MAINT: Remove untested option to build without onedal module

doc/sources/building-from-source.rst

@@ -62,7 +62,7 @@ To install the necessary Python dependencies:
 Non-Python dependencies
 ~~~~~~~~~~~~~~~~~~~~~~~
 
-Apart from Python libraries and from the |onedal|, the following dependencies are needed in order to compile the |sklearnex|:
+Apart from Python libraries and from the |onedal| (version ``2021.4`` or higher), the following dependencies are needed in order to compile the |sklearnex|:
 
 - A C++ compiler.
 - clang-format.
@@ -228,7 +228,6 @@ The following environment variables can be used to control setup aspects:
 - ``NO_DIST``: set to '1', 'yes' or alike to build without support for distributed mode.
 - ``NO_STREAM``: set to '1', 'yes' or alike to build without support for streaming mode.
 - ``NO_DPC``: set to '1', 'yes' or alike to build without support of oneDAL DPC++ interfaces.
-- ``OFF_ONEDAL_IFACE``: set to '1' to build without the support of oneDAL interfaces.
 - ``MAKEFLAGS``: the last `-j` flag determines the number of threads for building the onedal extension. It will default to the number of CPU threads when not set.
 
 .. note:: The ``-j`` flag in the ``MAKEFLAGS`` environment variable is superseded in ``setup.py`` modes which support the ``--parallel`` and ``-j`` command line flags.

setup.py

@@ -80,11 +80,10 @@ def check_for_build_arg(arg: str) -> bool:
     dal_root, "binary"
 )
 ONEDAL_VERSION = get_onedal_version(dal_root)
-ONEDAL_2021_3 = 2021 * 10000 + 3 * 100
-ONEDAL_2023_0_1 = 2023 * 10000 + 0 * 100 + 1
-is_onedal_iface = (
-    os.environ.get("OFF_ONEDAL_IFACE", "0") == "0" and ONEDAL_VERSION >= ONEDAL_2021_3
-)
+if ONEDAL_VERSION < 20210300:
+    raise ValueError(
+        "OneDAL version is too old. Please use a more recent version (>= 2021.04)."
+    )
 
 sklearnex_version = (
     os.environ["SKLEARNEX_VERSION"]
@@ -479,12 +478,11 @@ def onedal_run(self):
             debug_build=DEBUG_BUILD,
             using_lld=USING_LLD,
         )
-        if is_onedal_iface:
-            build_onedal("host")
-            if dpcpp:
-                build_onedal("dpc")
-                if build_distributed:
-                    build_onedal("spmd_dpc")
+        build_onedal("host")
+        if dpcpp:
+            build_onedal("dpc")
+            if build_distributed:
+                build_onedal("spmd_dpc")
 
     def onedal_post_build(self):
         if IS_MAC:
@@ -495,18 +493,6 @@ def onedal_post_build(self):
             major_is_available = (
                 find_library(f"libonedal_core.{major_version}.dylib") is not None
             )
-            if major_is_available and ONEDAL_VERSION == ONEDAL_2023_0_1:
-                extension_libs = list(pathlib.Path(".").glob("**/*darwin.so"))
-                onedal_libs = ["onedal", "onedal_dpc", "onedal_core", "onedal_thread"]
-                for ext_lib in extension_libs:
-                    for onedal_lib in onedal_libs:
-                        subprocess.call(
-                            "/usr/bin/install_name_tool -change "
-                            f"lib{onedal_lib}.dylib "
-                            f"lib{onedal_lib}.{major_version}.dylib "
-                            f"{ext_lib}".split(" "),
-                            shell=False,
-                        )
 
 
 class develop(onedal_build, orig_develop.develop):

sklearnex/__init__.py

@@ -55,14 +55,11 @@
     "utils",
 ]
 __version__ = "2199.9.9"
-onedal_iface_flag = os.environ.get("OFF_ONEDAL_IFACE", "0")
-if onedal_iface_flag == "0":
-    from onedal import _spmd_backend
-    from onedal.common.hyperparameters import get_hyperparameters, reset_hyperparameters
-
-    if _spmd_backend is not None:
-        __all__.append("spmd")
+from onedal import _spmd_backend
+from onedal.common.hyperparameters import get_hyperparameters, reset_hyperparameters
 
+if _spmd_backend is not None:
+    __all__.append("spmd")
 
 from ._utils import set_sklearn_ex_verbose
 

sklearnex/dispatcher.py

@@ -24,12 +24,6 @@
 from daal4py.sklearn.monkeypatch.dispatcher import PatchMap
 
 
-def _is_new_patching_available():
-    return os.environ.get("OFF_ONEDAL_IFACE", "0") == "0" and daal_check_version(
-        (2021, "P", 300)
-    )
-
-
 def _is_preview_enabled() -> bool:
     return "SKLEARNEX_PREVIEW" in os.environ
 
@@ -58,68 +52,54 @@ def get_patch_map_core(preview: bool = False) -> PatchMap:
     if preview:
         mapping = get_patch_map_core(preview=False)
 
-        if _is_new_patching_available():
-            import sklearn.covariance as covariance_module
-            import sklearn.decomposition as decomposition_module
-            from sklearn.covariance import (
-                EmpiricalCovariance as EmpiricalCovariance_sklearn,
+        import sklearn.covariance as covariance_module
+        import sklearn.decomposition as decomposition_module
+        from sklearn.covariance import EmpiricalCovariance as EmpiricalCovariance_sklearn
+        from sklearn.decomposition import IncrementalPCA as IncrementalPCA_sklearn
+
+        # Preview classes for patching
+        from .preview.covariance import (
+            EmpiricalCovariance as EmpiricalCovariance_sklearnex,
+        )
+        from .preview.decomposition import IncrementalPCA as IncrementalPCA_sklearnex
+
+        # Since the state of the lru_cache without preview cannot be
+        # guaranteed to not have already enabled sklearnex algorithms
+        # when preview is used, setting the mapping element[1] to None
+        # should NOT be done. This may lose track of the unpatched
+        # sklearn estimator or function.
