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[BUG] Critical: Fix cuGraph-PyG Edge Index Renumbering for Single-Edge Graphs #3605

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merged 3 commits into from
May 26, 2023
Merged

[BUG] Critical: Fix cuGraph-PyG Edge Index Renumbering for Single-Edge Graphs #3605

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272bf87
add store
alexbarghi-nv May 24, 2023
723d05e
Merge branch 'branch-23.06' into cugraph-pyg-fix-shortcut
alexbarghi-nv May 24, 2023
94406dd
Merge branch 'branch-23.06' into cugraph-pyg-fix-shortcut
alexbarghi-nv May 26, 2023
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29 changes: 19 additions & 10 deletions python/cugraph-pyg/cugraph_pyg/data/cugraph_store.py
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Original file line number Diff line number Diff line change
Expand Up @@ -696,7 +696,7 @@ def _get_vertex_groups_from_sample(

vtypes = cudf.Series(self.__vertex_type_offsets["type"])
if len(vtypes) == 1:
noi_index[vtypes[0]] = nodes_of_interest
noi_index[vtypes.iloc[0]] = nodes_of_interest
else:
noi_type_indices = torch.searchsorted(
torch.as_tensor(self.__vertex_type_offsets["stop"], device="cuda"),
Expand Down Expand Up @@ -788,17 +788,26 @@ def _get_renumbered_edge_groups_from_sample(
t_pyg_type = list(self.__edge_types_to_attrs.values())[0].edge_type
src_type, _, dst_type = t_pyg_type

sources = torch.as_tensor(sampling_results.sources.values, device="cuda")
src_id_table = noi_index[src_type]
src = torch.searchsorted(src_id_table, sources)
row_dict[t_pyg_type] = src
dst_id_table = noi_index[dst_type]
dst_id_map = (
cudf.Series(cupy.asarray(dst_id_table), name="dst")
.reset_index()
.rename(columns={"index": "new_id"})
.set_index("dst")
)
dst = dst_id_map["new_id"].loc[sampling_results.destinations]
col_dict[t_pyg_type] = torch.as_tensor(dst.values, device="cuda")

destinations = torch.as_tensor(
sampling_results.destinations.values, device="cuda"
src_id_table = noi_index[src_type]
src_id_map = (
cudf.Series(cupy.asarray(src_id_table), name="src")
.reset_index()
.rename(columns={"index": "new_id"})
.set_index("src")
)
dst_id_table = noi_index[dst_type]
dst = torch.searchsorted(dst_id_table, destinations)
col_dict[t_pyg_type] = dst
src = src_id_map["new_id"].loc[sampling_results.sources]
row_dict[t_pyg_type] = torch.as_tensor(src.values, device="cuda")

else:
# This will retrieve the single string representation.
# It needs to be converted to a tuple in the for loop below.
Expand Down