replace daal4py with sklearnex

src/dbs_all/dbs_patch.py

@@ -1,13 +1,12 @@
 from timeit import default_timer as timer
 
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 
-
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.cluster import DBSCAN
 import common
 

src/kmeans_all/kmeans_patch.py

@@ -1,16 +1,13 @@
 from timeit import default_timer as timer
 
-import xgboost as xgb
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-
-
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.cluster import KMeans
 
 kmeans_kwargs = {

src/kmeans_all/kmeans_patch_training.py

@@ -1,16 +1,13 @@
 from timeit import default_timer as timer
 
-import xgboost as xgb
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-
-
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.cluster import KMeans
 
 kmeans_kwargs = {

src/lm_all/lm_patch.py

@@ -1,7 +1,6 @@
-import daal4py as d4p
+from sklearnex import patch_sklearn
+patch_sklearn()
 
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.linear_model import LinearRegression
 
 from timeit import default_timer as timer

src/lm_all/lm_patch_training.py

@@ -1,6 +1,7 @@
-import numpy as np
-from daal4py.sklearn import patch_sklearn
+from sklearnex import patch_sklearn
 patch_sklearn()
+
+import numpy as np
 from sklearn.linear_model import LinearRegression
 from timeit import default_timer as timer
 from sklearn.metrics import mean_squared_error

src/logit_all/logit_patch.py

@@ -1,15 +1,13 @@
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from timeit import default_timer as timer
 
-import xgboost as xgb
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.linear_model import LogisticRegression
 
 

src/logit_all/logit_patch_training.py

@@ -1,17 +1,15 @@
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from timeit import default_timer as timer
 
-import xgboost as xgb
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-
 NUM_LOOPS = 100
 
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.linear_model import LogisticRegression
 
 

src/rf_all/rf_patch.py

@@ -1,14 +1,13 @@
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from timeit import default_timer as timer
 
-#import xgboost as xgb
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.ensemble import RandomForestRegressor
 
 NUM_LOOPS = 100

src/rf_all/rf_patch_training.py

@@ -1,14 +1,13 @@
+from sklearnex import patch_sklearn
+patch_sklearn()
+
 from timeit import default_timer as timer
 
-#import xgboost as xgb
 from sklearn.metrics import mean_squared_error
-import daal4py as d4p
 import numpy as np
 import pandas as pd
 import common
 
-import daal4py.sklearn
-daal4py.sklearn.patch_sklearn()
 from sklearn.ensemble import RandomForestRegressor
 
 NUM_LOOPS = 100