Add check on add_self_loops in HeteroConv and to_hetero

CHANGELOG.md

@@ -5,6 +5,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [2.0.5] - 2022-MM-DD
 ### Added
+- Added a check in `HeteroConv` and `to_hetero()` to ensure that `MessagePassing.add_self_loops` is disabled ([4647](https://github.com/pyg-team/pytorch_geometric/pull/4647))
 - Added `HeteroData.subgraph()` support ([#4635](https://github.com/pyg-team/pytorch_geometric/pull/4635))
 - Added the `AQSOL` dataset ([#4626](https://github.com/pyg-team/pytorch_geometric/pull/4626))
 - Added `HeteroData.node_items()` and `HeteroData.edge_items()` functionality ([#4644](https://github.com/pyg-team/pytorch_geometric/pull/4644))

test/nn/conv/test_hetero_conv.py

@@ -32,7 +32,8 @@ def test_hetero_conv(aggr):
         {
             ('paper', 'to', 'paper'): GCNConv(-1, 64),
             ('author', 'to', 'paper'): SAGEConv((-1, -1), 64),
-            ('paper', 'to', 'author'): GATConv((-1, -1), 64),
+            ('paper', 'to', 'author'): GATConv(
+                (-1, -1), 64, add_self_loops=False),
         }, aggr=aggr)
 
     assert len(list(conv.parameters())) > 0
@@ -77,3 +78,15 @@ def test_hetero_conv_with_custom_conv():
     assert len(out) == 2
     assert out['paper'].size() == (50, 64)
     assert out['author'].size() == (30, 64)
+
+
+class MessagePassingLoops(MessagePassing):
+    def __init__(self):
+        super().__init__()
+        self.add_self_loops = True
+
+
+def test_hetero_conv_self_loop_error():
+    HeteroConv({('a', 'to', 'a'): MessagePassingLoops()})
+    with pytest.raises(ValueError, match="incorrect message passing"):
+        HeteroConv({('a', 'to', 'b'): MessagePassingLoops()})

test/nn/test_to_hetero_transformer.py

@@ -1,5 +1,6 @@
 from typing import Tuple
 
+import pytest
 import torch
 from torch import Tensor
 from torch.nn import Linear, ReLU, Sequential
@@ -363,3 +364,28 @@ def test_graph_level_to_hetero():
     model = to_hetero(model, metadata, aggr='mean', debug=False)
     out = model(x_dict, edge_index_dict, batch_dict)
     assert out.size() == (1, 64)
+
+
+class MessagePassingLoops(MessagePassing):
+    def __init__(self):
+        super().__init__()
+        self.add_self_loops = True
+
+    def forward(self, x):
+        return x
+
+
+class ModelLoops(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.conv = MessagePassingLoops()
+
+    def forward(self, x):
+        return self.conv(x)
+
+
+def test_hetero_transformer_self_loop_error():
+    to_hetero(ModelLoops(), metadata=(['a'], [('a', 'to', 'a')]))
+    with pytest.raises(ValueError, match="incorrect message passing"):
+        to_hetero(ModelLoops(), metadata=(['a', 'b'], [('a', 'to', 'b'),
+                                                       ('b', 'to', 'a')]))

torch_geometric/nn/conv/hetero_conv.py

@@ -7,6 +7,7 @@
 
 from torch_geometric.nn.conv.hgt_conv import group
 from torch_geometric.typing import Adj, EdgeType, NodeType
+from torch_geometric.utils.hetero import check_add_self_loops
 
 
 class HeteroConv(Module):
@@ -47,6 +48,9 @@ def __init__(self, convs: Dict[EdgeType, Module],
                  aggr: Optional[str] = "sum"):
         super().__init__()
 
+        for edge_type, module in convs.items():
+            check_add_self_loops(module, [edge_type])
+
         src_node_types = set([key[0] for key in convs.keys()])
         dst_node_types = set([key[-1] for key in convs.keys()])
         if len(src_node_types - dst_node_types) > 0:

torch_geometric/nn/to_hetero_transformer.py

@@ -6,9 +6,12 @@
 import torch
 from torch.nn import Module
 
-from torch_geometric.nn.fx import Transformer
+from torch_geometric.nn.fx import Transformer, get_submodule
 from torch_geometric.typing import EdgeType, Metadata, NodeType
-from torch_geometric.utils.hetero import get_unused_node_types
+from torch_geometric.utils.hetero import (
+    check_add_self_loops,
+    get_unused_node_types,
+)
 
 try:
     from torch.fx import Graph, GraphModule, Node
@@ -168,6 +171,9 @@ def call_message_passing_module(self, node: Node, target: Any, name: str):
         # Add calls to edge type-wise `MessagePassing` modules and aggregate
         # the outputs to node type-wise embeddings afterwards.
 
+        module = get_submodule(self.module, target)
+        check_add_self_loops(module, self.metadata[1])
+
         # Group edge-wise keys per destination:
         key_name, keys_per_dst = {}, defaultdict(list)
         for key in self.metadata[1]:

torch_geometric/utils/hetero.py

@@ -47,3 +47,12 @@ def get_unused_node_types(node_types: List[NodeType],
                           edge_types: List[EdgeType]) -> Set[NodeType]:
     dst_node_types = set(edge_type[-1] for edge_type in edge_types)
     return set(node_types) - set(dst_node_types)
+
+
+def check_add_self_loops(module: torch.nn.Module, edge_types: List[EdgeType]):
+    is_bipartite = any([key[0] != key[-1] for key in edge_types])
+    if is_bipartite and getattr(module, 'add_self_loops', False):
+        raise ValueError(
+            f"'add_self_loops' attribute set to 'True' on module '{module}' "
+            f"for use with edge type(s) '{edge_types}'. This will lead to "
+            f"incorrect message passing results.")