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Keras Version Configuration for TF-GNN

The TensorFlow GNN library requires tf.keras to be Keras v2, because Keras v3 does not support composite tensor types like tfgnn.GraphTensor. Up to TF 2.15, Keras v2 was the default for tf.keras. For TF 2.16+, you need to make special arrangements, as described in this guide.

Installation and program execution

For TensorFlow 2.16 and up

TensorFlow as of release 2.16 depends on keras>=3 but no longer on a package for Keras v2. Install TF-GNN together with the package tf-keras that continues to supply an implementation of Keras v2.

pip install tensorflow-gnn tf-keras

Running a TF-GNN program under TF 2.16+ requires to set the environment variable TF_USE_LEGACY_KERAS to 1 one way or another, for example:

  • with the Unix shell command

    export TF_USE_LEGACY_KERAS=1

    or your system's equivalent;

  • at the top of the main Python program or Colab notebook by

    import os
os.environ["TF_USE_LEGACY_KERAS"] = "1"

    before any part of the program gets to import tensorflow.

For TensorFlow 2.15

Nothing special is required: TF 2.15 depends on keras==2.15.* and, by default, defines tf.keras with it.

In case TF_USE_LEGACY_KERAS is set to 1 and tf-keras is installed, then tf.keras is defined in terms of that package. While it offers the same API, it is a separate package with separate static registries and class hierarchies, so it does not mix well with user code that uses import keras and objects from keras.*. Hence we recommend to not use keras.* in user code.

For TensorFlow 2.12, 2.13 and 2.14

Nothing special is required: These TF 2.x versions depend on the matching version of Keras 2.x and define tf.keras with it. The environment variable TF_USE_LEGACY_KERAS is ignored.

Writing compatible code

For all supported TensorFlow versions

For use of TF-GNN under any supported version of TensorFlow, we recommend that user code does import tensorflow as tf and uses the Keras API at tf.keras.*. The installation instructions above make sure this is Keras v2, as required by the TF-GNN library itself.

Do not import and use keras.* directly: it will break for TF 2.16 and above.

For TF 2.16+ only

As of TF 2.16+, import tensorflow_gnn as tfgnn checks that tf.keras is Keras v2, which implies that it comes from the tf_keras package.

Users who wish to emphasize the use of Keras v2 at the expense of breaking compatibility with older versions of TensorFlow can use tf_keras as a syntactic alternative to tf.keras.

Other libraries from the TensorFlow ecosystem

Keras does not support mixing different versions or packages of it. Using TF-GNN in combination with other TensorFlow add-on libraries requires all of them to work with the same Keras package, and it must be Keras v2.