How to Fix ModuleNotFoundError: no module named ‘tensorflow.contrib’


no module named 'tensorflow.contrib'ModuleNotFoundError: no module named ‘tensorflow.contrib’ error occurs when you are using “TensorFlow version 2.x.x and tf.contrib no longer exist in Tensorflow 2.x.x because its modules were moved.”

How to fix it?

To fix the ModuleNotFoundError: no module named ‘tensorflow.contrib’ error, install the “tensorflow-addons” module.

pip install tensorflow-addons

ModuleNotFoundError - no module named 'tensorflow.contrib'

TensorFlow Addons is a repository of contributions that follow the best practices provided by the TensorFlow ecosystem. It contains a variety of extra layers, metrics, losses, and optimizers, including tensorflow.contrib module that are not present in the main TensorFlow library.

Once the installation is complete, you can import modules from tensorflow.contrib without encountering the error.

You can check out the official guide to migrate TensorFlow from version 1.x.x to 2.x.x.

Now, you can use the “layers” module from “tensorflow.contrib” like this:

import tensorflow_addons as tfa


This will print out a list of all the available layers in the tensorflow_addons.layers module. Each of these is a class that you can instantiate and use in your model.


TensorFlow Addons (TFA) has ended development and introduction of new features.
TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.
Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP).

For more information, see:

Alternate solution (Not recommended)

Switch back to TensorFlow 1.x.x

If you cannot find a way to do what you want with TensorFlow 2.0 and you don’t want to rewrite your code, you can switch back to TensorFlow 1.x.

However, TensorFlow 1.x is no longer actively maintained, so this should only be a temporary solution. You can install TensorFlow 1.15 (the last 1.x version) with pip:

pip install tensorflow==1.15

This solution is not recommended and can be used only in emergencies.

I hope the above solutions work for you and you can fix the error!

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