def _print_info(self):
print('Finished data loading.')
print(' NumNodes: {}'.format(self._graph.number_of_nodes()))
print(' NumEdges: {}'.format(self._graph.number_of_edges()))
print(' NumFeats: {}'.format(self._graph.ndata['feat'].shape[1]))
print(' NumClasses: {}'.format(self.num_classes))
print(' NumTrainingSamples: {}'.format(
F.nonzero_1d(self._graph.ndata['train_mask']).shape[0]))
print(' NumValidationSamples: {}'.format(
F.nonzero_1d(self._graph.ndata['val_mask']).shape[0]))
print(' NumTestSamples: {}'.format(
F.nonzero_1d(self._graph.ndata['test_mask']).shape[0]))
def load(self):
"""load the graph list and the labels from disk"""
graph_path = os.path.join(self.save_path, self.save_name + '.bin')
info_path = os.path.join(self.save_path, self.save_name + '.pkl')
graphs, _ = load_graphs(str(graph_path))
info = load_info(str(info_path))
self._num_classes = info['num_classes']
self._predict_category = info['predict_category']
self._hg = graphs[0]
train_mask = self._hg.nodes[self.predict_category].data['train_mask']
test_mask = self._hg.nodes[self.predict_category].data['test_mask']
self._labels = self._hg.nodes[self.predict_category].data['labels']
train_idx = F.nonzero_1d(train_mask)
test_idx = F.nonzero_1d(test_mask)
self._train_idx = train_idx
self._test_idx = test_idx