Closed lingfanyu closed 3 years ago
Sorry. Already fixed it.
def ogbn_sample(seed, samp_nodes):
np.random.seed(seed)
ylabel = torch.LongTensor(graph.y[samp_nodes])
feature, times, edge_list, indxs, _ = sample_subgraph(graph, \
inp = {'paper': np.concatenate([samp_nodes, graph.years[samp_nodes]]).reshape(2, -1).transpose()}, \
sampled_depth = args.sample_depth, sampled_number = args.sample_width, \
feature_extractor = feature_MAG)
node_feature, node_type, edge_time, edge_index, edge_type, node_dict, edge_dict = \
to_torch(feature, times, edge_list, graph)
train_mask = graph.train_mask[indxs['paper']]
valid_mask = graph.valid_mask[indxs['paper']]
test_mask = graph.test_mask[indxs['paper']]
ylabel = graph.y[indxs['paper']]
yindxs = indxs['paper'][test_mask]
return node_feature, node_type, edge_time, edge_index, edge_type, (train_mask, valid_mask, test_mask), ylabel, yindxs
Thanks!
There are not enough values to unpack: https://github.com/acbull/pyHGT/blob/16547c0c0a6977c40b8efa88a7f3e40cf1955362/ogbn-mag/eval_ogbn_mag.py#L140
yindxs
is not in return value ofogbn_sample
https://github.com/acbull/pyHGT/blob/16547c0c0a6977c40b8efa88a7f3e40cf1955362/ogbn-mag/eval_ogbn_mag.py#L81