Squashing

Author: Nikita Kulikov

.ci/pipeline/build-and-test-lnx.yml

@@ -24,8 +24,8 @@ steps:
     displayName: "System info"
   - script: |
       conda update -y -q conda
-      if [ $(echo $(PYTHON_VERSION) | grep '3.8\|3.9\|3.10') ]; then export DPCPP_PACKAGE="dpctl>=0.14 "; else export DPCPP_PACKAGE=""; fi
-      conda create -q -y -n CB -c conda-forge -c intel python=$(PYTHON_VERSION) dal-devel mpich pyyaml $DPCPP_PACKAGE dpcpp-cpp-rt>=2023.2.0
+      if [ $(echo $(PYTHON_VERSION) | grep '3.9\|3.10') ]; then export DPCPP_PACKAGE="dpctl>=0.15 "; else export DPCPP_PACKAGE=""; fi
+      conda create -q -y -n CB -c conda-forge -c intel python=$(PYTHON_VERSION) intel::dal-devel mpich pyyaml $DPCPP_PACKAGE "dpcpp-cpp-rt>=2024.0.0"
     displayName: "Conda create"
   - script: |
       . /usr/share/miniconda/etc/profile.d/conda.sh
@@ -47,7 +47,7 @@ steps:
       bash .ci/scripts/setup_sklearn.sh $(SKLEARN_VERSION)
       pip install --upgrade -r requirements-test.txt
       pip install $(python .ci/scripts/get_compatible_scipy_version.py)
-      if [ $(echo $(PYTHON_VERSION) | grep '3.8\|3.9\|3.10') ]; then conda install -q -y -c intel dpnp; fi
+      if [ $(echo $(PYTHON_VERSION) | grep '3.9\|3.10') ]; then conda install -q -y -c intel dpnp; fi
       pip list
     displayName: "Install testing requirements"
   - script: |

.ci/pipeline/build-and-test-win.yml

@@ -16,7 +16,7 @@
 steps:
   - powershell: Write-Host "##vso[task.prependpath]$env:CONDA\Scripts"
     displayName: Add conda to PATH
-  - script: conda create -q -y -n CB -c conda-forge -c intel python=$(PYTHON_VERSION) dal-devel impi-devel clang-format pyyaml
+  - script: conda create -q -y -n CB -c conda-forge -c intel python=$(PYTHON_VERSION) intel::dal-devel impi-devel clang-format pyyaml
     displayName: 'Create Anaconda environment'
   - script: |
       call activate CB

.ci/scripts/install_dpcpp.sh

@@ -21,6 +21,5 @@ rm GPG-PUB-KEY-INTEL-SW-PRODUCTS-2023.PUB
 echo "deb https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list
 sudo add-apt-repository -y "deb https://apt.repos.intel.com/oneapi all main"
 sudo apt-get update
-sudo apt-get install -y intel-dpcpp-cpp-compiler-2023.2.1
+sudo apt-get install -y intel-dpcpp-cpp-compiler-2024.0
 sudo bash -c 'echo libintelocl.so > /etc/OpenCL/vendors/intel-cpu.icd'
-sudo mv -f /opt/intel/oneapi/compiler/latest/linux/lib/oclfpga /opt/intel/oneapi/compiler/latest/linux/lib/oclfpga_

doc/third-party-programs-sklearnex.txt

@@ -242,7 +242,7 @@ DAMAGE.
 -------------------------------------------------------------
 
 3. Cython
-Apache License
+                                 Apache License
                            Version 2.0, January 2004
                         https://www.apache.org/licenses/
 
@@ -421,4 +421,209 @@ Apache License
 
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gen.py

@@ -27,9 +27,11 @@
 import re
 import shutil
 from collections import OrderedDict, defaultdict
+from os.path import isdir
 from os.path import join as jp
 from shutil import copytree, rmtree
 from subprocess import call
+from sys import platform
 
 from .format import mk_var
 from .parse import parse_header, parse_version
@@ -1196,7 +1198,15 @@ def gen_daal4py(dalroot, outdir, version, warn_all=False, no_dist=False, no_stre
     global no_warn
     if warn_all:
         no_warn = {}
-    orig_path = jp(dalroot, "include")
+    orig_path_candidates = [
+        jp(dalroot, "include", "dal"),
+        jp(dalroot, "Library", "include", "dal"),
+        jp(dalroot, "include"),
+    ]
+    for candidate in orig_path_candidates:
+        if isdir(candidate):
+            orig_path = candidate
+            break
     assert os.path.isfile(jp(orig_path, "algorithms", "algorithm.h")) and os.path.isfile(
         jp(orig_path, "algorithms", "model.h")
     ), (

generator/gen_daal4py.py

@@ -81,6 +81,7 @@ def _fit(self, X, y, sample_weight, module, queue):
             ).ravel()
         else:
             self.core_sample_indices_ = np.array([], dtype=np.intc)
+        self.core_sample_indices_ = self.core_sample_indices_.astype(np.intc)
         self.components_ = np.take(X, self.core_sample_indices_, axis=0)
         self.n_features_in_ = X.shape[1]
         return self

onedal/cluster/dbscan.py

@@ -91,9 +91,10 @@ def _check_params_vs_input(
         self, X_table, policy, default_n_init=10, dtype=np.float32
     ):
         # n_clusters
-        if X_table.shape[0] < self.n_clusters:
+        X_row_count = X_table.get_row_count()
+        if X_row_count < self.n_clusters:
             raise ValueError(
-                f"n_samples={X_table.shape[0]} should be >= n_clusters={self.n_clusters}."
+                f"n_samples={X_row_count} should be >= n_clusters={self.n_clusters}."
             )
 
         # tol
@@ -182,7 +183,7 @@ def _init_centroids_custom(
         elif _is_arraylike_not_scalar(init):
             centers = np.asarray(init)
             assert centers.shape[0] == n_clusters
-            assert centers.shape[1] == X_table.column_count
+            assert centers.shape[1] == X_table.get_column_count()
             centers = _convert_to_supported(policy, init)
             centers_table = to_table(centers)
         else:
@@ -221,10 +222,6 @@ def _init_centroids_generic(self, X, init, random_state, policy, dtype=np.float3
     def _fit_backend(self, X_table, centroids_table, module, policy, dtype=np.float32):
         params = self._get_onedal_params(dtype)
 
-        # TODO: check all features for having correct type
-        meta = _backend.get_table_metadata(X_table)
-        assert meta.get_npy_dtype(0) == dtype
-
         result = module.train(policy, params, X_table, centroids_table)
 
         return (
@@ -238,7 +235,7 @@ def _fit(self, X, module, queue=None):
         policy = self._get_policy(queue, X)
         _, X_table, dtype = self._get_params_and_input(X, policy)
 
-        self.n_features_in_ = X_table.column_count
+        self.n_features_in_ = X_table.get_column_count()
 
         best_model, best_n_iter = None, None
         best_inertia, best_labels = None, None