[Docker] Install for tensorflow-gpu
Docker for Tensorflow GPU install
2023-09-27 14:23:24 时间
Ref: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker
ubuntu@ip-172-31-39-8:/mnt$ nvidia-smi Thu Nov 5 08:57:35 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 Tesla T4 Off | 00000000:00:1E.0 Off | 0 | | N/A 58C P0 25W / 70W | 0MiB / 15109MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+ ubuntu@ip-172-31-39-8:/mnt$ docker -v Docker version 19.03.11, build dd360c7 ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ curl https://get.docker.com | sh \ > && sudo systemctl start docker \ > && sudo systemctl enable docker % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 0 0 0 0 0 0 0 0 --:--:-- 0:00:04 --:--:-- 0 100 13857 100 13857 0 0 2504 0 0:00:05 0:00:05 --:--:-- 3444 # Executing docker install script, commit: 26ff363bcf3b3f5a00498ac43694bf1c7d9ce16c Warning: the "docker" command appears to already exist on this system. If you already have Docker installed, this script can cause trouble, which is why we're displaying this warning and provide the opportunity to cancel the installation. If you installed the current Docker package using this script and are using it again to update Docker, you can safely ignore this message. You may press Ctrl+C now to abort this script. + sleep 20 + sudo -E sh -c apt-get update -qq >/dev/null + sudo -E sh -c DEBIAN_FRONTEND=noninteractive apt-get install -y -qq apt-transport-https ca-certificates curl >/dev/null + sudo -E sh -c curl -fsSL "https://download.docker.com/linux/ubuntu/gpg" | apt-key add -qq - >/dev/null Warning: apt-key output should not be parsed (stdout is not a terminal) + sudo -E sh -c echo "deb [arch=amd64] https://download.docker.com/linux/ubuntu bionic stable" > /etc/apt/sources.list.d/docker.list + sudo -E sh -c apt-get update -qq >/dev/null + [ -n ] + sudo -E sh -c apt-get install -y -qq --no-install-recommends docker-ce >/dev/null + sudo -E sh -c docker version Client: Docker Engine - Community Version: 19.03.13 API version: 1.40 Go version: go1.13.15 Git commit: 4484c46d9d Built: Wed Sep 16 17:02:36 2020 OS/Arch: linux/amd64 Experimental: false Server: Docker Engine - Community Engine: Version: 19.03.13 API version: 1.40 (minimum version 1.12) Go version: go1.13.15 Git commit: 4484c46d9d Built: Wed Sep 16 17:01:06 2020 OS/Arch: linux/amd64 Experimental: false containerd: Version: 1.3.7 GitCommit: 8fba4e9a7d01810a393d5d25a3621dc101981175 runc: Version: 1.0.0-rc10 GitCommit: dc9208a3303feef5b3839f4323d9beb36df0a9dd docker-init: Version: 0.18.0 GitCommit: fec3683 If you would like to use Docker as a non-root user, you should now consider adding your user to the "docker" group with something like: sudo usermod -aG docker ubuntu Remember that you will have to log out and back in for this to take effect! WARNING: Adding a user to the "docker" group will grant the ability to run containers which can be used to obtain root privileges on the docker host. Refer to https://docs.docker.com/engine/security/security/#docker-daemon-attack-surface for more information. Synchronizing state of docker.service with SysV service script with /lib/systemd/systemd-sysv-install. Executing: /lib/systemd/systemd-sysv-install enable docker ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ docker -v Docker version 19.03.11, build dd360c7 ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID) \ > && curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add - \ > && curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list OK deb https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/$(ARCH) / #deb https://nvidia.github.io/libnvidia-container/experimental/ubuntu18.04/$(ARCH) / deb https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/$(ARCH) / #deb https://nvidia.github.io/nvidia-container-runtime/experimental/ubuntu18.04/$(ARCH) / deb https://nvidia.github.io/nvidia-docker/ubuntu18.04/$(ARCH) / ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ curl -s -L https://nvidia.github.io/nvidia-container-runtime/experimental/$distribution/nvidia-container-runtime.list | sudo tee /etc/apt/sources.list.d/nvidia-container-runtime.list deb https://nvidia.github.io/libnvidia-container/experimental/ubuntu18.04/$(ARCH) / deb https://nvidia.github.io/nvidia-container-runtime/experimental/ubuntu18.04/$(ARCH) / ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ sudo apt-get update Hit:1 http://ap-southeast-2.ec2.archive.ubuntu.com/ubuntu bionic InRelease Hit:2 http://ap-southeast-2.ec2.archive.ubuntu.com/ubuntu bionic-updates InRelease Get:3 http://ap-southeast-2.ec2.archive.ubuntu.com/ubuntu bionic-backports InRelease [74.6 kB] Hit:4 https://download.docker.com/linux/ubuntu bionic InRelease Get:5 https://nvidia.github.io/libnvidia-container/experimental/ubuntu18.04/amd64 InRelease [1158 B] Get:6 https://nvidia.github.io/nvidia-container-runtime/experimental/ubuntu18.04/amd64 