[Bugfix] Handle a Corner Case of Batching after Removing Nodes/Edges (#2465)

* Update

* Update

* Update
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

python/dgl/dataloading/dataloader.py

@@ -227,7 +227,8 @@ class BlockSampler(object):
                     # to the mapping from the new graph to the old frontier.
                     # So we need to test if located_eids is empty, and do the remapping ourselves.
                     if len(located_eids) > 0:
-                        frontier = transform.remove_edges(frontier, located_eids)
+                        frontier = transform.remove_edges(
+                            frontier, located_eids, store_ids=True)
                         frontier.edata[EID] = F.gather_row(parent_eids, frontier.edata[EID])
                 else:
                     # (BarclayII) remove_edges only accepts removing one type of edges,
@@ -235,7 +236,8 @@ class BlockSampler(object):
                     new_eids = parent_eids.copy()
                     for k, v in located_eids.items():
                         if len(v) > 0:
-                            frontier = transform.remove_edges(frontier, v, etype=k)
+                            frontier = transform.remove_edges(
+                                frontier, v, etype=k, store_ids=True)
                             new_eids[k] = F.gather_row(parent_eids[k], frontier.edges[k].data[EID])
                     frontier.edata[EID] = new_eids
 

python/dgl/heterograph.py

@@ -520,7 +520,7 @@ class DGLHeteroGraph(object):
             self._edge_frames[etid].append(data)
         self._reset_cached_info()
 
-    def remove_edges(self, eids, etype=None):
+    def remove_edges(self, eids, etype=None, store_ids=False):
         r"""Remove multiple edges with the specified edge type
 
         Nodes will not be removed. After removing edges, the rest
@@ -536,6 +536,10 @@ class DGLHeteroGraph(object):
         etype : str or tuple of str, optional
             The type of the edges to remove. Can be omitted if there is
             only one edge type in the graph.
+        store_ids : bool, optional
+            If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+            and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+            respectively.
 
         Examples
         --------
@@ -602,12 +606,12 @@ class DGLHeteroGraph(object):
             else:
                 edges[c_etype] = self.edges(form='eid', order='eid', etype=c_etype)
 
-        sub_g = self.edge_subgraph(edges, preserve_nodes=True)
+        sub_g = self.edge_subgraph(edges, preserve_nodes=True, store_ids=store_ids)
         self._graph = sub_g._graph
         self._node_frames = sub_g._node_frames
         self._edge_frames = sub_g._edge_frames
 
-    def remove_nodes(self, nids, ntype=None):
+    def remove_nodes(self, nids, ntype=None, store_ids=False):
         r"""Remove multiple nodes with the specified node type
 
         Edges that connect to the nodes will be removed as well. After removing
@@ -623,6 +627,10 @@ class DGLHeteroGraph(object):
         ntype : str, optional
             The type of the nodes to remove. Can be omitted if there is
             only one node type in the graph.
+        store_ids : bool, optional
+            If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+            and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+            respectively.
 
         Examples
         --------
@@ -694,7 +702,7 @@ class DGLHeteroGraph(object):
                 nodes[c_ntype] = self.nodes(c_ntype)
 
         # node_subgraph
-        sub_g = self.subgraph(nodes)
+        sub_g = self.subgraph(nodes, store_ids=store_ids)
         self._graph = sub_g._graph
         self._node_frames = sub_g._node_frames
         self._edge_frames = sub_g._edge_frames

python/dgl/subgraph.py

@@ -17,7 +17,7 @@ from . import utils
 __all__ = ['node_subgraph', 'edge_subgraph', 'node_type_subgraph', 'edge_type_subgraph',
            'in_subgraph', 'out_subgraph']
 
-def node_subgraph(graph, nodes):
+def node_subgraph(graph, nodes, store_ids=True):
     """Return a subgraph induced on the given nodes.
 
     A node-induced subgraph is a subset of the nodes of a graph together with
@@ -29,9 +29,6 @@ def node_subgraph(graph, nodes):
     * Copy the features of the extracted nodes and edges to the resulting graph.
       The copy is *lazy* and incurs data movement only when needed.
 
