upd (#1321)

docs/source/developer/ffi.rst

@@ -217,4 +217,5 @@ out their price:
 Please note that containers are NOT meant for passing a large collection of
 items from/to C APIs. It will be quite slow in these cases. It is recommended
 to benchmark first. As an alternative, use NDArray for a large collection of
-numerical values and use BatchedDGLGraph for a lot of graphs.
+numerical values and use ``dgl.batch`` to batch a lot of ``DGLGraph``'s into 
+a single ``DGLGraph``.

python/dgl/data/graph_serialize.py

@@ -28,7 +28,8 @@ class GraphData(ObjectBase):
     @staticmethod
     def create(g: DGLGraph):
         """Create GraphData"""
-        assert g.batch_size == 1, "BatchedDGLGraph is not supported for serialization"
+        # TODO(zihao): support serialize batched graph in the future.
+        assert g.batch_size == 1, "Batched DGLGraph is not supported for serialization"
         ghandle = g._graph
         if len(g.ndata) != 0:
             node_tensors = dict()

python/dgl/graph.py

@@ -962,7 +962,7 @@ class DGLGraph(DGLBaseGraph):
         self._batch_num_nodes = batch_num_nodes
         self._batch_num_edges = batch_num_edges
 
-        # set parent if the graph is a induced subgraph.
+        # set parent if the graph is a subgraph.
         self._parent = parent
 
     def _create_subgraph(self, sgi, induced_nodes, induced_edges):
@@ -1893,7 +1893,7 @@ class DGLGraph(DGLBaseGraph):
 
     @property
     def parent(self):
-        """If current graph is a induced subgraph of a parent graph, return
+        """If current graph is a subgraph of a parent graph, return
         its parent graph, else return None.
 
         Returns

python/dgl/model_zoo/chem/gnn.py

@@ -110,7 +110,7 @@ class GATLayer(nn.Module):
 
         Parameters
         ----------
-        bg : BatchedDGLGraph
+        bg : DGLGraph
             Batched DGLGraphs for processing multiple molecules in parallel
         feats : FloatTensor of shape (N, M1)
             * N is the total number of atoms in the batched graph

tests/compute/test_transform.py

@@ -167,7 +167,7 @@ def test_laplacian_lambda_max():
     g = dgl.DGLGraph(nx.erdos_renyi_graph(N, 0.3))
     l_max = dgl.laplacian_lambda_max(g)
     assert (l_max[0] < 2 + eps)
-    # test BatchedDGLGraph
+    # test batched DGLGraph
     N_arr = [20, 30, 10, 12]
     bg = dgl.batch([
         dgl.DGLGraph(nx.erdos_renyi_graph(N, 0.3))