This directory contains examples and tutorials demonstrating how to use NSL.

The .py files in this directory are all example trainers runnable end-to-end as Python programs:

• adv_keras_cnn_mnist.py: Adversarial regularization on the MNIST dataset.
• graph_keras_mlp_cora.py: Graph regularization on the Cora dataset.
• graph_nets_cora_gcn.py: Graph Convolutional Network on the Cora dataset using GraphNets.
• graph_nets_cora_graph_regularization.py: Graph regularization on the Cora dataset using GraphNets.

The notebooks subdirectory contains colab-based tutorials that allow you to explore NSL interactively. This subdirectory is generally where most new tutorials are added. Note that the tutorials shown on our TensorFlow website are hosted under the g3doc/tutorials directory.

The preprocess subdirectory contains various data preprocessing scripts.