-    * Store the IDs of the extracted nodes and edges in the ``ndata`` and ``edata``
-      of the resulting graph under name ``dgl.NID`` and ``dgl.EID``, respectively.
-
     If the graph is heterogeneous, DGL extracts a subgraph per relation and composes
     them as the resulting graph. Thus, the resulting graph has the same set of relations
     as the input one.
@@ -52,6 +49,10 @@ def node_subgraph(graph, nodes):
         If the graph is homogeneous, one can directly pass the above formats.
         Otherwise, the argument must be a dictionary with keys being node types
         and values being the nodes.
+    store_ids : bool, optional
+        If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+        and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+        respectively.
 
     Returns
     -------
@@ -137,11 +138,11 @@ def node_subgraph(graph, nodes):
         induced_nodes.append(_process_nodes(ntype, nids))
     sgi = graph._graph.node_subgraph(induced_nodes)
     induced_edges = sgi.induced_edges
-    return _create_hetero_subgraph(graph, sgi, induced_nodes, induced_edges)
+    return _create_hetero_subgraph(graph, sgi, induced_nodes, induced_edges, store_ids)
 
 DGLHeteroGraph.subgraph = utils.alias_func(node_subgraph)
 
-def edge_subgraph(graph, edges, preserve_nodes=False):
+def edge_subgraph(graph, edges, preserve_nodes=False, store_ids=True):
     """Return a subgraph induced on the given edges.
 
     An edge-induced subgraph is equivalent to creating a new graph
@@ -153,9 +154,6 @@ def edge_subgraph(graph, edges, preserve_nodes=False):
     * Copy the features of the extracted nodes and edges to the resulting graph.
       The copy is *lazy* and incurs data movement only when needed.
 
-    * Store the IDs of the extracted nodes and edges in the ``ndata`` and ``edata``
-      of the resulting graph under name ``dgl.NID`` and ``dgl.EID``, respectively.
-
     If the graph is heterogeneous, DGL extracts a subgraph per relation and composes
     them as the resulting graph. Thus, the resulting graph has the same set of relations
     as the input one.
@@ -177,8 +175,12 @@ def edge_subgraph(graph, edges, preserve_nodes=False):
         Otherwise, the argument must be a dictionary with keys being edge types
         and values being the nodes.
     preserve_nodes : bool, optional
-        If true, do not relabel the incident nodes and remove the isolated nodes
+        If True, do not relabel the incident nodes and remove the isolated nodes
         in the extracted subgraph. (Default: False)
+    store_ids : bool, optional
+        If True, it will store the IDs of the extracted nodes and edges in the ``ndata``
+        and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+        respectively.
 
     Returns
     -------
@@ -278,7 +280,7 @@ def edge_subgraph(graph, edges, preserve_nodes=False):
         induced_edges.append(_process_edges(cetype, eids))
     sgi = graph._graph.edge_subgraph(induced_edges, preserve_nodes)
     induced_nodes = sgi.induced_nodes
-    return _create_hetero_subgraph(graph, sgi, induced_nodes, induced_edges)
+    return _create_hetero_subgraph(graph, sgi, induced_nodes, induced_edges, store_ids)
 
 DGLHeteroGraph.edge_subgraph = utils.alias_func(edge_subgraph)
 
@@ -632,7 +634,7 @@ DGLHeteroGraph.edge_type_subgraph = utils.alias_func(edge_type_subgraph)
 
 #################### Internal functions ####################
 
-def _create_hetero_subgraph(parent, sgi, induced_nodes, induced_edges):
+def _create_hetero_subgraph(parent, sgi, induced_nodes, induced_edges, store_ids=True):
     """Internal function to create a subgraph.
 
