Branch 22.06 bug fixes + update imports (rapidsai#2261)

This PR:

1. Updates reference code in the html documentation to reflect recent changes from 22.02 and 22.04 (closes rapidsai#2248 )
2. Updates the default value of max_depth within node2vec, so that a call without a default max_depth value still yields a result (closes rapidsai#2228)
3. Casts a list of start_vertices to int32 type. (closes rapidsai#2229)
4. Remove experimental from list of imports from within pylibcugraph

Authors:
  - https://github.com/betochimas

Approvers:
  - Brad Rees (https://github.com/BradReesWork)
  - Rick Ratzel (https://github.com/rlratzel)
  - Joseph Nke (https://github.com/jnke2016)

URL: rapidsai#2261

docs/cugraph/source/api_docs/dask-cugraph.rst

@@ -37,7 +37,7 @@ Example
             names=['src', 'dst'], 
             dtype=['int32', 'int32'])
 
-    G = cugraph.DiGraph()
+    G = cugraph.Graph(directed=True)
     G.from_dask_cudf_edgelist(e_list, source='src', destination='dst')
 
     # now run PageRank

python/cugraph/cugraph/sampling/node2vec.py

@@ -11,19 +11,19 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from pylibcugraph.experimental import (ResourceHandle,
-                                       GraphProperties,
-                                       SGGraph,
-                                       node2vec as pylibcugraph_node2vec,
-                                       )
+from pylibcugraph import (ResourceHandle,
+                          GraphProperties,
+                          SGGraph,
+                          node2vec as pylibcugraph_node2vec,
+                          )
 from cugraph.utilities import ensure_cugraph_obj_for_nx
 
 import cudf
 
 
 def node2vec(G,
              start_vertices,
-             max_depth=None,
+             max_depth=1,
              compress_result=True,
              p=1.0,
              q=1.0):
@@ -49,8 +49,9 @@ def node2vec(G,
         the random walks. In case of multi-column vertices it should be
         a cudf.DataFrame. Only supports int32 currently.
 
-    max_depth: int
-        The maximum depth of the random walks
+    max_depth: int, optional (default=1)
+        The maximum depth of the random walks. If not specified, the maximum
+        depth is set to 1.
 
     compress_result: bool, optional (default=True)
         If True, coalesced paths are returned with a sizes array with offsets.
@@ -93,11 +94,11 @@ def node2vec(G,
 
     """
     if (not isinstance(max_depth, int)) or (max_depth < 1):
-        raise ValueError(f"'max_depth' must be a positive integer, \
-                        got: {max_depth}")
+        raise ValueError(f"'max_depth' must be a positive integer, "
+                         f"got: {max_depth}")
     if (not isinstance(compress_result, bool)):
-        raise ValueError(f"'compress_result' must be a bool, \
-                        got: {compress_result}")
+        raise ValueError(f"'compress_result' must be a bool, "
+                         f"got: {compress_result}")
     if (not isinstance(p, float)) or (p <= 0.0):
         raise ValueError(f"'p' must be a positive float, got: {p}")
     if (not isinstance(q, float)) or (q <= 0.0):
@@ -109,10 +110,10 @@ def node2vec(G,
         start_vertices = [start_vertices]
 
     if isinstance(start_vertices, list):
-        start_vertices = cudf.Series(start_vertices)
+        start_vertices = cudf.Series(start_vertices, dtype='int32')
         if start_vertices.dtype != 'int32':
-            raise ValueError(f"'start_vertices' must have int32 values, \
-                            got: {start_vertices.dtype}")
+            raise ValueError(f"'start_vertices' must have int32 values, "
+                             f"got: {start_vertices.dtype}")
 
     if G.renumbered is True:
         if isinstance(start_vertices, cudf.DataFrame):
@@ -126,8 +127,8 @@ def node2vec(G,
     weights = G.edgelist.edgelist_df['weights']
 
     if srcs.dtype != 'int32':
-        raise ValueError(f"Graph vertices must have int32 values, \
-                        got: {srcs.dtype}")
+        raise ValueError(f"Graph vertices must have int32 values, "
+                         f"got: {srcs.dtype}")
 
     resource_handle = ResourceHandle()
     graph_props = GraphProperties(is_multigraph=G.is_multigraph())

