Switching to Legacy Keras in TensorFlow 2 : os.environ["TF_USE_LEGACY_KERAS"] = "1"

When working with TensorFlow 2, you may encounter the need to switch to the legacy Keras API. This can be achieved by setting the environment variable TF_USE_LEGACY_KERAS to "1".

Understanding Legacy Keras

Keras is a high-level neural networks API that runs on top of TensorFlow. The latest Keras underwent significant changes to improve its usability and efficiency. However, these changes may not be compatible with existing code written for earlier versions of Keras.

To address this, TensorFlow 2 provides a legacy Keras API that maintains the behavior of Keras prior to current default version. This allows developers to continue using their existing Keras code without having to make major modifications.

Setting the Environment Variable

To switch to the legacy Keras API in TensorFlow 2, you need to set the environment variable TF_USE_LEGACY_KERAS to "1". This can be done before importing TensorFlow:

import os

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

import tensorflow as tf

Effects of Legacy Keras

Once you have set the environment variable, TensorFlow will use the legacy Keras API instead of the default Keras API.

Conclusion

Setting the environment variable TF_USE_LEGACY_KERAS to "1" allows you to switch to the legacy Keras API in TensorFlow 2. This can be useful if you have existing Keras code that is not compatible with the default Keras API. By using the legacy Keras API, you can continue to use your existing code without having to make major modifications. However, it is important to note that the legacy Keras API is no longer under active development and may not receive new features or bug fixes.