How does Gretel-synthetics implement differential privacy?

The TensorFlow team has taken on a lot of the heavy lifting of implementing and releasing TensorFlow Privacy, an extension to TensorFlow that allows differentially private learning. Gretel synthetics implements TensorFlow’s open source code for DP-SGD in the Tensorflow-Privacy library with slight modifications to adapt it to recurrent neural networks, and improved the baseline performance by replacing the plain SGD optimizer with an RMSProp optimizer as it often gives higher accuracy than vanilla SGD (Tijmen Tieleman and Geoffrey Hinton, COURSERA: Neural networks for machine learning, 4(2):26–31, 2012).