Merge branch 'master' into tagdataset/add-llm-exp-pred

test/metrics/test_link_pred_metric.py

@@ -221,3 +221,20 @@ def test_link_pred_metric_collection(num_src_nodes, num_dst_nodes, num_edges):
     metric_collection.update(pred_index_mat, edge_label_index)
     assert metric_collection.compute() == expected
     metric_collection.reset()
+
+
+def test_empty_ground_truth():
+    pred = torch.rand(10, 5)
+    pred_index_mat = pred.argsort(dim=1)
+    edge_label_index = torch.empty(2, 0, dtype=torch.long)
+    edge_label_weight = torch.empty(0)
+
+    metric = LinkPredMAP(k=5)
+    metric.update(pred_index_mat, edge_label_index)
+    assert metric.compute() == 0
+    metric.reset()
+
+    metric = LinkPredNDCG(k=5, weighted=True)
+    metric.update(pred_index_mat, edge_label_index, edge_label_weight)
+    assert metric.compute() == 0
+    metric.reset()

torch_geometric/metrics/link_pred.py

@@ -30,6 +30,14 @@ def pred_rel_mat(self) -> Tensor:
         if hasattr(self, '_pred_rel_mat'):
             return self._pred_rel_mat  # type: ignore
 
+        if self.edge_label_index[1].numel() == 0:
+            self._pred_rel_mat = torch.zeros_like(
+                self.pred_index_mat,
+                dtype=torch.bool if self.edge_label_weight is None else
+                torch.get_default_dtype(),
+            )
+            return self._pred_rel_mat
+
         # Flatten both prediction and ground-truth indices, and determine
         # overlaps afterwards via `torch.searchsorted`.
         max_index = max(  # type: ignore