python/cugraph/cugraph/tests/test_node2vec.py

@@ -138,7 +138,7 @@ def test_node2vec_line(graph_file, directed):
 @pytest.mark.parametrize(*_get_param_args("graph_file", utils.DATASETS_SMALL))
 @pytest.mark.parametrize(*_get_param_args("directed", DIRECTED_GRAPH_OPTIONS))
 @pytest.mark.parametrize(*_get_param_args("compress", COMPRESSED))
-def test_node2vec_new(
+def test_node2vec(
     graph_file,
     directed,
     compress,

python/pylibcugraph/pylibcugraph/graphs.pyx

@@ -109,10 +109,10 @@ cdef class SGGraph(_GPUGraph):
     >>> dsts = cupy.asarray([1, 2, 3], dtype=numpy.int32)
     >>> seeds = cupy.asarray([0, 0, 1], dtype=numpy.int32)
     >>> weights = cupy.asarray([1.0, 1.0, 1.0], dtype=numpy.float32)
-    >>> resource_handle = pylibcugraph.experimental.ResourceHandle()
-    >>> graph_props = pylibcugraph.experimental.GraphProperties(
+    >>> resource_handle = pylibcugraph.ResourceHandle()
+    >>> graph_props = pylibcugraph.GraphProperties(
     ...     is_symmetric=False, is_multigraph=False)
-    >>> G = pylibcugraph.experimental.SGGraph(
+    >>> G = pylibcugraph.SGGraph(
     ...     resource_handle, graph_props, srcs, dsts, weights,
     ...     store_transposed=False, renumber=False, do_expensive_check=False)
 

python/pylibcugraph/pylibcugraph/node2vec.pyx

@@ -112,13 +112,13 @@ def node2vec(ResourceHandle resource_handle,
     >>> dsts = cupy.asarray([1, 2, 3], dtype=numpy.int32)
     >>> seeds = cupy.asarray([0, 0, 1], dtype=numpy.int32)
     >>> weights = cupy.asarray([1.0, 1.0, 1.0], dtype=numpy.float32)
-    >>> resource_handle = pylibcugraph.experimental.ResourceHandle()
-    >>> graph_props = pylibcugraph.experimental.GraphProperties(
+    >>> resource_handle = pylibcugraph.ResourceHandle()
+    >>> graph_props = pylibcugraph.GraphProperties(
     ...     is_symmetric=False, is_multigraph=False)
-    >>> G = pylibcugraph.experimental.SGGraph(
+    >>> G = pylibcugraph.SGGraph(
     ...     resource_handle, graph_props, srcs, dsts, weights,
     ...     store_transposed=False, renumber=False, do_expensive_check=False)
-    >>> (paths, weights, sizes) = pylibcugraph.experimental.node2vec(
+    >>> (paths, weights, sizes) = pylibcugraph.node2vec(
     ...                             resource_handle, G, seeds, 3, True, 1.0, 1.0)
 
     """

python/pylibcugraph/pylibcugraph/pagerank.pyx

@@ -121,13 +121,13 @@ def pagerank(ResourceHandle resource_handle,
     >>> srcs = cupy.asarray([0, 1, 2], dtype=numpy.int32)
     >>> dsts = cupy.asarray([1, 2, 3], dtype=numpy.int32)
     >>> weights = cupy.asarray([1.0, 1.0, 1.0], dtype=numpy.float32)
-    >>> resource_handle = pylibcugraph.experimental.ResourceHandle()
-    >>> graph_props = pylibcugraph.experimental.GraphProperties(
+    >>> resource_handle = pylibcugraph.ResourceHandle()
+    >>> graph_props = pylibcugraph.GraphProperties(
     ...     is_symmetric=False, is_multigraph=False)
-    >>> G = pylibcugraph.experimental.SGGraph(
+    >>> G = pylibcugraph.SGGraph(
     ...     resource_handle, graph_props, srcs, dsts, weights,
     ...     store_transposed=True, renumber=False, do_expensive_check=False)
-    >>> (vertices, pageranks) = pylibcugraph.experimental.pagerank(
+    >>> (vertices, pageranks) = pylibcugraph.pagerank(
     ...     resource_handle, G, None, alpha=0.85, epsilon=1.0e-6,
     ...     max_iterations=500, has_initial_guess=False,
     ...     do_expensive_check=False)

