Thing you want to do

Download TensorFlow Docker image https://www.tensorflow.org/install/docker?hl=ja Then, I want to start the container and check the operation of tensorflow.

Premise

Docker must be installed on any host.
You can use Docker commands.

How to install Docker https://qiita.com/kenichiro-yamato/items/7e3cb21613784a27409d

Prior confirmation

version

[root@docker ~]# docker -v
Docker version 19.03.7, build 7141c199a2

Container in operation

[root@docker ~]# docker ps
CONTAINER ID        IMAGE               COMMAND             CREATED             STATUS              PORTS               NAMES

Get image with docker pull

docker pull tensorflow/tensorflow

result

[root@docker ~]# docker pull tensorflow/tensorflow
Using default tag: latest
latest: Pulling from tensorflow/tensorflow
171857c49d0f: Pull complete
419640447d26: Pull complete
61e52f862619: Pull complete
40085aa86d3c: Pull complete
b827fdfa00c7: Pull complete
134f84527676: Pull complete
e1f30e7788ed: Pull complete
a13925316d82: Pull complete
5decca4d86ff: Pull complete
70c56a3cd1fa: Pull complete
Digest: sha256:c57fb9628d80872ece8640a22bd0153b2cc8d62d21d79f4d99c3b237a728b62e
Status: Downloaded newer image for tensorflow/tensorflow:latest
docker.io/tensorflow/tensorflow:latest

Confirm that the image was acquired

[root@docker ~]# docker images
REPOSITORY                             TAG                 IMAGE ID            CREATED             SIZE
tensorflow/tensorflow                  latest              623195db36df        7 weeks ago         1.46GB

Start the container with docker run

Change the option specifications such as memory specification, port specification, host specification, and shared directory specification as desired.

docker run -m 4096m -p 80:80 -d --privileged -h yamato.host -i -t -v /root/share:/share:rw --name tensorflow_container1 tensorflow/tensorflow

Confirm the start of the container and connect

[root@docker ~]# docker ps
CONTAINER ID        IMAGE                   COMMAND             CREATED             STATUS              PORTS                NAMES
62f578fc0279        tensorflow/tensorflow   "/bin/bash"         11 seconds ago      Up 10 seconds       0.0.0.0:80->80/tcp   tensorflow_container1

docker exec -it tensorflow_container1 /bin/bash

Connect to tensorflow_container1 with.

[root@docker ~]# docker exec -it tensorflow_container1 /bin/bash

________                               _______________
___  __/__________________________________  ____/__  /________      __
__  /  _  _ \_  __ \_  ___/  __ \_  ___/_  /_   __  /_  __ \_ | /| / /
_  /   /  __/  / / /(__  )/ /_/ /  /   _  __/   _  / / /_/ /_ |/ |/ /
/_/    \___//_/ /_//____/ \____//_/    /_/      /_/  \____/____/|__/

Successful connection.

Confirmation of initial state

You can already use python3 and pip.

root@yamato:~# python -V
Python 3.6.9

root@yamato:~# pip

Usage:
  pip <command> [options]

Since vim is not included, install it.

apt-get update

after

apt-get install vim

Then you can use vim.

Create a py file and try it

vim test.py


print ("Hello World! I am Kenichiro Yamato")

Run.

python test.py

Hello World! I am Kenichiro Yamato

Is displayed, OK.

Try tensorflow sample code

vi sample.py

import tensorflow as tf
mnist = tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0

model = tf.keras.models.Sequential([
  tf.keras.layers.Flatten(),
  tf.keras.layers.Dense(512, activation=tf.nn.relu),
  tf.keras.layers.Dropout(0.2),
  tf.keras.layers.Dense(10, activation=tf.nn.softmax)
])
model.compile(optimizer='adam',
              loss='sparse_categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x_train, y_train, epochs=5)
model.evaluate(x_test, y_test)