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2026-07-13 13:35:51 +08:00

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Python

# NOTE(vibwu): Currently cugraph must be imported before torch to avoid a resource cleanup issue.
# See https://github.com/rapidsai/cugraph/issues/2718
import cugraph # usort: skip
import backend as F
import dgl
def test_dummy():
cg = cugraph.Graph()
assert cg is not None
def test_to_cugraph_conversion():
g = dgl.graph((F.tensor([0, 1, 2, 3]), F.tensor([1, 0, 3, 2]))).to("cuda")
cugraph_g = g.to_cugraph()
assert cugraph_g.number_of_nodes() == g.num_nodes()
assert cugraph_g.number_of_edges() == g.num_edges()
assert cugraph_g.has_edge(0, 1)
assert cugraph_g.has_edge(1, 0)
assert cugraph_g.has_edge(3, 2)
def test_from_cugraph_conversion():
# cudf is a dependency of cugraph
import cudf
# directed graph conversion test
cugraph_g = cugraph.Graph(directed=True)
df = cudf.DataFrame({"source": [0, 1, 2, 3], "destination": [1, 2, 3, 2]})
cugraph_g.from_cudf_edgelist(df)
g = dgl.from_cugraph(cugraph_g)
assert g.device.type == "cuda"
assert g.num_nodes() == cugraph_g.number_of_nodes()
assert g.num_edges() == cugraph_g.number_of_edges()
# assert reverse edges are not present
assert g.has_edges_between(0, 1)
assert not g.has_edges_between(1, 0)
assert g.has_edges_between(1, 2)
assert not g.has_edges_between(2, 1)
assert g.has_edges_between(2, 3)
# undirected graph conversion test
cugraph_g = cugraph.Graph(directed=False)
df = cudf.DataFrame({"source": [0, 1, 2, 3], "destination": [1, 2, 3, 2]})
cugraph_g.from_cudf_edgelist(df)
g = dgl.from_cugraph(cugraph_g)
assert g.device.type == "cuda"
assert g.num_nodes() == cugraph_g.number_of_nodes()
# assert reverse edges are present
assert g.has_edges_between(0, 1)
assert g.has_edges_between(1, 0)
assert g.has_edges_between(1, 2)
assert g.has_edges_between(2, 1)
assert g.has_edges_between(2, 3)