updated MG Test code to not use DiGraph (#2213)

replace all DiGraph with Graph(directed=True)

Set some test to run on single GPU

Authors:
  - Brad Rees (https://github.com/BradReesWork)

Approvers:
  - Don Acosta (https://github.com/acostadon)
  - Joseph Nke (https://github.com/jnke2016)
  - Rick Ratzel (https://github.com/rlratzel)

URL: #2213

python/cugraph/cugraph/tests/dask/test_mg_bfs.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2021, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -13,17 +13,17 @@
 
 import cugraph.dask as dcg
 import gc
-import pytest
+# import pytest
 import cugraph
 import dask_cudf
 import cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests.utils import RAPIDS_DATASET_ROOT_DIR_PATH
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_bfs(dask_client):
     gc.collect()
 
@@ -60,10 +60,10 @@ def modify_dataset(df):
 
     df = modify_dataset(df)
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, "src", "dst")
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst")
 
     expected_dist = cugraph.bfs(g, [0, 1000])
@@ -85,9 +85,9 @@ def modify_dataset(df):
     assert err == 0
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_bfs_multi_column_depthlimit(dask_client):
     gc.collect()
 
@@ -115,10 +115,10 @@ def test_dask_bfs_multi_column_depthlimit(dask_client):
     df['src_b'] = df['src_a'] + 1000
     df['dst_b'] = df['dst_a'] + 1000
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, ["src_a", "src_b"], ["dst_a", "dst_b"])
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, ["src_a", "src_b"], ["dst_a", "dst_b"])
 
     start = cudf.DataFrame()

python/cugraph/cugraph/tests/dask/test_mg_comms.py

@@ -13,17 +13,17 @@
 
 import cugraph.dask as dcg
 import gc
-import pytest
+# import pytest
 import cugraph
 import dask_cudf
 import cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests.utils import RAPIDS_DATASET_ROOT_DIR_PATH
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_pagerank(dask_client):
     gc.collect()
 

python/cugraph/cugraph/tests/dask/test_mg_connectivity.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2021, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -13,17 +13,17 @@
 
 import cugraph.dask as dcg
 import gc
-import pytest
+# import pytest
 import cugraph
 import dask_cudf
 import cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests.utils import RAPIDS_DATASET_ROOT_DIR_PATH
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_wcc(dask_client):
     gc.collect()
 
@@ -47,10 +47,10 @@ def test_dask_wcc(dask_client):
         dtype=["int32", "int32", "float32"],
     )
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, "src", "dst", renumber=True)
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst")
 
     expected_dist = cugraph.weakly_connected_components(g)

python/cugraph/cugraph/tests/dask/test_mg_degree.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2018-2021, NVIDIA CORPORATION.
+# Copyright (c) 2018-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -49,10 +49,10 @@ def test_dask_mg_degree(dask_client):
         dtype=["int32", "int32", "float32"],
     )
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst")
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, "src", "dst")
 
     merge_df_in = (

python/cugraph/cugraph/tests/dask/test_mg_hits.py

@@ -16,7 +16,7 @@
 import pytest
 import cugraph
 import dask_cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests import utils
 
 # =============================================================================
@@ -97,9 +97,9 @@ def input_expected_output(input_combo):
 # =============================================================================
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_hits(dask_client, benchmark, input_expected_output):
 
     dg = input_expected_output["MGGraph"]

python/cugraph/cugraph/tests/dask/test_mg_louvain.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2021, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -17,7 +17,7 @@
 import cugraph
 import dask_cudf
 from cugraph.tests import utils
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 
 try:
     from rapids_pytest_benchmark import setFixtureParamNames
@@ -39,9 +39,9 @@ def setFixtureParamNames(*args, **kwargs):
 
 ###############################################################################
 # Fixtures
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 @pytest.fixture(scope="module",
                 params=utils.DATASETS_UNDIRECTED,
                 ids=[f"dataset={d.as_posix()}"
@@ -64,16 +64,16 @@ def daskGraphFromDataset(request, dask_client):
         dtype=["int32", "int32", "float32"],
     )
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst")
     return dg
 
 
 ###############################################################################
 # Tests
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_mg_louvain_with_edgevals(daskGraphFromDataset):
     # FIXME: daskGraphFromDataset returns a DiGraph, which Louvain is currently
     # accepting. In the future, an MNMG symmeterize will need to be called to

python/cugraph/cugraph/tests/dask/test_mg_pagerank.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2021, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -17,7 +17,7 @@
 import cugraph
 import dask_cudf
 import cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests.utils import RAPIDS_DATASET_ROOT_DIR_PATH
 
