Add torch to remaining spmd tests

ethanglaser · ethanglaser · commit 676fead0e1ea · 2026-04-08T15:29:13.000-07:00
diff --git a/sklearnex/spmd/basic_statistics/tests/test_incremental_basic_statistics_spmd.py b/sklearnex/spmd/basic_statistics/tests/test_incremental_basic_statistics_spmd.py
@@ -104,7 +104,7 @@ def test_incremental_basic_statistics_fit_spmd_gold(dataframe, queue, weighted,
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("num_blocks", [1, 2])
 @pytest.mark.parametrize("weighted", [True, False])
@@ -178,7 +178,7 @@ def test_incremental_basic_statistics_partial_fit_spmd_gold(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("num_blocks", [1, 2])
 @pytest.mark.parametrize("weighted", [True, False])
@@ -247,7 +247,7 @@ def test_incremental_basic_statistics_single_option_partial_fit_spmd_gold(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("num_blocks", [1, 2])
 @pytest.mark.parametrize("weighted", [True, False])
diff --git a/sklearnex/spmd/cluster/tests/test_dbscan_spmd.py b/sklearnex/spmd/cluster/tests/test_dbscan_spmd.py
@@ -67,7 +67,7 @@ def test_dbscan_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("min_samples", [2, 5, 15])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/cluster/tests/test_kmeans_spmd.py b/sklearnex/spmd/cluster/tests/test_kmeans_spmd.py
@@ -107,7 +107,7 @@ def test_kmeans_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("n_clusters", [2, 5, 15])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/covariance/tests/test_covariance_spmd.py b/sklearnex/spmd/covariance/tests/test_covariance_spmd.py
@@ -83,7 +83,7 @@ def test_covariance_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("assume_centered", [True, False])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/covariance/tests/test_incremental_covariance_spmd.py b/sklearnex/spmd/covariance/tests/test_incremental_covariance_spmd.py
@@ -88,7 +88,7 @@ def test_incremental_covariance_fit_spmd_gold(dataframe, queue, assume_centered,
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("num_blocks", [1, 2])
 @pytest.mark.parametrize("assume_centered", [True, False])
@@ -149,7 +149,7 @@ def test_incremental_covariance_partial_fit_spmd_gold(
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
 @pytest.mark.mpi
diff --git a/sklearnex/spmd/decomposition/tests/test_incremental_pca_spmd.py b/sklearnex/spmd/decomposition/tests/test_incremental_pca_spmd.py
@@ -95,7 +95,7 @@ def test_incremental_pca_fit_spmd_gold(dataframe, queue, whiten, dtype):
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("whiten", [True, False])
 @pytest.mark.parametrize("num_blocks", [1, 2])
@@ -159,7 +159,7 @@ def test_incremental_pca_partial_fit_spmd_gold(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("whiten", [True, False])
 @pytest.mark.parametrize("n_components", [None, 2, 5])
@@ -211,7 +211,7 @@ def test_incremental_pca_fit_spmd_random(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("whiten", [True, False])
 @pytest.mark.parametrize("n_components", [None, 2, 5])
diff --git a/sklearnex/spmd/decomposition/tests/test_pca_spmd.py b/sklearnex/spmd/decomposition/tests/test_pca_spmd.py
@@ -90,7 +90,7 @@ def test_pca_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("whiten", [True, False])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/ensemble/tests/test_forest_spmd.py b/sklearnex/spmd/ensemble/tests/test_forest_spmd.py
@@ -107,7 +107,7 @@ def test_rfcls_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("local_trees_mode", [False, True])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
@@ -242,7 +242,7 @@ def test_rfreg_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("local_trees_mode", [False, True])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/linear_model/tests/test_incremental_linear_spmd.py b/sklearnex/spmd/linear_model/tests/test_incremental_linear_spmd.py
@@ -37,7 +37,7 @@
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("fit_intercept", [True, False])
 @pytest.mark.parametrize("macro_block", [None, 1024])
@@ -196,7 +196,7 @@ def test_incremental_linear_regression_partial_fit_spmd_gold(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("fit_intercept", [True, False])
 @pytest.mark.parametrize("num_samples", [100, 1000])
@@ -261,7 +261,7 @@ def test_incremental_linear_regression_fit_spmd_random(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("fit_intercept", [True, False])
 @pytest.mark.parametrize("num_blocks", [1, 2])
diff --git a/sklearnex/spmd/linear_model/tests/test_linear_regression_spmd.py b/sklearnex/spmd/linear_model/tests/test_linear_regression_spmd.py
