Load Cora Dataset

load_data.py

import dgl
import tensorflow as tf

dataset = dgl.data.CoraGraphDataset()

# A DGL dataset may contain multiple graphs.
# In the case of Cora, there is only one graph.
g = dataset[0]

# g.ndata is a dictionary of nodes related data.
# Prepare the training, validation, and test datasets.
train_ds = tf.data.Dataset.zip((
    tf.data.Dataset.from_tensor_slices(g.ndata['feat'][g.ndata['train_mask']]),
    tf.data.Dataset.from_tensor_slices(g.ndata['label'][g.ndata['train_mask']])
)).batch(64)
val_ds = tf.data.Dataset.zip((
    tf.data.Dataset.from_tensor_slices(g.ndata['feat'][g.ndata['val_mask']]),
    tf.data.Dataset.from_tensor_slices(g.ndata['label'][g.ndata['val_mask']])
)).batch(64)
test_ds = tf.data.Dataset.zip((
    tf.data.Dataset.from_tensor_slices(g.ndata['feat'][g.ndata['test_mask']]),
    tf.data.Dataset.from_tensor_slices(g.ndata['label'][g.ndata['test_mask']])
)).batch(64)