import dgl.data as data import unittest import backend as F @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_minigc(): ds = data.MiniGCDataset(16, 10, 20) g, l = list(zip(*ds)) print(g, l) @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_gin(): ds_n_graphs = { 'MUTAG': 188, 'IMDBBINARY': 1000, 'IMDBMULTI': 1500, 'PROTEINS': 1113, 'PTC': 344, } for name, n_graphs in ds_n_graphs.items(): ds = data.GINDataset(name, self_loop=False, degree_as_nlabel=False) assert len(ds) == n_graphs, (len(ds), name) @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_fraud(): g = data.FraudDataset('amazon')[0] assert g.num_nodes() == 11944 g = data.FraudAmazonDataset()[0] assert g.num_nodes() == 11944 g = data.FraudYelpDataset()[0] assert g.num_nodes() == 45954 @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_fakenews(): ds = data.FakeNewsDataset('politifact', 'bert') assert len(ds) == 314 ds = data.FakeNewsDataset('gossipcop', 'profile') assert len(ds) == 5464 @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_tudataset_regression(): ds = data.TUDataset('ZINC_test', force_reload=True) assert len(ds) == 5000 @unittest.skipIf(F._default_context_str == 'gpu', reason="Datasets don't need to be tested on GPU.") def test_data_hash(): class HashTestDataset(data.DGLDataset): def __init__(self, hash_key=()): super(HashTestDataset, self).__init__('hashtest', hash_key=hash_key) def _load(self): pass a = HashTestDataset((True, 0, '1', (1,2,3))) b = HashTestDataset((True, 0, '1', (1,2,3))) c = HashTestDataset((True, 0, '1', (1,2,4))) assert a.hash == b.hash assert a.hash != c.hash if __name__ == '__main__': test_minigc() test_gin() test_data_hash() test_tudataset_regression() test_fraud() test_fakenews()