def client_connection():
cluster = LocalCUDACluster()
client = Client(cluster)
Comms.initialize(p2p=True)
yield client
Comms.destroy()
client.close()
cluster.close()
def client_connection():
# setup
cluster = LocalCUDACluster()
client = Client(cluster)
Comms.initialize()
yield client
# teardown
Comms.destroy()
client.close()
cluster.close()
def test_dask_bfs():
gc.collect()
cluster = LocalCUDACluster()
client = Client(cluster)
Comms.initialize()
input_data_path = r"../datasets/netscience.csv"
chunksize = dcg.get_chunksize(input_data_path)
ddf = dask_cudf.read_csv(input_data_path,
chunksize=chunksize,
delimiter=' ',
names=['src', 'dst', 'value'],
dtype=['int32', 'int32', 'float32'])
df = cudf.read_csv(input_data_path,
delimiter=' ',
names=['src', 'dst', 'value'],
dtype=['int32', 'int32', 'float32'])
g = cugraph.DiGraph()
g.from_cudf_edgelist(df, 'src', 'dst', renumber=True)
dg = cugraph.DiGraph()
dg.from_dask_cudf_edgelist(ddf, renumber=True)
expected_dist = cugraph.bfs(g, 0)
result_dist = dcg.bfs(dg, 0, True)
compare_dist = expected_dist.merge(result_dist,
on="vertex",
suffixes=['_local', '_dask'])
err = 0
for i in range(len(compare_dist)):
if (compare_dist['distance_local'].iloc[i] !=
compare_dist['distance_dask'].iloc[i]):
err = err + 1
assert err == 0
Comms.destroy()
client.close()
cluster.close()
def _close(self):
Comms.destroy()
if self._client is not None:
self._client.close()
if self._cluster is not None:
self._cluster.close()
