How to Check Your TensorFlow Version in Colab?

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To check your TensorFlow version in your Jupyter Notebook such as Google’s Colab, use the following two commands:

  • import tensorflow as tf This imports the TensorFlow library and stores it in the variable named tf.
  • print(tf.__version__) This prints the installed TensorFlow version number in the format x.y.z.

The following code example uses the dunder attribute __version__ on the tf module. Libraries commonly maintain their version information in this dunder attribute.

import tensorflow as tf

You can check this out in the following online Jupyter Notebook I’ve prepared for you using a shareable Google Colab notebook:

The interactive Jupyter Notebook opens in a new tab if you click on the image!

How to Switch the TensorFlow version on Colab?

Colab has two TensorFlow versions pre-installed:

  • 2.x version, and for legacy reasons,
  • 1.x version.

Per default, Colab uses TensorFlow version 2.x but you can switch to another version by using a bit of “TensorFlow magic” as a percentage-prefixed tensorflow_version expression in any of your cells:

%tensorflow_version 1.x

After evaluating this statement, the Colab notebook will switch to a state where the TensorFlow version 1.x is used rather than 2.x as per default.

Here’s how this will look like in a cell:

%tensorflow_version 1.x
import tensorflow as tf

And the output in my Colab Notebook is:

TensorFlow 1.x selected.

Note that if you’ve already run any cell that imports the TensorFlow library, you need to restart the notebook by choosing Runtime > Restart runtime in your Colab notebook:

As an alternative to check the TensorFlow version, you can also use the tf.version.VERSION attribute like so:

import tensorflow as tf

This doesn’t work for some older versions of TensorFlow but the alternative tf.__version__ should work for all!

Programmer Humor

“Real programmers set the universal constants at the start such that the universe evolves to contain the disk with the data they want.”xkcd