chore: import upstream snapshot with attribution

2026-07-13 13:35:51 +08:00
commit c36a561cd8
2172 changed files with 455595 additions and 0 deletions
@@ -0,0 +1,36 @@
+import dgl.graphbolt as gb
+import pytest
+import torch
+from dgl import AddSelfLoop
+from dgl.data import AsNodePredDataset, CoraGraphDataset
+
+
+def test_LegacyDataset_homo_node_pred():
+    cora = CoraGraphDataset(transform=AddSelfLoop())
+    dataset = gb.LegacyDataset(cora)
+
+    # Check tasks.
+    assert len(dataset.tasks) == 1
+    task = dataset.tasks[0]
+    assert task.train_set.names == ("seeds", "labels")
+    assert len(task.train_set) == 140
+    assert task.validation_set.names == ("seeds", "labels")
+    assert len(task.validation_set) == 500
+    assert task.test_set.names == ("seeds", "labels")
+    assert len(task.test_set) == 1000
+    assert task.metadata["num_classes"] == 7
+
+    num_nodes = 2708
+    assert dataset.graph.num_nodes == num_nodes
+    assert len(dataset.all_nodes_set) == num_nodes
+    assert dataset.feature.size("node", None, "feat") == torch.Size([1433])
+    assert (
+        dataset.feature.read(
+            "node", None, "feat", torch.tensor([num_nodes - 1])
+        ).size(dim=0)
+        == 1
+    )
+    # Out of bound indexing results in segmentation fault instead of exception
+    # in CI. This may be related to docker env. Skip it for now.
+    # with pytest.raises(IndexError):
+    #    dataset.feature.read("node", None, "feat", torch.Tensor([num_nodes]))