Merge branch 'branch-25.04' into one-pass-conda-test-env

rapidsai · Feb 18, 2025 · 4a89590 · 4a89590
2 parents 347da2a + b777261
commit 4a89590
Show file tree

Hide file tree

Showing 3 changed files with 50 additions and 26 deletions.
diff --git a/cpp/src/community/legacy/spectral_clustering.cu b/cpp/src/community/legacy/spectral_clustering.cu
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2020-2024, NVIDIA CORPORATION.
+ * Copyright (c) 2020-2025, NVIDIA CORPORATION.
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -88,12 +88,14 @@ void balancedCutClustering_impl(legacy::GraphCSRView<vertex_t, edge_t, weight_t>
 
   using index_type = vertex_t;
   using value_type = weight_t;
+  using nnz_type   = edge_t;
 
-  raft::spectral::matrix::sparse_matrix_t<index_type, value_type> const r_csr_m{handle, graph};
+  raft::spectral::matrix::sparse_matrix_t<index_type, value_type, nnz_type> const r_csr_m{handle,
+                                                                                          graph};
 
-  raft::spectral::eigen_solver_config_t<index_type, value_type> eig_cfg{
+  raft::spectral::eigen_solver_config_t<index_type, value_type, nnz_type> eig_cfg{
     n_eig_vects, evs_max_it, restartIter_lanczos, evs_tol, reorthog, seed1};
-  raft::spectral::lanczos_solver_t<index_type, value_type> eig_solver{eig_cfg};
+  raft::spectral::lanczos_solver_t<index_type, value_type, nnz_type> eig_solver{eig_cfg};
 
   raft::spectral::cluster_solver_config_t<index_type, value_type> clust_cfg{
     n_clusters, kmean_max_it, kmean_tol, seed2};
@@ -158,12 +160,14 @@ void spectralModularityMaximization_impl(
 
   using index_type = vertex_t;
   using value_type = weight_t;
+  using nnz_type   = edge_t;
 
-  raft::spectral::matrix::sparse_matrix_t<index_type, value_type> const r_csr_m{handle, graph};
+  raft::spectral::matrix::sparse_matrix_t<index_type, value_type, nnz_type> const r_csr_m{handle,
+                                                                                          graph};
 
-  raft::spectral::eigen_solver_config_t<index_type, value_type> eig_cfg{
+  raft::spectral::eigen_solver_config_t<index_type, value_type, nnz_type> eig_cfg{
     n_eig_vects, evs_max_it, restartIter_lanczos, evs_tol, reorthog, seed1};
-  raft::spectral::lanczos_solver_t<index_type, value_type> eig_solver{eig_cfg};
+  raft::spectral::lanczos_solver_t<index_type, value_type, nnz_type> eig_solver{eig_cfg};
 
   raft::spectral::cluster_solver_config_t<index_type, value_type> clust_cfg{
     n_clusters, kmean_max_it, kmean_tol, seed2};
@@ -190,8 +194,10 @@ void analyzeModularityClustering_impl(legacy::GraphCSRView<vertex_t, edge_t, wei
 
   using index_type = vertex_t;
   using value_type = weight_t;
+  using nnz_type   = edge_t;
 
-  raft::spectral::matrix::sparse_matrix_t<index_type, value_type> const r_csr_m{handle, graph};
+  raft::spectral::matrix::sparse_matrix_t<index_type, value_type, nnz_type> const r_csr_m{handle,
+                                                                                          graph};
 
   weight_t mod;
   raft::spectral::analyzeModularity(handle, r_csr_m, n_clusters, clustering, mod);
@@ -216,8 +222,10 @@ void analyzeBalancedCut_impl(legacy::GraphCSRView<vertex_t, edge_t, weight_t> co
 
   using index_type = vertex_t;
   using value_type = weight_t;
+  using nnz_type   = edge_t;
 
-  raft::spectral::matrix::sparse_matrix_t<index_type, value_type> const r_csr_m{handle, graph};
+  raft::spectral::matrix::sparse_matrix_t<index_type, value_type, nnz_type> const r_csr_m{handle,
+                                                                                          graph};
 
   raft::spectral::analyzePartition(handle, r_csr_m, n_clusters, clustering, edge_cut, cost);
 

diff --git a/python/cugraph/cugraph/structure/graph_primtypes.pyx b/python/cugraph/cugraph/structure/graph_primtypes.pyx
@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2024, NVIDIA CORPORATION.
+# Copyright (c) 2020-2025, 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
@@ -36,7 +36,7 @@ cdef move_device_buffer_to_column(
     buff = DeviceBuffer.c_from_unique_ptr(move(device_buffer_unique_ptr))
     buff = as_buffer(buff)
     if buff.nbytes != 0:
-        column = cudf.core.column.build_column(buff, dtype=dtype)
+        column = cudf.core.column.build_column(buff, dtype=cudf.dtype(dtype))
         return column
     return None
 

diff --git a/python/cugraph/cugraph/structure/hypergraph.py b/python/cugraph/cugraph/structure/hypergraph.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2024, NVIDIA CORPORATION.
+# Copyright (c) 2020-2025, 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
@@ -40,6 +40,9 @@
 from cugraph.structure.symmetrize import symmetrize
 
