def split_val_test_to_batches(self):
# Split the val and test sets to batchs, no shuffling is needed
graphs, labels = helper.group_same_size(self.val_graphs, self.val_labels)
graphs, labels = helper.split_to_batches(graphs, labels, self.batch_size)
self.num_iterations_val = len(graphs)
self.val_graphs_batches, self.val_labels_batches = graphs, labels
if self.config.dataset_name == 'QM9':
# Benchmark graphs have no test sets
graphs, labels = helper.group_same_size(self.test_graphs, self.test_labels)
graphs, labels = helper.split_to_batches(graphs, labels, self.batch_size)
self.num_iterations_test = len(graphs)
self.test_graphs_batches, self.test_labels_batches = graphs, labels
def reshuffle_data(self):
graphs, labels = helper.group_same_size(self.train_graphs,
self.train_labels)
graphs, labels = helper.shuffle_same_size(graphs, labels)
graphs, labels = helper.split_to_batches(graphs, labels,
self.batch_size)
self.num_iterations_train = len(graphs)
graphs, labels = helper.shuffle(graphs, labels)
self.iter = zip(graphs, labels)