 
@@ -50,9 +50,9 @@ def personalize(vertices, personalization_perc):
 PERSONALIZATION_PERC = [0, 10, 50]
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 @pytest.mark.parametrize("personalization_perc", PERSONALIZATION_PERC)
 def test_dask_pagerank(dask_client, personalization_perc):
     gc.collect()
@@ -77,10 +77,10 @@ def test_dask_pagerank(dask_client, personalization_perc):
         dtype=["int32", "int32", "float32"],
     )
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, "src", "dst")
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst")
 
     personalization = None

python/cugraph/cugraph/tests/dask/test_mg_sssp.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2021, NVIDIA CORPORATION.
+# Copyright (c) 2020-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -13,17 +13,17 @@
 
 import cugraph.dask as dcg
 import gc
-import pytest
+# import pytest
 import cugraph
 import dask_cudf
 import cudf
-from cugraph.dask.common.mg_utils import is_single_gpu
+# from cugraph.dask.common.mg_utils import is_single_gpu
 from cugraph.tests.utils import RAPIDS_DATASET_ROOT_DIR_PATH
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_dask_sssp(dask_client):
     gc.collect()
 
@@ -47,10 +47,10 @@ def test_dask_sssp(dask_client):
         dtype=["int32", "int32", "float32"],
     )
 
-    g = cugraph.DiGraph()
+    g = cugraph.Graph(directed=True)
     g.from_cudf_edgelist(df, "src", "dst", "value", renumber=True)
 
-    dg = cugraph.DiGraph()
+    dg = cugraph.Graph(directed=True)
     dg.from_dask_cudf_edgelist(ddf, "src", "dst", "value")
 
     expected_dist = cugraph.sssp(g, 0)

python/cugraph/cugraph/tests/dask/test_mg_utility.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2018-2021, NVIDIA CORPORATION.
+# Copyright (c) 2018-2022, NVIDIA CORPORATION.
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
 # You may obtain a copy of the License at
@@ -35,9 +35,9 @@ def setup_function():
     gc.collect()
 
 
-@pytest.mark.skipif(
-    is_single_gpu(), reason="skipping MG testing on Single GPU system"
-)
+# @pytest.mark.skipif(
+#    is_single_gpu(), reason="skipping MG testing on Single GPU system"
+# )
 def test_from_edgelist(dask_client):
     input_data_path = (RAPIDS_DATASET_ROOT_DIR_PATH /
                        "karate.csv").as_posix()
@@ -53,9 +53,9 @@ def test_from_edgelist(dask_client):
 
     dg1 = cugraph.from_edgelist(
         ddf, source="src", destination="dst", edge_attr="value",
-        create_using=cugraph.DiGraph)
+        create_using=cugraph.Graph(directed=True))
 
-    dg2 = cugraph.DiGraph()
+    dg2 = cugraph.Graph(directed=True)
     dg2.from_dask_cudf_edgelist(
         ddf, source="src", destination="dst", edge_attr="value"
     )

python/cugraph/cugraph/tests/utils.py

@@ -20,12 +20,12 @@
 import networkx as nx
 import numpy as np
 import cupy as cp
-from cupyx.scipy.sparse.coo import coo_matrix as cp_coo_matrix
-from cupyx.scipy.sparse.csr import csr_matrix as cp_csr_matrix
-from cupyx.scipy.sparse.csc import csc_matrix as cp_csc_matrix
-from scipy.sparse.coo import coo_matrix as sp_coo_matrix
-from scipy.sparse.csr import csr_matrix as sp_csr_matrix
-from scipy.sparse.csc import csc_matrix as sp_csc_matrix
+from cupyx.scipy.sparse import coo_matrix as cp_coo_matrix
+from cupyx.scipy.sparse import csr_matrix as cp_csr_matrix
+from cupyx.scipy.sparse import csc_matrix as cp_csc_matrix
+from scipy.sparse import coo_matrix as sp_coo_matrix
+from scipy.sparse import csr_matrix as sp_csr_matrix
+from scipy.sparse import csc_matrix as sp_csc_matrix
 from pathlib import Path
 import cudf
 import dask_cudf

python/cugraph/cugraph/utilities/utils.py

@@ -24,9 +24,9 @@
 # optional dependencies
 try:
     import cupy as cp
-    from cupyx.scipy.sparse.coo import coo_matrix as cp_coo_matrix
-    from cupyx.scipy.sparse.csr import csr_matrix as cp_csr_matrix
-    from cupyx.scipy.sparse.csc import csc_matrix as cp_csc_matrix
+    from cupyx.scipy.sparse import coo_matrix as cp_coo_matrix
+    from cupyx.scipy.sparse import csr_matrix as cp_csr_matrix
+    from cupyx.scipy.sparse import csc_matrix as cp_csc_matrix
 
     __cp_matrix_types = [cp_coo_matrix, cp_csr_matrix, cp_csc_matrix]
     __cp_compressed_matrix_types = [cp_csr_matrix, cp_csc_matrix]
@@ -39,9 +39,9 @@
 
 try:
     import scipy as sp
-    from scipy.sparse.coo import coo_matrix as sp_coo_matrix
-    from scipy.sparse.csr import csr_matrix as sp_csr_matrix
-    from scipy.sparse.csc import csc_matrix as sp_csc_matrix
+    from scipy.sparse import coo_matrix as sp_coo_matrix
+    from scipy.sparse import csr_matrix as sp_csr_matrix
+    from scipy.sparse import csc_matrix as sp_csc_matrix
 
     __sp_matrix_types = [sp_coo_matrix, sp_csr_matrix, sp_csc_matrix]
     __sp_compressed_matrix_types = [sp_csr_matrix, sp_csc_matrix]