Add test_model_03().

src/icosagon/convolve.py

@@ -16,7 +16,7 @@ class GraphConv(torch.nn.Module):
         super().__init__(**kwargs)
         self.in_channels = in_channels
         self.out_channels = out_channels
-        self.weight = init_glorot(in_channels, out_channels)
+        self.weight = torch.nn.Parameter(init_glorot(in_channels, out_channels))
         self.adjacency_matrix = adjacency_matrix
 
 

src/icosagon/declayer.py

@@ -68,7 +68,7 @@ class DecodeLayer(torch.nn.Module):
         self.build()
 
     def build(self) -> None:
-        self.decoders = []
+        self.decoders = torch.nn.ModuleList()
         for fam in self.data.relation_families:
             dec = fam.decoder_class(self.input_dim, len(fam.relation_types),
                 self.keep_prob, self.activation)

src/icosagon/trainprep.py

@@ -111,7 +111,7 @@ def prepare_adj_mat(adj_mat: torch.Tensor,
     edges_neg = train_val_test_split_edges(edges_neg, ratios)
 
     adj_mat_train = torch.sparse_coo_tensor(indices = edges_pos.train.transpose(0, 1),
-        values=torch.ones(len(edges_pos.train), shape=adj_mat.shape, dtype=adj_mat.dtype))
+        values=torch.ones(len(edges_pos.train)), size=adj_mat.shape, dtype=adj_mat.dtype)
 
     return adj_mat_train, edges_pos, edges_neg
 

tests/icosagon/test_model.py

@@ -81,4 +81,8 @@ def test_model_03():
     assert isinstance(state_dict, dict)
     # print(state_dict['param_groups'])
     # print(list(m.seq.parameters()))
-    print(list(m.seq[1].parameters()))
+    assert len(list(m.seq[0].parameters())) == 1
+    assert len(list(m.seq[1].parameters())) == 1
+    assert len(list(m.seq[2].parameters())) == 1
+    assert len(list(m.seq[3].parameters())) == 2
+    # print(list(m.seq[1].parameters()))