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use nvidia/cuda:10.1-base-ubuntu18.04 as base image

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Christoph Schranz 2020-09-01 18:48:29 +02:00
parent 73d4188b5a
commit e5eb8f6e1b
3 changed files with 6 additions and 20 deletions
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14
.build/Dockerfile
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@ -2,8 +2,8 @@
# Use NVIDIA CUDA as base image and run the same installation as in the other packages.
# The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch
FROM nvidia/cuda:10.1-base-ubuntu18.04
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
FROM nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04
LABEL authors="Christoph Schranz <christoph.schranz@salzburgresearch.at>, Mathematical Michael <consistentbayes@gmail.com>"
# This is a concatenated Dockerfile, the maintainers of subsequent sections may vary.
RUN chmod 1777 /tmp && chmod 1777 /var/tmp
@ -41,7 +41,6 @@ RUN apt-get update \
locales \
fonts-liberation \
run-one \
openssh-client \
&& apt-get clean && rm -rf /var/lib/apt/lists/*
RUN echo "en_US.UTF-8 UTF-8" > /etc/locale.gen && \
@ -385,11 +384,6 @@ LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu
# installation via conda leads to errors in version 4.8.2
#RUN conda install --quiet --yes \
# 'tensorflow-gpu=2.1*' \
# 'keras-gpu' && \
# fix-permissions $CONDA_DIR && \
# fix-permissions /home/$NB_USER
RUN pip install --upgrade pip && \
pip install --no-cache-dir "tensorflow-gpu>=2.1.*" && \
pip install --no-cache-dir keras
@ -414,7 +408,7 @@ RUN conda clean --all -f -y && \
############################ Useful packages ###############################
############################################################################
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
LABEL authors="Christoph Schranz <christoph.schranz@salzburgresearch.at>, Mathematical Michael <consistentbayes@gmail.com>"
USER root
@ -432,7 +426,7 @@ RUN set -ex \
graphviz==0.11 \
' \
&& apt-get update \
&& apt-get -y install htop apt-utils graphviz libgraphviz-dev \
&& apt-get -y install htop apt-utils graphviz libgraphviz-dev openssh-client \
&& pip install --no-cache-dir $buildDeps
# Install various extensions

8
src/Dockerfile.gpulibs
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@ -2,11 +2,6 @@ LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
# Install Tensorflow, check compatibility here: https://www.tensorflow.org/install/gpu
# installation via conda leads to errors in version 4.8.2
#RUN conda install --quiet --yes \
# 'tensorflow-gpu=2.1*' \
# 'keras-gpu' && \
# fix-permissions $CONDA_DIR && \
# fix-permissions /home/$NB_USER
RUN pip install --upgrade pip && \
pip install --no-cache-dir "tensorflow-gpu>=2.1.*" && \
pip install --no-cache-dir keras
@ -15,9 +10,6 @@ RUN pip install --upgrade pip && \
RUN conda install --quiet --yes \
pyyaml mkl mkl-include setuptools cmake cffi typing
# Deep-NN libs
RUN apt-get update && apt-get install -y libcudnn7-dev && rm -rf /var/lib/apt/lists/*
# Check compatibility here: https://pytorch.org/get-started/locally/
RUN conda install --quiet --yes \
pytorch \

4
src/Dockerfile.header
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@ -1,6 +1,6 @@
# Use NVIDIA CUDA as base image and run the same installation as in the other packages.
# The version of cudatoolkit must match those of the base image, see Dockerfile.pytorch
FROM nvidia/cuda:10.1-base-ubuntu18.04
LABEL maintainer="Christoph Schranz <christoph.schranz@salzburgresearch.at>"
FROM nvidia/cuda:10.1-cudnn7-runtime-ubuntu18.04
LABEL authors="Christoph Schranz <christoph.schranz@salzburgresearch.at>, Mathematical Michael <consistentbayes@gmail.com>"
# This is a concatenated Dockerfile, the maintainers of subsequent sections may vary.
RUN chmod 1777 /tmp && chmod 1777 /var/tmp