ENH: SPMD interface for IncrementalBasicStatistics

onedal/basic_statistics/basic_statistics.cpp

@@ -224,6 +224,7 @@ ONEDAL_PY_INIT_MODULE(basic_statistics) {
 
 #ifdef ONEDAL_DATA_PARALLEL_SPMD
     ONEDAL_PY_INSTANTIATE(init_compute_ops, sub, policy_spmd, task::compute);
+    ONEDAL_PY_INSTANTIATE(init_finalize_compute_ops, sub, policy_spmd, task::compute);
 #else // ONEDAL_DATA_PARALLEL_SPMD
     ONEDAL_PY_INSTANTIATE(init_compute_ops, sub, policy_list, task::compute);
     ONEDAL_PY_INSTANTIATE(init_partial_compute_ops, sub, policy_list, task::compute);

onedal/basic_statistics/incremental_basic_statistics.py

@@ -66,12 +66,12 @@ class IncrementalBasicStatistics(BaseBasicStatistics):
 
     def __init__(self, result_options="all"):
         super().__init__(result_options, algorithm="by_default")
-        module = self._get_backend("basic_statistics")
-        self._partial_result = module.partial_compute_result()
+        self._reset()
 
     def _reset(self):
-        module = self._get_backend("basic_statistics")
-        self._partial_result = module.partial_train_result()
+        self._partial_result = self._get_backend(
+            "basic_statistics", None, "partial_compute_result"
+        )
 
     def partial_fit(self, X, weights=None, queue=None):
         """
@@ -92,19 +92,20 @@ def partial_fit(self, X, weights=None, queue=None):
         self : object
             Returns the instance itself.
         """
-        if not hasattr(self, "_policy"):
-            self._policy = self._get_policy(queue, X)
-
-        X, weights = _convert_to_supported(self._policy, X, weights)
+        self._queue = queue
+        policy = self._get_policy(queue, X)
+        X, weights = _convert_to_supported(policy, X, weights)
 
         if not hasattr(self, "_onedal_params"):
             dtype = get_dtype(X)
-            self._onedal_params = self._get_onedal_params(dtype)
+            self._onedal_params = self._get_onedal_params(False, dtype=dtype)
 
         X_table, weights_table = to_table(X, weights)
-        module = self._get_backend("basic_statistics")
-        self._partial_result = module.partial_compute(
-            self._policy,
+        self._partial_result = self._get_backend(
+            "basic_statistics",
+            None,
+            "partial_compute",
+            policy,
             self._onedal_params,
             self._partial_result,
             X_table,
@@ -119,16 +120,26 @@ def finalize_fit(self, queue=None):
         Parameters
         ----------
         queue : dpctl.SyclQueue
-            Not used here, added for API conformance
+            If not None, use this queue for computations.
 
         Returns
         -------
         self : object
             Returns the instance itself.
         """
-        module = self._get_backend("basic_statistics")
-        result = module.finalize_compute(
-            self._policy, self._onedal_params, self._partial_result
+
+        if queue is not None:
+            policy = self._get_policy(queue)
+        else:
+            policy = self._get_policy(self._queue)
+
+        result = self._get_backend(
+            "basic_statistics",
+            None,
+            "finalize_compute",
+            policy,
+            self._onedal_params,
+            self._partial_result,
         )
         options = self._get_result_options(self.options).split("|")
         for opt in options:

onedal/spmd/basic_statistics/__init__.py

@@ -15,5 +15,6 @@
 # ==============================================================================
 
 from .basic_statistics import BasicStatistics
+from .incremental_basic_statistics import IncrementalBasicStatistics
 
-__all__ = ["BasicStatistics"]
+__all__ = ["BasicStatistics", "IncrementalBasicStatistics"]

onedal/spmd/basic_statistics/basic_statistics.py

@@ -14,8 +14,6 @@
 # limitations under the License.
 # ==============================================================================
 