@@ -102,7 +102,7 @@ def test_linear_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("n_features", [10, 100])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/linear_model/tests/test_logistic_regression_spmd.py b/sklearnex/spmd/linear_model/tests/test_logistic_regression_spmd.py
@@ -112,7 +112,7 @@ def test_logistic_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("tol", [1e-2, 1e-4])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
diff --git a/sklearnex/spmd/neighbors/tests/test_neighbors_spmd.py b/sklearnex/spmd/neighbors/tests/test_neighbors_spmd.py
@@ -109,7 +109,7 @@ def test_knncls_spmd_gold(dataframe, queue):
 @pytest.mark.parametrize("weights", ["uniform", "distance"])
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
@@ -247,7 +247,7 @@ def test_knnreg_spmd_gold(dataframe, queue):
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
@@ -312,7 +312,7 @@ def test_knnreg_spmd_synthetic(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.mpi
 def test_knnsearch_spmd_gold(dataframe, queue):
@@ -349,7 +349,7 @@ def test_knnsearch_spmd_gold(dataframe, queue):
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.parametrize("dtype", [np.float32, np.float64])
 @pytest.mark.parametrize("array_api_dispatch", [True, False])
@@ -398,7 +398,7 @@ def test_knnsearch_spmd_synthetic(
 )
 @pytest.mark.parametrize(
     "dataframe,queue",
-    get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),
+    get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),
 )
 @pytest.mark.mpi
 def test_knn_spmd_empty_kneighbors(dataframe, queue):

Original file line number	Diff line number	Diff line change
`@@ -104,7 +104,7 @@ def test_incremental_basic_statistics_fit_spmd_gold(dataframe, queue, weighted,`
`104`	`104`	`)`
`105`	`105`	`@pytest.mark.parametrize(`
`106`	`106`	`"dataframe,queue",`
`107`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`107`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`108`	`108`	`)`
`109`	`109`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
`110`	`110`	`@pytest.mark.parametrize("weighted", [True, False])`
`@@ -178,7 +178,7 @@ def test_incremental_basic_statistics_partial_fit_spmd_gold(`
`178`	`178`	`)`
`179`	`179`	`@pytest.mark.parametrize(`
`180`	`180`	`"dataframe,queue",`
`181`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`181`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`182`	`182`	`)`
`183`	`183`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
`184`	`184`	`@pytest.mark.parametrize("weighted", [True, False])`
`@@ -247,7 +247,7 @@ def test_incremental_basic_statistics_single_option_partial_fit_spmd_gold(`
`247`	`247`	`)`
`248`	`248`	`@pytest.mark.parametrize(`
`249`	`249`	`"dataframe,queue",`
`250`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`250`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`251`	`251`	`)`
`252`	`252`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
`253`	`253`	`@pytest.mark.parametrize("weighted", [True, False])`
Original file line number	Diff line number	Diff line change
`@@ -67,7 +67,7 @@ def test_dbscan_spmd_gold(dataframe, queue):`
`67`	`67`	`@pytest.mark.parametrize("min_samples", [2, 5, 15])`
`68`	`68`	`@pytest.mark.parametrize(`
`69`	`69`	`"dataframe,queue",`
`70`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`70`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`71`	`71`	`)`
`72`	`72`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`73`	`73`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`
Original file line number	Diff line number	Diff line change
`@@ -107,7 +107,7 @@ def test_kmeans_spmd_gold(dataframe, queue):`
`107`	`107`	`@pytest.mark.parametrize("n_clusters", [2, 5, 15])`
`108`	`108`	`@pytest.mark.parametrize(`
`109`	`109`	`"dataframe,queue",`
`110`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`110`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`111`	`111`	`)`
`112`	`112`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`113`	`113`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`
Original file line number	Diff line number	Diff line change
`@@ -83,7 +83,7 @@ def test_covariance_spmd_gold(dataframe, queue):`
`83`	`83`	`@pytest.mark.parametrize("assume_centered", [True, False])`
`84`	`84`	`@pytest.mark.parametrize(`
`85`	`85`	`"dataframe,queue",`
`86`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`86`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`87`	`87`	`)`
`88`	`88`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`89`	`89`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`
Original file line number	Diff line number	Diff line change
