Re-enable optimization

python/cugraph/cugraph/structure/graph_implementation/simpleDistributedGraph.py

@@ -14,6 +14,7 @@
 import gc
 from typing import Union
 import warnings
+import random
 
 import cudf
 import cupy as cp
@@ -182,7 +183,9 @@ def __from_edgelist(
         # Repartition to 2 partitions per GPU for memory efficient process
         input_ddf = input_ddf.repartition(npartitions=len(workers) * 2)
         # FIXME: Make a copy of the input ddf before implicitly altering it.
-        input_ddf = input_ddf.map_partitions(lambda df: df.copy())
+        input_ddf = input_ddf.map_partitions(
+            lambda df: df.copy(), token="custom-" + str(random.random())
+        )
         # The dataframe will be symmetrized iff the graph is undirected
         # otherwise, the inital dataframe will be returned
         if edge_attr is not None:

python/cugraph/cugraph/tests/traversal/test_bfs_mg.py

@@ -12,6 +12,7 @@
 # limitations under the License.
 
 import gc
+import random
 
 import pytest
 
@@ -61,7 +62,9 @@ def modify_dataset(df):
         return cudf.concat([df, temp_df])
 
     meta = ddf._meta
-    ddf = ddf.map_partitions(modify_dataset, meta=meta)
+    ddf = ddf.map_partitions(
+        modify_dataset, meta=meta, token="custom-" + str(random.random())
+    )
 
     df = cudf.read_csv(
         input_data_path,