
libnccl2=$NCCL_VERSION-1+cuda9.1 && \
apt-mark hold libnccl2 && \
rm -rf /var/lib/apt/lists/*
# CUDNN INSTALLATION
####################
ENV CUDNN_VERSION 7.1.2.21
LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"
RUN apt-get update && apt-get install -y --no-install-recommends \
libcudnn7=$CUDNN_VERSION-1+cuda9.1 && \
apt-mark hold libcudnn7 && \
rm -rf /var/lib/apt/lists/*
RUN pip3 install --upgrade pip \
&& pip install wheel numpy scipy nilearn matplotlib scikit-image nibabel \
&& pip install http://download.pytorch.org/whl/cpu/torch-1.1.0-cp35-cp35m-linux_x86_64.whl
# This command does not get cached -> very slow each time when building container -> use prebuild mrtrix_RC3.tar.gz instead
#RUN mkdir /code && cd /code \
# && git clone https://github.com/MRtrix3/mrtrix3.git \
# && cd mrtrix3/ \
# && git checkout 3.0_RC3 \
# && ./configure \
# && ./build \
# && ./set_path \
RUN mkdir -p ~/.tractseg \
&& mkdir -p /code \
&& curl -SL -o /code/mrtrix3_RC3.tar.gz https://zenodo.org/record/1415322/files/mrtrix3_RC3.tar.gz?download=1
RUN tar -zxvf /code/mrtrix3_RC3.tar.gz -C code \
&& /code/mrtrix3/set_path
# Uncomment if we want to rebuild the following commands (otherwise using cache)
#RUN echo "rebuild"
RUN pip install --upgrade https://github.com/MIC-DKFZ/TractSeg/archive/master.zip
RUN download_all_pretrained_weights
# Does not work -> added mrtrix to path in python
ENV PATH /code/mrtrix3/bin:$PATH
# Using this we can avoid having to call TractSeg each time -> but has problems finding bet then
#ENTRYPOINT ["TractSeg"]