fix style

rapidsai · Jan 13, 2025 · f0e3b0f · f0e3b0f
1 parent af3b31f
commit f0e3b0f
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Showing 3 changed files with 18 additions and 35 deletions.
diff --git a/python/cugraph/cugraph/dask/sampling/biased_random_walks.py b/python/cugraph/cugraph/dask/sampling/biased_random_walks.py
@@ -32,10 +32,8 @@
 
 
 def convert_to_cudf(
-    cp_paths: cp.ndarray,
-    number_map=None,
-    is_vertex_paths: bool = False
-    ) -> cudf.Series:
+    cp_paths: cp.ndarray, number_map=None, is_vertex_paths: bool = False
+) -> cudf.Series:
     """
     Creates cudf Series from cupy arrays from pylibcugraph wrapper
     """
@@ -55,12 +53,8 @@ def convert_to_cudf(
 
 
 def _call_plc_biased_random_walks(
-    sID: bytes,
-    mg_graph_x,
-    st_x: cudf.Series,
-    max_depth: int,
-    random_state: int
-    ) -> Tuple[cp.ndarray, cp.ndarray]:
+    sID: bytes, mg_graph_x, st_x: cudf.Series, max_depth: int, random_state: int
+) -> Tuple[cp.ndarray, cp.ndarray]:
 
     return pylibcugraph_biased_random_walks(
         resource_handle=ResourceHandle(Comms.get_handle(sID).getHandle()),
@@ -73,10 +67,9 @@ def _call_plc_biased_random_walks(
 
 def biased_random_walks(
     input_graph,
-    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series
-    ] = None,
+    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series] = None,
     max_depth: int = 1,
-    random_state: int = None
+    random_state: int = None,
 ) -> Tuple[Union[dask_cudf.Series, dask_cudf.DataFrame], dask_cudf.Series, int]:
     """
     compute random walks under the biased sampling framework for each nodes in

diff --git a/python/cugraph/cugraph/dask/sampling/node2vec_random_walks.py b/python/cugraph/cugraph/dask/sampling/node2vec_random_walks.py
@@ -31,10 +31,8 @@
 
 
 def convert_to_cudf(
-    cp_paths: cp.ndarray,
-    number_map=None,
-    is_vertex_paths: bool = False
-    ) -> cudf.Series:
+    cp_paths: cp.ndarray, number_map=None, is_vertex_paths: bool = False
+) -> cudf.Series:
     """
     Creates cudf Series from cupy arrays from pylibcugraph wrapper
     """
@@ -58,9 +56,9 @@ def _call_plc_node2vec_random_walks(
     mg_graph_x,
     st_x: cudf.Series,
     max_depth: int,
-    p: float, 
+    p: float,
     q: float,
-    random_state: int
+    random_state: int,
 ) -> Tuple[cp.ndarray, cp.ndarray]:
 
     return pylibcugraph_node2vec_random_walks(
@@ -76,12 +74,11 @@ def _call_plc_node2vec_random_walks(
 
 def node2vec_random_walks(
     input_graph,
-    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series
-    ] = None,
+    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series] = None,
     max_depth: int = 1,
     p: float = 1.0,
     q: float = 1.0,
-    random_state: int = None
+    random_state: int = None,
 ) -> Tuple[Union[dask_cudf.Series, dask_cudf.DataFrame], dask_cudf.Series, int]:
     """
     compute random walks under the node2vec sampling framework for each nodes in

diff --git a/python/cugraph/cugraph/dask/sampling/uniform_random_walks.py b/python/cugraph/cugraph/dask/sampling/uniform_random_walks.py
@@ -32,10 +32,8 @@
 
 
 def convert_to_cudf(
-    cp_paths: cp.ndarray,
-    number_map=None,
-    is_vertex_paths: bool = False
-    ) -> cudf.Series:
+    cp_paths: cp.ndarray, number_map=None, is_vertex_paths: bool = False
+) -> cudf.Series:
     """
     Creates cudf Series from cupy arrays from pylibcugraph wrapper
     """
@@ -55,12 +53,8 @@ def convert_to_cudf(
 
 
 def _call_plc_uniform_random_walks(
-    sID: bytes,
-    mg_graph_x,
-    st_x: cudf.Series,
-    max_depth: int,
-    random_state: int
-    ) -> Tuple[cp.ndarray, cp.ndarray]:
+    sID: bytes, mg_graph_x, st_x: cudf.Series, max_depth: int, random_state: int
+) -> Tuple[cp.ndarray, cp.ndarray]:
 
     return pylibcugraph_uniform_random_walks(
         resource_handle=ResourceHandle(Comms.get_handle(sID).getHandle()),
@@ -73,10 +67,9 @@ def _call_plc_uniform_random_walks(
 
 def uniform_random_walks(
     input_graph,
-    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series
-    ] = None,
+    start_vertices: Union[int, list, cudf.Series, cudf.DataFrame, cudf.Series] = None,
     max_depth: int = 1,
-    random_state: int = None
+    random_state: int = None,
 ) -> Tuple[Union[dask_cudf.Series, dask_cudf.DataFrame], dask_cudf.Series, int]:
     """
     compute random walks under the uniform sampling framework for each nodes in