chore: import upstream snapshot with attribution

tests/python/pytorch/nn/conv/test_gatedgcnconv.py

@@ -0,0 +1,26 @@
+import io
+
+import backend as F
+
+import dgl.nn.pytorch as nn
+import pytest
+from utils import parametrize_idtype
+from utils.graph_cases import get_cases
+
+tmp_buffer = io.BytesIO()
+
+
+@parametrize_idtype
+@pytest.mark.parametrize("g", get_cases(["homo"], exclude=["zero-degree"]))
+def test_gatedgcn_conv(g, idtype):
+    ctx = F.ctx()
+    g = g.astype(idtype).to(ctx)
+    gatedgcnconv = nn.GatedGCNConv(10, 10, 5)
+    feat = F.randn((g.num_nodes(), 10))
+    efeat = F.randn((g.num_edges(), 10))
+    gatedgcnconv = gatedgcnconv.to(ctx)
+
+    h, edge_h = gatedgcnconv(g, feat, efeat)
+    # current we only do shape check
+    assert h.shape == (g.number_of_dst_nodes(), 5)
+    assert edge_h.shape == (g.number_of_edges(), 5)