Tutorial: Using Tensorflow with Docker

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--D. Thiebaut (talk) 22:42, 12 February 2017 (EST)


 

DockerLogo.png


These are very quick instructions for installing Docker under Mac OSX and for running Tensorflow on it. This is a summarized version of the longer explanations given on the official TensorFlow Install page:

and the Docker Install page:


Install Docker



Run Docker


  • Find Docker in the Applications and run it
  • It will open a Terminal window
  • Note the IP that is specified at the end (should be http://192.168.99.100/)
                        ##         .
                  ## ## ##        ==
               ## ## ## ## ##    ===
           /"""""""""""""""""\___/ ===
      ~~~ {~~ ~~~~ ~~~ ~~~~ ~~~ ~ /  ===- ~~~
           \______ o           __/
             \    \         __/
              \____\_______/


docker is configured to use the default machine with IP 192.168.99.100
For help getting started, check out the docs at https://docs.docker.com

docker is configured to use the default machine with IP 192.168.99.100
For help getting started, check out the docs at https://docs.docker.com
  • Quick Docker by pressing Ctrl-C twice and return to the command line


Install TensorFlow "in" Docker


  • Run the following command at the prompt, in the same Terminal session:
docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow
This will download tensorflow and will take a few minutes (~ 8 minutes)
  • Make a note of the URL that is given. It will be of the form:
 http://localhost:8888/tree?token=someLongSeriesOfHexadecimalDigits


Create a Script to Start Docker Automatically


If you are using a Mac or Linux machine, create a script called startDocker.sh in your bin directory: 

#! /bin/bash

docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow


Make your script executable: 

chmod +x startDocker.sh


Start Jupiter


Jupiter is an application that runs in a browser and presents the user a virtual disk where the user can create folders and write programs.

  • To start the Jupiter connected to Docker, open your browser and enter the URL that was given to you in the previous step.
http://localhost:8888/tree?token=someLongSeriesOfHexadecimalDigits
If you get an error message, replace localhost by the IP given next to the whale logo, above (I got 192.168.99.100 when I started Docker).
http://192.168.99.100:8888/tree?token=someLongSeriesOfHexadecimalDigits
  • You should end up with a window similar to this one:


DockerTensorflowJupiter.jpg


  • Double-click on the 1_hello_tensorflow.ipynb Jupiter notebook to open it.
  • You may get an error when the notebook opens. Just click on Cell then Run All to get rid of the error.
  • If the page appears without errors, then all the Tensorflow mini-programs will have run without errors, and you're all set!


Using Jupiter


Hello TensorFlow!


In Jupyter, create a new notebook, and paste the following code into it: 

'''
HelloWorld example using TensorFlow library.
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''

from __future__ import print_function

import tensorflow as tf

# Simple hello world using TensorFlow

# Create a Constant op
# The op is added as a node to the default graph.
#
# The value returned by the constructor represents the output
# of the Constant op.
hello = tf.constant('Hello, TensorFlow!')

# Start tf session
sess = tf.Session()

# Run the op
print(sess.run(hello))


HelloTensorFlowExample.png


  • Click on Cell, Run Cells. You should see the "Hello TensorFlow! message appear on the page.
  • Your installation of TensorFlow works!


Quick Tutorial on how to use Jupyter















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