Add basic tests that smoked out a couple issues :)

python/nx-cugraph/nx_cugraph/convert_matrix.py

@@ -42,7 +42,7 @@ def from_pandas_edgelist(
         # Optimistically try to use cupy, but fall back to numpy if necessary
         src_array = src_series.to_cupy()
         dst_array = dst_series.to_cupy()
-    except (AttributeError, ValueError, NotImplementedError):
+    except (AttributeError, TypeError, ValueError, NotImplementedError):
         src_array = src_series.to_numpy()
         dst_array = dst_series.to_numpy()
     try:
@@ -77,9 +77,13 @@ def from_pandas_edgelist(
         src_indices = cp.asarray(np_or_cp.searchsorted(nodes, src_array), index_dtype)
         dst_indices = cp.asarray(np_or_cp.searchsorted(nodes, dst_array), index_dtype)
     else:
-        if not is_src_copied:
+        if is_src_copied:
+            src_indices = src_array
+        else:
             src_indices = cp.array(src_array)
-        if not is_dst_copied:
+        if is_dst_copied:
+            dst_indices = dst_array
+        else:
             dst_indices = cp.array(dst_array)
 
     if not graph_class.is_directed():

python/nx-cugraph/nx_cugraph/tests/test_convert_matrix.py

@@ -0,0 +1,82 @@
+# Copyright (c) 2024, 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
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import pandas as pd
+import pytest
+
+import nx_cugraph as nxcg
+from nx_cugraph.utils import _cp_iscopied_asarray
+
+try:
+    import cudf
+except ModuleNotFoundError:
+    cudf = None
+
+
+data = [
+    {"source": [0, 1], "target": [1, 2]},  # nodes are 0, 1, 2
+    {"source": [0, 1], "target": [1, 3]},  # nodes are 0, 1, 3 (need renumbered!)
+    {"source": ["a", "b"], "target": ["b", "c"]},  # nodes are 'a', 'b', 'c'
+]
+
+
+@pytest.mark.skipif("not cudf")
+@pytest.mark.parametrize("data", data)
+def test_from_cudf_edgelist(data):
+    df = cudf.DataFrame(data)
+    nxcg.from_pandas_edgelist(df)  # Basic smoke test
+    source = df["source"]
+    if source.dtype == int:
+        is_copied, src_array = _cp_iscopied_asarray(source)
+        assert is_copied is False
+        is_copied, src_array = _cp_iscopied_asarray(source.to_cupy())
+        assert is_copied is False
+        is_copied, src_array = _cp_iscopied_asarray(source, orig_object=source)
+        assert is_copied is False
+        is_copied, src_array = _cp_iscopied_asarray(
+            source.to_cupy(), orig_object=source
+        )
+        assert is_copied is False
+        # to numpy
+        is_copied, src_array = _cp_iscopied_asarray(source.to_numpy())
+        assert is_copied is True
+        is_copied, src_array = _cp_iscopied_asarray(
+            source.to_numpy(), orig_object=source
+        )
+        assert is_copied is True
+    else:
+        with pytest.raises(TypeError):
+            _cp_iscopied_asarray(source)
+        with pytest.raises(TypeError):
+            _cp_iscopied_asarray(source.to_cupy())
+        with pytest.raises(ValueError, match="Unsupported dtype"):
+            _cp_iscopied_asarray(source.to_numpy())
+        with pytest.raises(ValueError, match="Unsupported dtype"):
+            _cp_iscopied_asarray(source.to_numpy(), orig_object=source)
+
+
+@pytest.mark.parametrize("data", data)
+def test_from_pandas_edgelist(data):
+    df = pd.DataFrame(data)
+    nxcg.from_pandas_edgelist(df)  # Basic smoke test
+    source = df["source"]
+    if source.dtype == int:
+        is_copied, src_array = _cp_iscopied_asarray(source)
+        assert is_copied is True
+        is_copied, src_array = _cp_iscopied_asarray(source, orig_object=source)
+        assert is_copied is True
+        is_copied, src_array = _cp_iscopied_asarray(source.to_numpy())
+        assert is_copied is True
+        is_copied, src_array = _cp_iscopied_asarray(
+            source.to_numpy(), orig_object=source
+        )
+        assert is_copied is True