+        # Covariance
+        preview_mapping = {
+            "sklearn.covariance.EmpiricalCovariance": (
+                covariance_module,
+                "EmpiricalCovariance",
+                EmpiricalCovariance_sklearnex,
+                EmpiricalCovariance_sklearn,
+            ),
+            "sklearn.decomposition.IncrementalPCA": (
+                decomposition_module,
+                "IncrementalPCA",
+                IncrementalPCA_sklearnex,
+                IncrementalPCA_sklearn,
+            ),
+        }
+        if daal_check_version((2024, "P", 1)):
+            import sklearn.linear_model as linear_model_module
+            from sklearn.linear_model import (
+                LogisticRegressionCV as LogisticRegressionCV_sklearn,
+            )
+
+            from .preview.linear_model import (
+                LogisticRegressionCV as LogisticRegressionCV_sklearnex,
             )
-            from sklearn.decomposition import IncrementalPCA as IncrementalPCA_sklearn
 
-            # Preview classes for patching
-            from .preview.covariance import (
-                EmpiricalCovariance as EmpiricalCovariance_sklearnex,
+            preview_mapping["sklearn.linear_model.LogisticRegressionCV"] = (
+                linear_model_module,
+                "LogisticRegressionCV",
+                LogisticRegressionCV_sklearnex,
+                LogisticRegressionCV_sklearn,
             )
-            from .preview.decomposition import IncrementalPCA as IncrementalPCA_sklearnex
-
-            # Since the state of the lru_cache without preview cannot be
-            # guaranteed to not have already enabled sklearnex algorithms
-            # when preview is used, setting the mapping element[1] to None
-            # should NOT be done. This may lose track of the unpatched
-            # sklearn estimator or function.
-            # Covariance
-            preview_mapping = {
-                "sklearn.covariance.EmpiricalCovariance": (
-                    covariance_module,
-                    "EmpiricalCovariance",
-                    EmpiricalCovariance_sklearnex,
-                    EmpiricalCovariance_sklearn,
-                ),
-                "sklearn.decomposition.IncrementalPCA": (
-                    decomposition_module,
-                    "IncrementalPCA",
-                    IncrementalPCA_sklearnex,
-                    IncrementalPCA_sklearn,
-                ),
-            }
-            if daal_check_version((2024, "P", 1)):
-                import sklearn.linear_model as linear_model_module
-                from sklearn.linear_model import (
-                    LogisticRegressionCV as LogisticRegressionCV_sklearn,
-                )
-
-                from .preview.linear_model import (
-                    LogisticRegressionCV as LogisticRegressionCV_sklearnex,
-                )
-
-                preview_mapping["sklearn.linear_model.LogisticRegressionCV"] = (
-                    linear_model_module,
-                    "LogisticRegressionCV",
-                    LogisticRegressionCV_sklearnex,
-                    LogisticRegressionCV_sklearn,
-                )
-            return mapping | preview_mapping
-
-        return mapping
-
-    # Comment 2026-01-20: This route is untested. It was meant to support
-    # a situation in which the 'onedal' module is not compiled, and instead
-    # the patching takes classes from daal4py, while still importing from
-    # the sklearnex module. This is not tested in any kind of configurations.
-    if not _is_new_patching_available():
-        from daal4py.sklearn.monkeypatch.dispatcher import _get_map_of_algorithms
-
-        return _get_map_of_algorithms()
+        return mapping | preview_mapping
 
     # Scikit-learn* modules
     import sklearn as base_module
@@ -515,7 +495,7 @@ def patch_sklearn(
 
     patch_map: PatchMap = get_patch_map()
 
-    if name is not None and _is_new_patching_available():
+    if name is not None:
         names_mandatory = [
             "sklearn.set_config",
             "sklearn.get_config",