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PiperOrigin-RevId: 240186934
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A. Unique TensorFlower
TensorFlower Gardener
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# To push a new version:
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# 1. Download tensorrt from
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# https://developer.nvidia.com/nvidia-tensorrt-5x-download
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# and copy it into /tmp.
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# 2. $ ./Dockerfile.rbe.cuda10.0-cudnn7-centos.sh
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# 3. $ docker push gcr.io/tensorflow-testing/nosla-cuda10.0-cudnn7-centos7
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#
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# We can't currently build this Dockerfile directly:
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# tensorrt for centos is only availble via a authenticated download link from
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# nvidia, and it's larger than citc's max file size.
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# To work around this, we create a Docker environment in /tmp to build the
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# image from in a shell script (2).
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FROM nvidia/cuda:10.0-cudnn7-devel-centos7
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LABEL maintainer="Manuel Klimek <klimek@google.com>"
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# Install packages required to build tensorflow.
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RUN yum install -y centos-release-scl && \
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yum install -y \
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devtoolset-7 \
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java-1.8.0-openjdk-devel \
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patch \
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rh-python34 \
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wget && \
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yum clean all -y
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# TODO(klimek): Once nvidia provides a way to install tensorrt from within
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# docker, switch to that. Until then, we copy the tensorrt rpm into the docker
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# environment.
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ADD tensorrt.rpm tensorrt.rpm
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RUN rpm -ihv tensorrt.rpm && \
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yum install -y --nogpgcheck tensorrt && \
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rm -f tensorrt.rpm
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# Enable devtoolset-7 and rh-python34 in the docker image.
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env PATH="/opt/rh/rh-python34/root/usr/bin:/opt/rh/devtoolset-7/root/usr/bin:/usr/local/nvidia/bin:/usr/local/cuda/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin" \
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LD_LIBRARY_PATH="/opt/rh/rh-python34/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:/opt/rh/devtoolset-7/root/usr/lib64/dyninst:/opt/rh/devtoolset-7/root/usr/lib/dyninst:/opt/rh/devtoolset-7/root/usr/lib64:/opt/rh/devtoolset-7/root/usr/lib:/usr/local/nvidia/lib:/usr/local/nvidia/lib64" \
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PCP_DIR="/opt/rh/devtoolset-7/root" \
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PERL5LIB="/opt/rh/devtoolset-7/root//usr/lib64/perl5/vendor_perl:/opt/rh/devtoolset-7/root/usr/lib/perl5:/opt/rh/devtoolset-7/root//usr/share/perl5/vendor_perl" \
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PKG_CONFIG_PATH="/opt/rh/rh-python34/root/usr/lib64/pkgconfig/"
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# Install pip packages needed to build tensorflow.
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COPY install/*.sh /install/
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RUN grep -E 'easy_install |pip3' install/install_pip_packages.sh \
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| grep -v 'no-binary=:all:' \
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> install/centos_pip_packages.sh && \
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bash install/centos_pip_packages.sh
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# Install a /usr/bin/python3 link.
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# centos by default does not provide links, and instead relies on paths into
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# /opt/ to switch to alternative configurations. For bazel remote builds,
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# the python path between the local machine running bazel and the remote setup
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# must be the same.
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RUN update-alternatives --install /usr/bin/python3 python3 /opt/rh/rh-python34/root/usr/bin/python3 0
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# Install a ubuntu-compatible openjdk link so that ubuntu JAVA_HOME works
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# for this image.
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# TODO(klimek): Figure out a way to specify a different remote java path from
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# the local one.
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RUN ln -s /usr/lib/jvm/java /usr/lib/jvm/java-8-openjdk-amd64
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tensorflow/tools/ci_build/Dockerfile.rbe.cuda10.0-cudnn7-centos7.sh
Executable file
42
tensorflow/tools/ci_build/Dockerfile.rbe.cuda10.0-cudnn7-centos7.sh
Executable file
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#!/bin/bash -eux
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# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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#
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# Script to create a centos7 docker image.
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# Before running, copy tensorrt into /tmp after downlading it from:
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# https://developer.nvidia.com/nvidia-tensorrt-5x-download
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#
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# TODO(klimek): once there are downloadable images for tensorrt for centos7
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# similar to debian, use those.
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#
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# Note that this creates a lot of large files in your filesystem:
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# 1. The tensorrt rpm itself in your downloads folder.
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# 2. The tensorrt copy in /tmp.
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# 3. For each time this script is run and fails, there's a remaining copy
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# in the corresponding /tmp directory.
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# 4. The docker cache grows large very quickly.
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#
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# To clean up failed script runs:
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# $ rm /tmp/*/*.rpm
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WORKDIR="$(mktemp -d)"
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BASE="$(pwd)"
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cp -R "${BASE}/"* "${WORKDIR}/"
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cp "/tmp/nv-tensorrt-repo-rhel7-cuda10.0-trt5.0.2.6-ga-20181010-1-1.x86_64.rpm" "${WORKDIR}/tensorrt.rpm"
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cd "${WORKDIR}"
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docker build -f Dockerfile.rbe.cuda10.0-cudnn7-centos7 \
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--tag "gcr.io/tensorflow-testing/nosla-cuda10.0-cudnn7-centos7" .
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cd "${BASE}"
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rm -rf "${WORKDIR}"
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