 
+_str_dtype = np.dtype("str")
+
+
 def hypergraph(
     values,
     columns=None,
@@ -328,17 +331,19 @@ def _create_entity_nodes(
         cudf.DataFrame(
             dict(
                 [
-                    (NODEID, cudf.core.column.column_empty(0, "str")),
+                    (NODEID, cudf.core.column.column_empty(0, _str_dtype)),
                     (
                         CATEGORY,
                         cudf.core.column.column_empty(
-                            0, "str" if not categorical_metadata else _empty_cat_dt()
+                            0,
+                            _str_dtype if not categorical_metadata else _empty_cat_dt(),
                         ),
                     ),
                     (
                         NODETYPE,
                         cudf.core.column.column_empty(
-                            0, "str" if not categorical_metadata else _empty_cat_dt()
+                            0,
+                            _str_dtype if not categorical_metadata else _empty_cat_dt(),
                         ),
                     ),
                 ]
@@ -428,13 +433,15 @@ def _create_hyper_edges(
             dict(
                 (
                     [
-                        (EVENTID, cudf.core.column.column_empty(0, "str")),
-                        (ATTRIBID, cudf.core.column.column_empty(0, "str")),
+                        (EVENTID, cudf.core.column.column_empty(0, _str_dtype)),
+                        (ATTRIBID, cudf.core.column.column_empty(0, _str_dtype)),
                         (
                             EDGETYPE,
                             cudf.core.column.column_empty(
                                 0,
-                                "str" if not categorical_metadata else _empty_cat_dt(),
+                                _str_dtype
+                                if not categorical_metadata
+                                else _empty_cat_dt(),
                             ),
                         ),
                     ]
@@ -447,7 +454,9 @@ def _create_hyper_edges(
                             CATEGORY,
                             cudf.core.column.column_empty(
                                 0,
-                                "str" if not categorical_metadata else _empty_cat_dt(),
+                                _str_dtype
+                                if not categorical_metadata
+                                else _empty_cat_dt(),
                             ),
                         )
                     ]
@@ -523,14 +532,16 @@ def _create_direct_edges(
             dict(
                 (
                     [
-                        (EVENTID, cudf.core.column.column_empty(0, "str")),
-                        (SOURCE, cudf.core.column.column_empty(0, "str")),
-                        (TARGET, cudf.core.column.column_empty(0, "str")),
+                        (EVENTID, cudf.core.column.column_empty(0, _str_dtype)),
+                        (SOURCE, cudf.core.column.column_empty(0, _str_dtype)),
+                        (TARGET, cudf.core.column.column_empty(0, _str_dtype)),
                         (
                             EDGETYPE,
                             cudf.core.column.column_empty(
                                 0,
-                                "str" if not categorical_metadata else _empty_cat_dt(),
+                                _str_dtype
+                                if not categorical_metadata
+                                else _empty_cat_dt(),
                             ),
                         ),
                     ]
@@ -543,7 +554,9 @@ def _create_direct_edges(
                             CATEGORY,
                             cudf.core.column.column_empty(
                                 0,
-                                "str" if not categorical_metadata else _empty_cat_dt(),
+                                _str_dtype
+                                if not categorical_metadata
+                                else _empty_cat_dt(),
                             ),
                         )
                     ]
@@ -611,7 +624,8 @@ def _str_scalar_to_category(size, val):
         data=None,
         size=size,
         dtype=cudf.CategoricalDtype(
-            categories=cudf.core.column.as_column([val], dtype="str"), ordered=False
+            categories=cudf.core.column.as_column([val], dtype=_str_dtype),
+            ordered=False,
         ),
         mask=None,
         offset=0,
@@ -626,4 +640,6 @@ def _prepend_str(col, val):
 
 # Make an empty categorical string dtype
 def _empty_cat_dt():
-    return cudf.CategoricalDtype(categories=np.array([], dtype="str"), ordered=False)
+    return cudf.CategoricalDtype(
+        categories=np.array([], dtype=_str_dtype), ordered=False
+    )