Fix test_decode_layer_03.

tests/icosagon/test_declayer.py

@@ -79,23 +79,24 @@ def test_decode_layer_03():
     d = Data()
     d.add_node_type('Dummy 1', 100)
     d.add_node_type('Dummy 2', 100)
-    d.add_relation_type('Dummy Relation 1', 0, 1,
+    fam = d.add_relation_family('Dummy 1-Dummy 2', 0, 1, True)
+    fam.add_relation_type('Dummy Relation 1',
         torch.rand((100, 100), dtype=torch.float32).round().to_sparse())
     prep_d = prepare_training(d, TrainValTest(.8, .1, .1))
 
     in_layer = OneHotInputLayer(d)
     d_layer = DecagonLayer(in_layer.output_dim, 32, d)
-    dec_layer = DecodeLayer(input_dim=d_layer.output_dim, data=prep_d, keep_prob=1.,
-        decoder_class={(0, 1): DEDICOMDecoder}, activation=lambda x: x)
+    dec_layer = DecodeLayer(input_dim=d_layer.output_dim, data=prep_d,
+        keep_prob=1., activation=lambda x: x)
     seq = torch.nn.Sequential(in_layer, d_layer, dec_layer)
 
-    pred_adj_matrices = seq(None)
-    assert isinstance(pred_adj_matrices, dict)
-    assert len(pred_adj_matrices) == 2
-    assert isinstance(pred_adj_matrices[0, 1], list)
-    assert isinstance(pred_adj_matrices[1, 0], list)
-    assert len(pred_adj_matrices[0, 1]) == 1
-    assert len(pred_adj_matrices[1, 0]) == 1
+    pred = seq(None)
+    assert isinstance(pred, Predictions)
+    assert len(pred.relation_families) == 1
+    assert isinstance(pred.relation_families[0], RelationFamilyPredictions)
+    assert isinstance(pred.relation_families[0].relation_types, list)
+    assert len(pred.relation_families[0].relation_types) == 1
+    assert isinstance(pred.relation_families[0].relation_types[0], RelationPredictions)
 
 
 def test_decode_layer_04():