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[HOTFIX] Updates cudf usage for compatibility with cudf>=23.10.1 #4007

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2 changes: 1 addition & 1 deletion ci/test_python.sh
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,7 @@ rapids-mamba-retry install \
--channel "${PYTHON_CHANNEL}" \
libcugraph \
pylibcugraph \
cugraph \
"${PYTHON_CHANNEL}"::cugraph \
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nx-cugraph \
cugraph-service-server \
cugraph-service-client
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5 changes: 5 additions & 0 deletions ci/test_wheel_nx-cugraph.sh
Original file line number Diff line number Diff line change
Expand Up @@ -3,4 +3,9 @@

set -eoxu pipefail

# Download the pylibcugraph built in the previous step
RAPIDS_PY_CUDA_SUFFIX="$(rapids-wheel-ctk-name-gen ${RAPIDS_CUDA_VERSION})"
RAPIDS_PY_WHEEL_NAME="pylibcugraph_${RAPIDS_PY_CUDA_SUFFIX}" rapids-download-wheels-from-s3 ./local-pylibcugraph-dep
python -m pip install --no-deps ./local-pylibcugraph-dep/pylibcugraph*.whl

./ci/test_wheel.sh nx-cugraph python/nx-cugraph
24 changes: 6 additions & 18 deletions python/cugraph/cugraph/structure/property_graph.py
Original file line number Diff line number Diff line change
Expand Up @@ -800,15 +800,9 @@ def add_vertex_data(
tmp_df.index = tmp_df.index.rename(self.vertex_col_name)

# FIXME: handle case of a type_name column already being in tmp_df
if self.__series_type is cudf.Series:
# cudf does not yet support initialization with a scalar
tmp_df[TCN] = cudf.Series(
cudf.Series([type_name], dtype=cat_dtype).repeat(len(tmp_df)),
index=tmp_df.index,
)
else:
# pandas is oddly slow if dtype is passed to the constructor here
tmp_df[TCN] = pd.Series(type_name, index=tmp_df.index).astype(cat_dtype)
tmp_df[TCN] = self.__series_type(type_name, index=tmp_df.index).astype(
cat_dtype
)

if property_columns:
# all columns
Expand Down Expand Up @@ -1207,15 +1201,9 @@ def add_edge_data(
tmp_df[self.src_col_name] = tmp_df[vertex_col_names[0]]
tmp_df[self.dst_col_name] = tmp_df[vertex_col_names[1]]

if self.__series_type is cudf.Series:
# cudf does not yet support initialization with a scalar
tmp_df[TCN] = cudf.Series(
cudf.Series([type_name], dtype=cat_dtype).repeat(len(tmp_df)),
index=tmp_df.index,
)
else:
# pandas is oddly slow if dtype is passed to the constructor here
tmp_df[TCN] = pd.Series(type_name, index=tmp_df.index).astype(cat_dtype)
tmp_df[TCN] = self.__series_type(type_name, index=tmp_df.index).astype(
cat_dtype
)

# Add unique edge IDs to the new rows. This is just a count for each
# row starting from the last edge ID value, with initial edge ID 0.
Expand Down
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