InRelease [1149 B] Get:7 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 InRelease [1139 B] Get:8 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/amd64 InRelease [1136 B] Get:9 https://nvidia.github.io/nvidia-docker/ubuntu18.04/amd64 InRelease [1129 B] Hit:10 http://security.ubuntu.com/ubuntu bionic-security InRelease Hit:11 http://ppa.launchpad.net/graphics-drivers/ppa/ubuntu bionic InRelease Get:12 https://nvidia.github.io/libnvidia-container/experimental/ubuntu18.04/amd64 Packages [3392 B] Get:13 https://nvidia.github.io/nvidia-container-runtime/experimental/ubuntu18.04/amd64 Packages [804 B] Get:14 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 Packages [9128 B] Get:15 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/amd64 Packages [6148 B] Get:16 https://nvidia.github.io/nvidia-docker/ubuntu18.04/amd64 Packages [4332 B] Fetched 104 kB in 2s (62.5 kB/s) Reading package lists... Done ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ sudo apt-get install -y nvidia-docker2 Reading package lists... Done Building dependency tree Reading state information... Done The following additional packages will be installed: libnvidia-container-tools libnvidia-container1 nvidia-container-runtime nvidia-container-toolkit The following NEW packages will be installed: libnvidia-container-tools libnvidia-container1 nvidia-container-runtime nvidia-container-toolkit nvidia-docker2 0 upgraded, 5 newly installed, 0 to remove and 16 not upgraded. Need to get 1471 kB of archives. After this operation, 4683 kB of additional disk space will be used. Get:1 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 libnvidia-container1 1.3.0-1 [67.0 kB] Get:2 https://nvidia.github.io/libnvidia-container/stable/ubuntu18.04/amd64 libnvidia-container-tools 1.3.0-1 [20.4 kB] Get:3 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/amd64 nvidia-container-toolkit 1.3.0-1 [763 kB] Get:4 https://nvidia.github.io/nvidia-container-runtime/stable/ubuntu18.04/amd64 nvidia-container-runtime 3.4.0-1 [615 kB] Get:5 https://nvidia.github.io/nvidia-docker/ubuntu18.04/amd64 nvidia-docker2 2.5.0-1 [5912 B] Fetched 1471 kB in 0s (26.4 MB/s) Selecting previously unselected package libnvidia-container1:amd64. (Reading database ... 108331 files and directories currently installed.) Preparing to unpack .../libnvidia-container1_1.3.0-1_amd64.deb ... Unpacking libnvidia-container1:amd64 (1.3.0-1) ... Selecting previously unselected package libnvidia-container-tools. Preparing to unpack .../libnvidia-container-tools_1.3.0-1_amd64.deb ... Unpacking libnvidia-container-tools (1.3.0-1) ... Selecting previously unselected package nvidia-container-toolkit. Preparing to unpack .../nvidia-container-toolkit_1.3.0-1_amd64.deb ... Unpacking nvidia-container-toolkit (1.3.0-1) ... Selecting previously unselected package nvidia-container-runtime. Preparing to unpack .../nvidia-container-runtime_3.4.0-1_amd64.deb ... Unpacking nvidia-container-runtime (3.4.0-1) ... Selecting previously unselected package nvidia-docker2. Preparing to unpack .../nvidia-docker2_2.5.0-1_all.deb ... Unpacking nvidia-docker2 (2.5.0-1) ... Setting up libnvidia-container1:amd64 (1.3.0-1) ... Setting up libnvidia-container-tools (1.3.0-1) ... Setting up nvidia-container-toolkit (1.3.0-1) ... Setting up nvidia-container-runtime (3.4.0-1) ... Setting up nvidia-docker2 (2.5.0-1) ... Processing triggers for libc-bin (2.27-3ubuntu1.2) ... ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ sudo systemctl restart docker ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ sudo docker run --rm --gpus all nvidia/cuda:11.0-base nvidia-smi Unable to find image 'nvidia/cuda:11.0-base' locally 11.0-base: Pulling from nvidia/cuda 54ee1f796a1e: Pull complete f7bfea53ad12: Pull complete 46d371e02073: Pull complete b66c17bbf772: Pull complete 3642f1a6dfb3: Pull complete e5ce55b8b4b9: Pull complete 155bc0332b0a: Pull complete Digest: sha256:774ca3d612de15213102c2dbbba55df44dc5cf9870ca2be6c6e9c627fa63d67a Status: Downloaded newer image for nvidia/cuda:11.0-base Thu Nov 5 09:04:59 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 Tesla T4 Off | 00000000:00:1E.0 Off | 0 | | N/A 44C P0 21W / 70W | 0MiB / 15109MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ ubuntu@ip-172-31-39-8:/mnt$ docker images REPOSITORY TAG IMAGE ID CREATED SIZE nvidia/cuda 11.0-base 2ec708416bb8 2 months ago 122MB
先确保hosting pc上的driver安装好，再安装如下命令。
有可能，因默认的版本问题而导致代码执行出现各种小问题。
FROM tensorflow/tensorflow:latest-gpu MAINTAINER sbll@gmail.com RUN pip install tensorflow-gpu==1.14 \ && pip install keras==2.3.1 \ && pip install numpy \ && pip install scikit-image \ && pip install efficientnet \ && pip install awscli --upgrade --user \ && pip install boto3 COPY ./package /package WORKDIR "/package" CMD python hello.py; python world.py
/* continue */
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