sym_src, sym_dst, sym_w = cugraph.symmetrize(
cu_M["0"], cu_M["1"], cu_M["2"]
)
compare(cu_M["0"], cu_M["1"], cu_M["2"], sym_src, sym_dst, sym_w)
@pytest.fixture(scope="module")
def client_connection():
(cluster, client) = setup_local_dask_cluster(p2p=True)
yield client
teardown_local_dask_cluster(cluster, client)
@pytest.mark.skipif(
is_single_gpu(), reason="skipping MG testing on Single GPU system"
)
@pytest.mark.parametrize("graph_file", utils.DATASETS_UNDIRECTED)
def test_mg_symmetrize(graph_file, client_connection):
gc.collect()
ddf = utils.read_dask_cudf_csv_file(graph_file)
sym_src, sym_dst = cugraph.symmetrize(ddf["src"], ddf["dst"])
# convert to regular cudf to facilitate comparison
df = ddf.compute()
compare(
df["src"], df["dst"], None, sym_src.compute(), sym_dst.compute(), None
)
@pytest.fixture
def client_connection():
cluster = LocalCUDACluster()
client = Client(cluster)
Comms.initialize(p2p=True)
yield client
Comms.destroy()
client.close()
cluster.close()
@pytest.mark.skipif(is_single_gpu(),
reason="skipping MG testing on Single GPU system")
def test_dask_sssp(client_connection):
gc.collect()
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"],
)
import pytest
import cudf
import dask_cudf
from cugraph.dask.common.mg_utils import (is_single_gpu,
setup_local_dask_cluster,
teardown_local_dask_cluster)
from cugraph.generators import rmat
import cugraph
##############################################################################
_cluster = None
_client = None
_is_single_gpu = is_single_gpu()
_visible_devices = None
_scale_values = [2, 4, 16]
_scale_test_ids = [f"scale={x}" for x in _scale_values]
_mg_values = [False, True]
_mg_test_ids = [f"mg={x}" for x in _mg_values]
_graph_types = [cugraph.Graph, cugraph.DiGraph, None, int]
_graph_test_ids = [
f"create_using={getattr(x,'__name__',str(x))}" for x in _graph_types
]
def _call_rmat(scale, num_edges, create_using, mg):
"""
Simplifies calling RMAT by requiring only specific args that are varied by
these tests and hard-coding all others.
