dmlc--dgl
Hongzhi (Steve), Chen
f0759a96ee
* auto-format-test * more * remove --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>
65 行
1.9 KiB
Python
65 行
1.9 KiB
Python
# NOTE(vibwu): Currently cugraph must be imported before torch to avoid a resource cleanup issue.
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# See https://github.com/rapidsai/cugraph/issues/2718
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import cugraph # usort: skip
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import backend as F
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import dgl
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def test_dummy():
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cg = cugraph.Graph()
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assert cg is not None
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def test_to_cugraph_conversion():
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g = dgl.graph((F.tensor([0, 1, 2, 3]), F.tensor([1, 0, 3, 2]))).to("cuda")
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cugraph_g = g.to_cugraph()
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assert cugraph_g.number_of_nodes() == g.number_of_nodes()
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assert cugraph_g.number_of_edges() == g.number_of_edges()
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assert cugraph_g.has_edge(0, 1)
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assert cugraph_g.has_edge(1, 0)
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assert cugraph_g.has_edge(3, 2)
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def test_from_cugraph_conversion():
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# cudf is a dependency of cugraph
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import cudf
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# directed graph conversion test
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cugraph_g = cugraph.Graph(directed=True)
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df = cudf.DataFrame({"source": [0, 1, 2, 3], "destination": [1, 2, 3, 2]})
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cugraph_g.from_cudf_edgelist(df)
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g = dgl.from_cugraph(cugraph_g)
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assert g.device.type == "cuda"
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assert g.number_of_nodes() == cugraph_g.number_of_nodes()
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assert g.number_of_edges() == cugraph_g.number_of_edges()
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# assert reverse edges are not present
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assert g.has_edges_between(0, 1)
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assert not g.has_edges_between(1, 0)
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assert g.has_edges_between(1, 2)
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assert not g.has_edges_between(2, 1)
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assert g.has_edges_between(2, 3)
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# undirected graph conversion test
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cugraph_g = cugraph.Graph(directed=False)
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df = cudf.DataFrame({"source": [0, 1, 2, 3], "destination": [1, 2, 3, 2]})
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cugraph_g.from_cudf_edgelist(df)
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g = dgl.from_cugraph(cugraph_g)
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assert g.device.type == "cuda"
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assert g.number_of_nodes() == cugraph_g.number_of_nodes()
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# assert reverse edges are present
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assert g.has_edges_between(0, 1)
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assert g.has_edges_between(1, 0)
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assert g.has_edges_between(1, 2)
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assert g.has_edges_between(2, 1)
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assert g.has_edges_between(2, 3)
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