     Parameters
@@ -647,14 +649,18 @@ def _create_hetero_subgraph(parent, sgi, induced_nodes, induced_edges):
     induced_edges : list[Tensor] or None
         Induced edge IDs. Will store it as the dgl.EID ndata unless it
         is None, which means the induced edge IDs are the same as the parent edge IDs.
+    store_ids : bool
+        If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+        and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+        respectively.
 
     Returns
     -------
     DGLGraph
         Graph
     """
-    node_frames = utils.extract_node_subframes(parent, induced_nodes)
-    edge_frames = utils.extract_edge_subframes(parent, induced_edges)
+    node_frames = utils.extract_node_subframes(parent, induced_nodes, store_ids)
+    edge_frames = utils.extract_edge_subframes(parent, induced_edges, store_ids)
     hsg = DGLHeteroGraph(sgi.graph, parent.ntypes, parent.etypes)
     utils.set_new_frames(hsg, node_frames=node_frames, edge_frames=edge_frames)
     return hsg

python/dgl/transform.py

@@ -1116,7 +1116,7 @@ def add_edges(g, u, v, data=None, etype=None):
     g.add_edges(u, v, data=data, etype=etype)
     return g
 
-def remove_edges(g, eids, etype=None):
+def remove_edges(g, eids, etype=None, store_ids=False):
     r"""Remove the specified edges and return a new graph.
 
     Also delete the features of the edges. The edges must exist in the graph.
@@ -1135,6 +1135,10 @@ def remove_edges(g, eids, etype=None):
           triplet format in the graph.
 
         Can be omitted if the graph has only one type of edges.
+    store_ids : bool, optional
+        If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+        and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+        respectively.
 
     Return
     ------
@@ -1179,11 +1183,11 @@ def remove_edges(g, eids, etype=None):
     remove_nodes
     """
     g = g.clone()
-    g.remove_edges(eids, etype=etype)
+    g.remove_edges(eids, etype=etype, store_ids=store_ids)
     return g
 
 
-def remove_nodes(g, nids, ntype=None):
+def remove_nodes(g, nids, ntype=None, store_ids=False):
     r"""Remove the specified nodes and return a new graph.
 
     Also delete the features. Edges that connect from/to the nodes will be
@@ -1197,6 +1201,10 @@ def remove_nodes(g, nids, ntype=None):
     ntype : str, optional
         The type of the nodes to remove. Can be omitted if there is
         only one node type in the graph.
+    store_ids : bool, optional
+        If True, it will store the raw IDs of the extracted nodes and edges in the ``ndata``
+        and ``edata`` of the resulting graph under name ``dgl.NID`` and ``dgl.EID``,
+        respectively.
 
     Return
     ------
@@ -1247,7 +1255,7 @@ def remove_nodes(g, nids, ntype=None):
     remove_edges
     """
     g = g.clone()
-    g.remove_nodes(nids, ntype=ntype)
+    g.remove_nodes(nids, ntype=ntype, store_ids=store_ids)
     return g
 
 def add_self_loop(g, etype=None):

python/dgl/utils/internal.py

@@ -754,7 +754,7 @@ def relabel(x):
                                F.copy_to(F.arange(0, len(unique_x), dtype), ctx))
     return unique_x, old_to_new
 
-def extract_node_subframes(graph, nodes):
+def extract_node_subframes(graph, nodes, store_ids=True):
     """Extract node features of the given nodes from :attr:`graph`
     and return them in frames.
 
@@ -769,8 +769,10 @@ def extract_node_subframes(graph, nodes):
         The graph to extract features from.
     nodes : list[Tensor] or None
         Node IDs. If not None, the list length must be equal to the number of node types
-        in the graph. The returned frames store the node IDs in the ``dgl.NID`` field
-        unless it is None, which means the whole frame is shallow-copied.
+        in the graph. If None, the whole frame is shallow-copied.
+    store_ids : bool
+        If True, the returned frames will store :attr:`nodes` in the ``dgl.NID`` field
+        unless it is None.
 
