100 lines
3.7 KiB
Bash
100 lines
3.7 KiB
Bash
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#!/usr/bin/env bash
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. 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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## @description download nvidia docker bin
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## @audience public
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## @stability stable
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function download_nvidia_docker_bin()
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{
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# download http server
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if [[ -n "$DOWNLOAD_HTTP" ]]; then
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MY_NVIDIA_DOCKER_RPM_URL="${DOWNLOAD_HTTP}/downloads/nvidia-docker/${NVIDIA_DOCKER_RPM}"
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else
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MY_NVIDIA_DOCKER_RPM_URL=${NVIDIA_DOCKER_RPM_URL}
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fi
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if [[ -f "${DOWNLOAD_DIR}/nvidia-docker/${NVIDIA_DOCKER_RPM}" ]]; then
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echo "${DOWNLOAD_DIR}/nvidia-docker/${NVIDIA_DOCKER_RPM} is exist."
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else
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echo "download ${MY_NVIDIA_DOCKER_RPM_URL} ..."
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wget -P ${DOWNLOAD_DIR}/nvidia-docker/ ${MY_NVIDIA_DOCKER_RPM_URL}
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fi
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}
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## @description install nvidia docker
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## @audience public
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## @stability stable
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function install_nvidia_docker()
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{
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download_nvidia_docker_bin
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sudo rpm -i ${DOWNLOAD_DIR}/nvidia-docker/${NVIDIA_DOCKER_RPM}
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echo -e "\033[32m===== Start nvidia-docker =====\033[0m"
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sudo systemctl start nvidia-docker
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echo -e "\033[32m===== Check nvidia-docker status =====\033[0m"
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systemctl status nvidia-docker
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echo -e "\033[32m===== Check nvidia-docker log =====\033[0m"
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journalctl -u nvidia-docker
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echo -e "\033[32m===== Test nvidia-docker-plugin =====\033[0m"
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curl http://localhost:3476/v1.0/docker/cli
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# create nvidia driver library path
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if [ ! -d "/var/lib/nvidia-docker/volumes/nvidia_driver" ]; then
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echo "WARN: /var/lib/nvidia-docker/volumes/nvidia_driver folder path is not exist!"
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mkdir -p /var/lib/nvidia-docker/volumes/nvidia_driver
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fi
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local nvidiaVersion=`get_nvidia_version`
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echo -e "\033[31m nvidia detect version is ${nvidiaVersion}\033[0m"
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mkdir /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}
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mkdir /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}/bin
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mkdir /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}/lib64
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cp /usr/bin/nvidia* /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}/bin
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cp /usr/lib64/libcuda* /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}/lib64
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cp /usr/lib64/libnvidia* /var/lib/nvidia-docker/volumes/nvidia_driver/${nvidiaVersion}/lib64
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echo -e "\033[32m===== Please manually execute the following command =====\033[0m"
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echo -e "\033[32mshell:> nvidia-docker run --rm ${DOCKER_REGISTRY}/nvidia/cuda:9.0-devel nvidia-smi
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# If you don't see the list of graphics cards above, the NVIDIA driver installation failed. =====
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\033[0m"
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echo -e "\033[32m===== Please manually execute the following command =====\033[0m"
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echo -e "\033[32m# Test with tf.test.is_gpu_available()
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shell:> nvidia-docker run -it ${DOCKER_REGISTRY}/tensorflow/tensorflow:1.9.0-gpu bash
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# In docker container
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container:> python
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python:> import tensorflow as tf
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python:> tf.test.is_gpu_available()
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python:> exit()
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\033[0m"
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}
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## @description uninstall nvidia docker
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## @audience public
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## @stability stable
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function uninstall_nvidia_docker()
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{
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echo "This method is not implemented."
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}
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