`@@ -88,7 +88,7 @@ def test_incremental_covariance_fit_spmd_gold(dataframe, queue, assume_centered,`
`88`	`88`	`)`
`89`	`89`	`@pytest.mark.parametrize(`
`90`	`90`	`"dataframe,queue",`
`91`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`91`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`92`	`92`	`)`
`93`	`93`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
`94`	`94`	`@pytest.mark.parametrize("assume_centered", [True, False])`
`@@ -149,7 +149,7 @@ def test_incremental_covariance_partial_fit_spmd_gold(`
`149`	`149`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`150`	`150`	`@pytest.mark.parametrize(`
`151`	`151`	`"dataframe,queue",`
`152`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`152`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`153`	`153`	`)`
`154`	`154`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`
`155`	`155`	`@pytest.mark.mpi`
Original file line number	Diff line number	Diff line change
`@@ -95,7 +95,7 @@ def test_incremental_pca_fit_spmd_gold(dataframe, queue, whiten, dtype):`
`95`	`95`	`)`
`96`	`96`	`@pytest.mark.parametrize(`
`97`	`97`	`"dataframe,queue",`
`98`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`98`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`99`	`99`	`)`
`100`	`100`	`@pytest.mark.parametrize("whiten", [True, False])`
`101`	`101`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
`@@ -159,7 +159,7 @@ def test_incremental_pca_partial_fit_spmd_gold(`
`159`	`159`	`)`
`160`	`160`	`@pytest.mark.parametrize(`
`161`	`161`	`"dataframe,queue",`
`162`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`162`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`163`	`163`	`)`
`164`	`164`	`@pytest.mark.parametrize("whiten", [True, False])`
`165`	`165`	`@pytest.mark.parametrize("n_components", [None, 2, 5])`
`@@ -211,7 +211,7 @@ def test_incremental_pca_fit_spmd_random(`
`211`	`211`	`)`
`212`	`212`	`@pytest.mark.parametrize(`
`213`	`213`	`"dataframe,queue",`
`214`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`214`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`215`	`215`	`)`
`216`	`216`	`@pytest.mark.parametrize("whiten", [True, False])`
`217`	`217`	`@pytest.mark.parametrize("n_components", [None, 2, 5])`
Original file line number	Diff line number	Diff line change
`@@ -90,7 +90,7 @@ def test_pca_spmd_gold(dataframe, queue):`
`90`	`90`	`@pytest.mark.parametrize("whiten", [True, False])`
`91`	`91`	`@pytest.mark.parametrize(`
`92`	`92`	`"dataframe,queue",`
`93`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`93`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`94`	`94`	`)`
`95`	`95`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`96`	`96`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`
Original file line number	Diff line number	Diff line change
`@@ -37,7 +37,7 @@`
`37`	`37`	`)`
`38`	`38`	`@pytest.mark.parametrize(`
`39`	`39`	`"dataframe,queue",`
`40`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`40`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`41`	`41`	`)`
`42`	`42`	`@pytest.mark.parametrize("fit_intercept", [True, False])`
`43`	`43`	`@pytest.mark.parametrize("macro_block", [None, 1024])`
`@@ -196,7 +196,7 @@ def test_incremental_linear_regression_partial_fit_spmd_gold(`
`196`	`196`	`)`
`197`	`197`	`@pytest.mark.parametrize(`
`198`	`198`	`"dataframe,queue",`
`199`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`199`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`200`	`200`	`)`
`201`	`201`	`@pytest.mark.parametrize("fit_intercept", [True, False])`
`202`	`202`	`@pytest.mark.parametrize("num_samples", [100, 1000])`
`@@ -261,7 +261,7 @@ def test_incremental_linear_regression_fit_spmd_random(`
`261`	`261`	`)`
`262`	`262`	`@pytest.mark.parametrize(`
`263`	`263`	`"dataframe,queue",`
`264`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`264`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`265`	`265`	`)`
`266`	`266`	`@pytest.mark.parametrize("fit_intercept", [True, False])`
`267`	`267`	`@pytest.mark.parametrize("num_blocks", [1, 2])`
Original file line number	Diff line number	Diff line change
`@@ -102,7 +102,7 @@ def test_linear_spmd_gold(dataframe, queue):`
`102`	`102`	`@pytest.mark.parametrize("n_features", [10, 100])`
`103`	`103`	`@pytest.mark.parametrize(`
`104`	`104`	`"dataframe,queue",`
`105`		`- get_dataframes_and_queues(dataframe_filter_="dpnp", device_filter_="gpu"),`
	`105`	`+ get_dataframes_and_queues(dataframe_filter_="dpnp,torch", device_filter_="gpu"),`
`106`	`106`	`)`
`107`	`107`	`@pytest.mark.parametrize("dtype", [np.float32, np.float64])`
`108`	`108`	`@pytest.mark.parametrize("array_api_dispatch", [True, False])`