style

python/cugraph/cugraph/dask/sampling/uniform_neighbor_sample.py

@@ -317,11 +317,11 @@ def _call_plc_uniform_neighbor_sample_legacy(
         random_state=random_state,
         return_hops=return_hops,
     )
-    
+
     output = convert_to_cudf(
         cp_arrays, weight_t, with_edge_properties, return_offsets=return_offsets
     )
-    
+
     if isinstance(output, (list, tuple)) and len(output) == 1:
         return output[0]
     return output

python/cugraph/cugraph/gnn/data_loading/bulk_sampler.py

@@ -42,7 +42,7 @@ def __init__(
         graph,
         seeds_per_call: int = 200_000,
         batches_per_partition: int = 100,
-        renumber: bool=False,
+        renumber: bool = False,
         log_level: int = None,
         **kwargs,
     ):
@@ -107,7 +107,7 @@ def batch_size(self) -> int:
     @property
     def batches_per_partition(self) -> int:
         return self.__batches_per_partition
-    
+
     @property
     def renumber(self) -> bool:
         return self.__renumber
@@ -254,7 +254,7 @@ def flush(self) -> None:
             with_batch_ids=True,
             with_edge_properties=True,
             return_offsets=True,
-            renumber=self.__renumber
+            renumber=self.__renumber,
         )
 
         if self.__renumber:
@@ -281,7 +281,9 @@ def flush(self) -> None:
         # Write batches to parquet
         self.__write(samples, offsets, renumber_map)
         if isinstance(self.__batches, dask_cudf.DataFrame):
-            futures = [f.release() for f in futures_of(samples)] + [f.release() for f in futures_of(offsets)]
+            futures = [f.release() for f in futures_of(samples)] + [
+                f.release() for f in futures_of(offsets)
+            ]
             if renumber_map is not None:
                 futures += [f.release() for f in futures_of(renumber_map)]
             wait(futures)

python/cugraph/cugraph/gnn/data_loading/bulk_sampler_io.py

@@ -103,7 +103,9 @@ def _write_samples_to_parquet(
             renumber_map_o = cudf.concat(
                 [
                     offsets_p.renumber_map_offsets + map_offset,
-                    cudf.Series([len(renumber_map_p) + len(offsets_p) + 1], dtype="int32"),
+                    cudf.Series(
+                        [len(renumber_map_p) + len(offsets_p) + 1], dtype="int32"
+                    ),
                 ]
             )
 

python/cugraph/cugraph/tests/sampling/test_bulk_sampler.py

@@ -60,7 +60,7 @@ def test_bulk_sampler_simple(scratch_dir):
     bs.flush()
 
     recovered_samples = cudf.read_parquet(samples_path)
-    assert 'map' not in recovered_samples.columns
+    assert "map" not in recovered_samples.columns
 
     for b in batches["batch"].unique().values_host.tolist():
         assert b in recovered_samples["batch_id"].values_host.tolist()
@@ -112,7 +112,7 @@ def test_bulk_sampler_remainder(scratch_dir):
     bs.flush()
 
     recovered_samples = cudf.read_parquet(samples_path)
-    assert 'map' not in recovered_samples.columns
+    assert "map" not in recovered_samples.columns
 
     for b in batches["batch"].unique().values_host.tolist():
         assert b in recovered_samples["batch_id"].values_host.tolist()
@@ -168,7 +168,7 @@ def test_bulk_sampler_large_batch_size(scratch_dir):
     bs.flush()
 
     recovered_samples = cudf.read_parquet(samples_path)
-    assert 'map' not in recovered_samples.columns
+    assert "map" not in recovered_samples.columns
 
     for b in batches["batch"].unique().values_host.tolist():
         assert b in recovered_samples["batch_id"].values_host.tolist()

python/cugraph/cugraph/tests/sampling/test_bulk_sampler_mg.py

@@ -64,7 +64,7 @@ def test_bulk_sampler_simple(dask_client, scratch_dir):
     bs.flush()
 
     recovered_samples = cudf.read_parquet(samples_path)
-    assert 'map' not in recovered_samples.columns
+    assert "map" not in recovered_samples.columns
 
     for b in batches["batch"].unique().compute().values_host.tolist():
         assert b in recovered_samples["batch_id"].values_host.tolist()
@@ -108,7 +108,7 @@ def test_bulk_sampler_mg_graph_sg_input(dask_client, scratch_dir):
     bs.flush()
 
     recovered_samples = cudf.read_parquet(samples_path)
-    assert 'map' not in recovered_samples.columns
+    assert "map" not in recovered_samples.columns
 
     for b in batches["batch"].unique().values_host.tolist():
         assert b in recovered_samples["batch_id"].values_host.tolist()