Deprecate handle from public APIs

docs/source/api.rst

@@ -215,29 +215,24 @@ Metrics (regression, classification, and distance)
 
 Metrics (clustering and manifold learning)
 ------------------------------------------
-  .. automodule:: cuml.metrics.trustworthiness
-    :members:
 
-  .. automodule:: cuml.metrics.cluster.adjusted_rand_index
-    :members:
+  .. autofunction:: cuml.metrics.trustworthiness
 
-  .. automodule:: cuml.metrics.cluster.entropy
-    :members:
+  .. autofunction:: cuml.metrics.cluster.adjusted_rand_score
 
-  .. automodule:: cuml.metrics.cluster.homogeneity_score
-    :members:
+  .. autofunction:: cuml.metrics.cluster.entropy
 
-  .. automodule:: cuml.metrics.cluster.silhouette_score
-    :members:
+  .. autofunction:: cuml.metrics.cluster.homogeneity_score
 
-  .. automodule:: cuml.metrics.cluster.completeness_score
-    :members:
+  .. autofunction:: cuml.metrics.cluster.silhouette_score
 
-  .. automodule:: cuml.metrics.cluster.mutual_info_score
-    :members:
+  .. autofunction:: cuml.metrics.cluster.silhouette_samples
 
-  .. automodule:: cuml.metrics.cluster.v_measure_score
-    :members:
+  .. autofunction:: cuml.metrics.cluster.completeness_score
+
+  .. autofunction:: cuml.metrics.cluster.mutual_info_score
+
+  .. autofunction:: cuml.metrics.cluster.v_measure_score
 
 Benchmarking
 ------------

python/cuml/cuml/__init__.py

@@ -14,7 +14,6 @@
     del libcuml
 
 import cupy
-from pylibraft.common import Handle
 from rmm.allocators.cupy import rmm_cupy_allocator
 
 import cuml.feature_extraction
@@ -87,6 +86,18 @@ def __getattr__(name):
         except AttributeError:
             _global_settings_data.settings = GlobalSettings()
             return _global_settings_data.settings
+    elif name == "Handle":
+        import warnings
+
+        from pylibraft.common import Handle
+
+        warnings.warn(
+            "cuml.Handle was deprecated in 26.02 and will be removed in 26.04. "
+            "There is no need to manually specify a `handle`, cuml now manages "
+            "this resource for you automatically.",
+            FutureWarning,
+        )
+        return Handle
 
     raise AttributeError(f"module {__name__} has no attribute {name}")
 

python/cuml/cuml/cluster/agglomerative.pyx

@@ -8,7 +8,7 @@ from cuml.common import input_to_cuml_array
 from cuml.common.array_descriptor import CumlArrayDescriptor
 from cuml.common.doc_utils import generate_docstring
 from cuml.internals.array import CumlArray
-from cuml.internals.base import Base
+from cuml.internals.base import Base, get_handle
 from cuml.internals.mixins import ClusterMixin, CMajorInputTagMixin
 from cuml.internals.outputs import reflect
 
@@ -80,13 +80,13 @@ class AgglomerativeClustering(Base, ClusterMixin, CMajorInputTagMixin):
         Indirectly influences the number of neighbors to use when
         ``connectivity="knn"``, with ``n_neighbors = log(n_samples) + c``. The
         default of 15 should suffice for most problems.
-    handle : cuml.Handle
-        Specifies the cuml.handle that holds internal CUDA state for
-        computations in this model. Most importantly, this specifies the CUDA
-        stream that will be used for the model's computations, so users can
-        run different models concurrently in different streams by creating
-        handles in several streams.
-        If it is None, a new one is created.
+    handle : cuml.Handle or None, default=None
+
+        .. deprecated:: 26.02
+            The `handle` argument was deprecated in 26.02 and will be removed
+            in 26.04. There's no need to pass in a handle, cuml now manages
+            this resource automatically.
+
     verbose : int or boolean, default=False
         Sets logging level. It must be one of `cuml.common.logger.level_*`.
         See :ref:`verbosity-levels` for more info.
@@ -194,7 +194,8 @@ class AgglomerativeClustering(Base, ClusterMixin, CMajorInputTagMixin):
         labels = CumlArray.empty(n_rows, dtype="int32", order="C")
         children = CumlArray.empty((n_rows - 1, 2), dtype="int32", order="C")
 
-        cdef handle_t* handle_ = <handle_t*><size_t>self.handle.getHandle()
+        handle = get_handle(model=self)
+        cdef handle_t* handle_ = <handle_t*><size_t>handle.getHandle()
         cdef int c = self.c
         cdef float* X_ptr = <float*><uintptr_t>X.ptr
         cdef int* children_ptr = <int*><uintptr_t>children.ptr
@@ -214,7 +215,7 @@ class AgglomerativeClustering(Base, ClusterMixin, CMajorInputTagMixin):
                 use_knn,
                 c,
             )
-        self.handle.sync()
+        handle.sync()
 
         # We only support single linkage for now, for other linkage types
         # n_connected_components_ and n_leaves_ will differ

python/cuml/cuml/cluster/dbscan.pyx

@@ -2,15 +2,14 @@
 # SPDX-FileCopyrightText: Copyright (c) 2019-2025, NVIDIA CORPORATION.
 # SPDX-License-Identifier: Apache-2.0
 #
-
 import cupy as cp
 import numpy as np
 
 from cuml.common.array_descriptor import CumlArrayDescriptor
 from cuml.common.doc_utils import generate_docstring
 from cuml.internals import logger, reflect
 from cuml.internals.array import CumlArray
-from cuml.internals.base import Base
+from cuml.internals.base import Base, get_handle
 from cuml.internals.input_utils import input_to_cuml_array
 from cuml.internals.interop import (
     InteropMixin,
@@ -152,13 +151,13 @@ class DBSCAN(Base,
     eps : float (default = 0.5)
         The maximum distance between 2 points such they reside in the same
         neighborhood.
-    handle : cuml.Handle
-        Specifies the cuml.handle that holds internal CUDA state for
-        computations in this model. Most importantly, this specifies the CUDA
-        stream that will be used for the model's computations, so users can
-        run different models concurrently in different streams by creating
-        handles in several streams.
-        If it is None, a new one is created.
+    handle : cuml.Handle or None, default=None
+
+        .. deprecated:: 26.02
+            The `handle` argument was deprecated in 26.02 and will be removed
+            in 26.04. There's no need to pass in a handle, cuml now manages
+            this resource automatically.
+
     min_samples : int (default = 5)
         The number of samples in a neighborhood such that this group can be
         considered as an important core point (including the point itself).
@@ -399,7 +398,8 @@ class DBSCAN(Base,
         cdef uintptr_t core_sample_indices_ptr = (
             0 if core_sample_indices is None else core_sample_indices.ptr
         )
-        cdef handle_t* handle_ = <handle_t*><size_t>self.handle.getHandle()
+        handle = get_handle(model=self)
+        cdef handle_t* handle_ = <handle_t*><size_t>handle.getHandle()
         cdef bool X_f32 = X.dtype == np.float32
         cdef bool labels_i32 = labels.dtype == np.int32
 
@@ -467,7 +467,7 @@ class DBSCAN(Base,
                         algorithm,
                         verbose,
                         multi_gpu)
-        self.handle.sync()
+        handle.sync()
 
         if core_sample_indices is not None:
             # Trim the core_sample_indices array if necessary. In the common case