python/pylibcugraph/pylibcugraph/sssp.pyx

@@ -105,13 +105,13 @@ def sssp(ResourceHandle resource_handle,
     >>> srcs = cupy.asarray([0, 1, 2], dtype=numpy.int32)
     >>> dsts = cupy.asarray([1, 2, 3], dtype=numpy.int32)
     >>> weights = cupy.asarray([1.0, 1.0, 1.0], dtype=numpy.float32)
-    >>> resource_handle = pylibcugraph.experimental.ResourceHandle()
-    >>> graph_props = pylibcugraph.experimental.GraphProperties(
+    >>> resource_handle = pylibcugraph.ResourceHandle()
+    >>> graph_props = pylibcugraph.GraphProperties(
     ...     is_symmetric=False, is_multigraph=False)
-    >>> G = pylibcugraph.experimental.SGGraph(
+    >>> G = pylibcugraph.SGGraph(
     ...     resource_handle, graph_props, srcs, dsts, weights,
     ...     store_transposed=False, renumber=False, do_expensive_check=False)
-    >>> (vertices, distances, predecessors) = pylibcugraph.experimental.sssp(
+    >>> (vertices, distances, predecessors) = pylibcugraph.sssp(
     ...     resource_handle, G, source=1, cutoff=999,
     ...     compute_predecessors=True, do_expensive_check=False)
     >>> vertices

python/pylibcugraph/pylibcugraph/tests/conftest.py

@@ -115,10 +115,10 @@ def create_SGGraph(device_srcs,
     Creates and returns a SGGraph instance and the corresponding ResourceHandle
     using the parameters passed in.
     """
-    from pylibcugraph.experimental import (SGGraph,
-                                           ResourceHandle,
-                                           GraphProperties,
-                                           )
+    from pylibcugraph import (SGGraph,
+                              ResourceHandle,
+                              GraphProperties,
+                              )
     resource_handle = ResourceHandle()
     graph_props = GraphProperties(is_symmetric=False, is_multigraph=False)
 

python/pylibcugraph/pylibcugraph/tests/test_graph_sg.py

@@ -60,7 +60,7 @@ def test_graph_properties():
 
 
 def test_resource_handle():
-    from pylibcugraph.experimental import ResourceHandle
+    from pylibcugraph import ResourceHandle
     # This type has no attributes and is just defined to pass a struct from C
     # back in to C. In the future it may take args to acquire specific
     # resources, but for now just make sure nothing crashes.
@@ -69,10 +69,10 @@ def test_resource_handle():
 
 
 def test_sg_graph(graph_data):
-    from pylibcugraph.experimental import (SGGraph,
-                                           ResourceHandle,
-                                           GraphProperties,
-                                           )
+    from pylibcugraph import (SGGraph,
+                              ResourceHandle,
+                              GraphProperties,
+                              )
     # is_valid will only be True if the arrays are expected to produce a valid
     # graph. If False, ensure SGGraph() raises the proper exception.
     (device_srcs, device_dsts, device_weights, ds_name, is_valid) = graph_data

python/pylibcugraph/pylibcugraph/tests/test_katz_centrality.py

@@ -14,11 +14,17 @@
 import pytest
 import cupy as cp
 import numpy as np
-from pylibcugraph.experimental import (ResourceHandle,
-                                       GraphProperties,
-                                       SGGraph,
-                                       katz_centrality)
-from pylibcugraph.testing import utils
+from pylibcugraph import (ResourceHandle,
+                          GraphProperties,
+                          SGGraph,
+                          )
+from pylibcugraph.experimental import katz_centrality
+from cugraph.testing import utils
+import pathlib
+import pylibcugraph
+
+
+datasets = pathlib.Path(pylibcugraph.__path__[0]).parent.parent.parent
 
 
 # =============================================================================

python/pylibcugraph/pylibcugraph/tests/test_neighborhood_sampling.py

@@ -18,8 +18,8 @@
 from pylibcugraph import (MGGraph,
                           ResourceHandle,
                           GraphProperties,
-                          uniform_neighborhood_sampling,
                           )
+from pylibcugraph.experimental import uniform_neighborhood_sampling
 
 
 # =============================================================================

python/pylibcugraph/pylibcugraph/tests/test_pagerank.py

@@ -89,7 +89,7 @@
 # auto-transposing in C) or raise the appropriate exception.
 
 def test_pagerank(sg_transposed_graph_objs):
-    from pylibcugraph.experimental import pagerank
+    from pylibcugraph import pagerank
 
     (g, resource_handle, ds_name) = sg_transposed_graph_objs
     (expected_verts, expected_pageranks) = _test_data[ds_name]

python/pylibcugraph/pylibcugraph/tests/test_sssp.py

@@ -101,7 +101,7 @@
 # Tests
 # =============================================================================
 def test_sssp(sg_graph_objs):
-    from pylibcugraph.experimental import sssp
+    from pylibcugraph import sssp
 
     (g, resource_handle, ds_name) = sg_graph_objs