如何在 f26 上用 Docker 跑 Tensorflow

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How to Install Tensorflow using Docker on Fedora 26


裝 GPU 驅動

放進來篇幅太長，請參考我之前的筆記在 Fedora 上安裝 Nvidia 1080Ti 的驅動

裝 Docker CE

參考

其實只有幾行，先處理一些前置作業，安裝 repo

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$ sudo dnf remove docker docker-common docker-selinux docker-engine-selinux docker-engine
$ sudo dnf -y install dnf-plugins-core
$ sudo dnf config-manager --add-repo https://download.docker.com/linux/fedora/docker-ce.repo

然後安裝 docker

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$ sudo dnf install -y docker-ce
$ dnf list docker-ce  --showduplicates | sort -r
docker-ce.x86_64               17.09.0.ce-1.fc26               docker-ce-stable

官方建議在 production 系統上應該要安裝同一版本的 docker-ce，所以安裝時要給版本參數

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$ sudo dnf -y install docker-ce-17.09.0.ce-1.fc26
$ sudo systemctl start docker; sudo systemctl enable docker
$ sudo docker run hello-world

應該會看到歡迎訊息，如果不想用了要解除安裝

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$ sudo dnf remove docker-ce
$ sudo rm -rf /var/lib/docke

裝 nvidia-docker

官方教學在 nvidia-docker github 的 README.md 上

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# Install nvidia-docker and nvidia-docker-plugin
$ wget -P /tmp https://github.com/NVIDIA/nvidia-docker/releases/download/v1.0.1/nvidia-docker-1.0.1-1.x86_64.rpm
$ sudo rpm -i /tmp/nvidia-docker*.rpm && rm /tmp/nvidia-docker*.rpm
$ sudo systemctl start nvidia-docker
# Test nvidia-smi
$ nvidia-docker run --rm nvidia/cuda nvidia-smi

最後一行 # Test nvidia-smi 會跟 $ nvidia-smi 有一樣的輸出，就是裝 GPU driver 時曾經出現的這張

Hello Tensorflow

我們可以用類似下列的指令，從 tensor flow 的 repo 拉適合的 binary 來玩

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$ nvidia-docker run -it -p <hostPort:containerPort> <TensorFlowGPUImage>

validate your installation

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$ docker run -it gcr.io/tensorflow/tensorflow bash
Unable to find image 'gcr.io/tensorflow/tensorflow:latest' locally
latest: Pulling from tensorflow/tensorflow
f6fa9a861b90: Pull complete 
da7318603015: Pull complete 
6a8bd10c9278: Pull complete 
d5a40291440f: Pull complete 
bbdd8a83c0f1: Pull complete 
abeb898c5fe7: Pull complete 
d66940709c30: Pull complete 
44835d776a0b: Pull complete 
6ec5364eed97: Pull complete 
3ff1cc6e638b: Pull complete 
56aa69af61b9: Pull complete 
982e3b05055e: Pull complete 
Digest: sha256:581e048541034a6992d85cfd37fd36e8085d34142bcb7f57a2a680dc96e38f7e
Status: Downloaded newer image for gcr.io/tensorflow/tensorflow:latest
root@47a80733b08c:/notebooks#

進入 docker 之後，進入 python interactive shell

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>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>>> sess = tf.Session()
>>> print(sess.run(hello))
Hello, TensorFlow!