     Returns
     -------
@@ -783,7 +785,8 @@ def extract_node_subframes(graph, nodes):
         node_frames = []
         for i, ind_nodes in enumerate(nodes):
             subf = graph._node_frames[i].subframe(ind_nodes)
-            subf[NID] = ind_nodes
+            if store_ids:
+                subf[NID] = ind_nodes
             node_frames.append(subf)
     return node_frames
 
@@ -823,7 +826,7 @@ def extract_node_subframes_for_block(graph, srcnodes, dstnodes):
         node_frames.append(subf)
     return node_frames
 
-def extract_edge_subframes(graph, edges):
+def extract_edge_subframes(graph, edges, store_ids=True):
     """Extract edge features of the given edges from :attr:`graph`
     and return them in frames.
 
@@ -838,8 +841,10 @@ def extract_edge_subframes(graph, edges):
         The graph to extract features from.
     edges : list[Tensor] or None
         Edge IDs. If not None, the list length must be equal to the number of edge types
-        in the graph. The returned frames store the edge IDs in the ``dgl.NID`` field
-        unless it is None, which means the whole frame is shallow-copied.
+        in the graph. If None, the whole frame is shallow-copied.
+    store_ids : bool
+        If True, the returned frames will store :attr:`edges` in the ``dgl.EID`` field
+        unless it is None.
 
     Returns
     -------
@@ -852,7 +857,8 @@ def extract_edge_subframes(graph, edges):
         edge_frames = []
         for i, ind_edges in enumerate(edges):
             subf = graph._edge_frames[i].subframe(ind_edges)
-            subf[EID] = ind_edges
+            if store_ids:
+                subf[EID] = ind_edges
             edge_frames.append(subf)
     return edge_frames
 

tests/compute/test_removal.py

-import os
 import backend as F
-import networkx as nx
 import numpy as np
 import dgl
 from test_utils import parametrize_dtype
@@ -18,6 +16,8 @@ def test_node_removal(idtype):
     g.remove_nodes(range(4, 7))
     assert g.number_of_nodes() == 7
     assert F.array_equal(g.ndata['id'], F.tensor([0, 1, 2, 3, 7, 8, 9]))
+    assert dgl.NID not in g.ndata
+    assert dgl.EID not in g.edata
 
     # add nodes
     g.add_nodes(3)
@@ -25,9 +25,11 @@ def test_node_removal(idtype):
     assert F.array_equal(g.ndata['id'], F.tensor([0, 1, 2, 3, 7, 8, 9, 0, 0, 0]))
 
     # remove nodes
-    g.remove_nodes(range(1, 4))
+    g.remove_nodes(range(1, 4), store_ids=True)
     assert g.number_of_nodes() == 7
     assert F.array_equal(g.ndata['id'], F.tensor([0, 7, 8, 9, 0, 0, 0]))
+    assert dgl.NID in g.ndata
+    assert dgl.EID in g.edata
 
 @parametrize_dtype
 def test_multigraph_node_removal(idtype):
@@ -99,6 +101,8 @@ def test_edge_removal(idtype):
     assert g.number_of_nodes() == 5
     assert g.number_of_edges() == 18
     assert F.array_equal(g.edata['id'], F.tensor(list(range(13)) + list(range(20, 25))))
+    assert dgl.NID not in g.ndata
+    assert dgl.EID not in g.edata
 
     # add edges
     g.add_edge(3, 3)
@@ -107,10 +111,12 @@ def test_edge_removal(idtype):
     assert F.array_equal(g.edata['id'], F.tensor(list(range(13)) + list(range(20, 25)) + [0]))
 
     # remove edges
-    g.remove_edges(range(2, 10))
+    g.remove_edges(range(2, 10), store_ids=True)
     assert g.number_of_nodes() == 5
     assert g.number_of_edges() == 11
     assert F.array_equal(g.edata['id'], F.tensor([0, 1, 10, 11, 12, 20, 21, 22, 23, 24, 0]))
+    assert dgl.NID in g.ndata
+    assert dgl.EID in g.edata
 
 @parametrize_dtype
 def test_node_and_edge_removal(idtype):