Difference between revisions of "Tutorial: Using Tensorflow with Docker"
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− | 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: | + | 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: |
* https://www.tensorflow.org/get_started/os_setup#test_the_tensorflow_installation | * https://www.tensorflow.org/get_started/os_setup#test_the_tensorflow_installation | ||
and the Docker Install page: | and the Docker Install page: | ||
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<br /> | <br /> | ||
+ | =Create a Script to Start Docker Automatically= | ||
+ | <br /> | ||
+ | If you are using a Mac or Linux machine, create a script called '''startDocker.sh''' in your bin directory: | ||
+ | <br /> | ||
+ | :<source lang="bash"> | ||
+ | #! /bin/bash | ||
+ | |||
+ | docker run -it -p 8888:8888 gcr.io/tensorflow/tensorflow | ||
+ | </source> | ||
+ | <br /> | ||
+ | Make your script executable: | ||
+ | |||
+ | chmod +x startDocker.sh | ||
+ | |||
+ | |||
+ | <br /> | ||
+ | |||
=Start Jupiter= | =Start Jupiter= | ||
<br /> | <br /> | ||
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. | 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, | + | * 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 | http://192.168.99.100:8888/tree?token=someLongSeriesOfHexadecimalDigits | ||
Line 85: | Line 106: | ||
* If the page appears without errors, then all the Tensorflow mini-programs will have run without errors, and you're all set! | * If the page appears without errors, then all the Tensorflow mini-programs will have run without errors, and you're all set! | ||
<br /> | <br /> | ||
+ | |||
=Using Jupiter = | =Using Jupiter = | ||
+ | <br /> | ||
+ | ==Hello TensorFlow!== | ||
+ | <br /> | ||
+ | In Jupyter, create a new notebook, and paste the following code into it: | ||
+ | <br /> | ||
+ | ::<source lang="python"> | ||
+ | ''' | ||
+ | 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)) | ||
+ | |||
+ | </source> | ||
+ | <br /> | ||
+ | [[Image:HelloTensorFlowExample.png|600px|center]] | ||
+ | <br /> | ||
+ | * Click on '''Cell''', '''Run Cells'''. You should see the "Hello TensorFlow!'' message appear on the page. | ||
+ | * Your installation of TensorFlow works! | ||
+ | <br /> | ||
+ | |||
+ | ==Quick Tutorial on how to use Jupyter== | ||
<br /> | <br /> | ||
* Here's a [http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb quick tutorial] on using the Jupyter dashboard. | * Here's a [http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb quick tutorial] on using the Jupyter dashboard. |
Latest revision as of 10:54, 9 June 2017
--D. Thiebaut (talk) 22:42, 12 February 2017 (EST)
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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
- Go there: https://docs.docker.com/docker-for-mac/
- Download
- Click on the package (do not worry about the warning)
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:
- 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))
- 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
- Here's a quick tutorial on using the Jupyter dashboard.