-import warnings
-
 from onedal.basic_statistics import BasicStatistics as BasicStatistics_Batch
 
 from ..._device_offload import support_usm_ndarray

onedal/spmd/basic_statistics/incremental_basic_statistics.py

@@ -0,0 +1,69 @@
+# ==============================================================================
+# Copyright 2024 Intel 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.
+# ==============================================================================
+
+from daal4py.sklearn._utils import get_dtype
+
+from ...basic_statistics import (
+    IncrementalBasicStatistics as base_IncrementalBasicStatistics,
+)
+from ...datatypes import _convert_to_supported, to_table
+from .._base import BaseEstimatorSPMD
+
+
+class IncrementalBasicStatistics(BaseEstimatorSPMD, base_IncrementalBasicStatistics):
+    def _reset(self):
+        self._partial_result = super(base_IncrementalBasicStatistics, self)._get_backend(
+            "basic_statistics", None, "partial_compute_result"
+        )
+
+    def partial_fit(self, X, weights=None, queue=None):
+        """
+        Computes partial data for basic statistics
+        from data batch X and saves it to `_partial_result`.
+
+        Parameters
+        ----------
+        X : array-like of shape (n_samples, n_features)
+            Training data batch, where `n_samples` is the number of samples
+            in the batch, and `n_features` is the number of features.
+
+        queue : dpctl.SyclQueue
+            If not None, use this queue for computations.
+
+        Returns
+        -------
+        self : object
+            Returns the instance itself.
+        """
+        self._queue = queue
+        policy = super(base_IncrementalBasicStatistics, self)._get_policy(queue, X)
+        X, weights = _convert_to_supported(policy, X, weights)
+
+        if not hasattr(self, "_onedal_params"):
+            dtype = get_dtype(X)
+            self._onedal_params = self._get_onedal_params(False, dtype=dtype)
+
+        X_table, weights_table = to_table(X, weights)
+        self._partial_result = super(base_IncrementalBasicStatistics, self)._get_backend(
+            "basic_statistics",
+            None,
+            "partial_compute",
+            policy,
+            self._onedal_params,
+            self._partial_result,
+            X_table,
+            weights_table,
+        )

sklearnex/basic_statistics/incremental_basic_statistics.py

@@ -120,7 +120,7 @@ def __init__(self, result_options="all", batch_size=None):
 
     def _onedal_supported(self, method_name, *data):
         patching_status = PatchingConditionsChain(
-            f"sklearn.covariance.{self.__class__.__name__}.{method_name}"
+            f"sklearn.basic_statistics.{self.__class__.__name__}.{method_name}"
         )
         return patching_status
 
@@ -135,9 +135,9 @@ def _get_onedal_result_options(self, options):
         assert isinstance(onedal_options, str)
         return options
 
-    def _onedal_finalize_fit(self):
+    def _onedal_finalize_fit(self, queue=None):
         assert hasattr(self, "_onedal_estimator")
-        self._onedal_estimator.finalize_fit()
+        self._onedal_estimator.finalize_fit(queue=queue)
         self._need_to_finalize = False
 
     def _onedal_partial_fit(self, X, sample_weight=None, queue=None):
@@ -171,7 +171,7 @@ def _onedal_partial_fit(self, X, sample_weight=None, queue=None):
             self._onedal_estimator = self._onedal_incremental_basic_statistics(
                 **onedal_params
             )
-        self._onedal_estimator.partial_fit(X, sample_weight, queue)
+        self._onedal_estimator.partial_fit(X, weights=sample_weight, queue=queue)
         self._need_to_finalize = True
 
     def _onedal_fit(self, X, sample_weight=None, queue=None):
@@ -203,7 +203,7 @@ def _onedal_fit(self, X, sample_weight=None, queue=None):
 
         self.n_features_in_ = X.shape[1]
 
-        self._onedal_finalize_fit()
+        self._onedal_finalize_fit(queue=queue)
 
         return self
 

sklearnex/spmd/basic_statistics/__init__.py

@@ -15,5 +15,6 @@
 # ==============================================================================
 
 from .basic_statistics import BasicStatistics
+from .incremental_basic_statistics import IncrementalBasicStatistics
 
-__all__ = ["BasicStatistics"]
+__all__ = ["BasicStatistics", "IncrementalBasicStatistics"]

sklearnex/spmd/basic_statistics/incremental_basic_statistics.py

@@ -0,0 +1,30 @@
+# ==============================================================================
+# Copyright 2024 Intel 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.
+# ==============================================================================
+
+
+from onedal.spmd.basic_statistics import (
+    IncrementalBasicStatistics as onedalSPMD_IncrementalBasicStatistics,
+)
+
+from ...basic_statistics import (
+    IncrementalBasicStatistics as base_IncrementalBasicStatistics,
+)
+
+
+class IncrementalBasicStatistics(base_IncrementalBasicStatistics):
+    _onedal_incremental_basic_statistics = staticmethod(
+        onedalSPMD_IncrementalBasicStatistics
+    )