diff --git a/sklearnex/linear_model/tests/test_incremental_linear.py b/sklearnex/linear_model/tests/test_incremental_linear.py
index 54c33239ee..296c714ead 100644
--- a/sklearnex/linear_model/tests/test_incremental_linear.py
+++ b/sklearnex/linear_model/tests/test_incremental_linear.py
@@ -46,12 +46,13 @@ def test_sklearnex_fit_on_gold_data(dataframe, queue, fit_intercept, macro_block
     inclin.fit(X_df, y_df)
 
     y_pred = inclin.predict(X_df)
+    np_y_pred = _as_numpy(y_pred)
 
-    tol = 2e-6 if y_pred.dtype == np.float32 else 1e-7
+    tol = 2e-6 if dtype == np.float32 else 1e-7
     assert_allclose(inclin.coef_, [1], atol=tol)
     if fit_intercept:
         assert_allclose(inclin.intercept_, [0], atol=tol)
-    assert_allclose(_as_numpy(y_pred), y, atol=tol)
+    assert_allclose(np_y_pred, y, atol=tol)
 
 
 @pytest.mark.parametrize("dataframe,queue", get_dataframes_and_queues())
@@ -84,14 +85,15 @@ def test_sklearnex_partial_fit_on_gold_data(
 
     X_df = _convert_to_dataframe(X, sycl_queue=queue, target_df=dataframe)
     y_pred = inclin.predict(X_df)
+    np_y_pred = _as_numpy(y_pred)
 
     assert inclin.n_features_in_ == 1
-    tol = 2e-6 if y_pred.dtype == np.float32 else 1e-7
+    tol = 2e-6 if dtype == np.float32 else 1e-7
     assert_allclose(inclin.coef_, [[1]], atol=tol)
     if fit_intercept:
         assert_allclose(inclin.intercept_, 3, atol=tol)
 
-    assert_allclose(_as_numpy(y_pred), y, atol=tol)
+    assert_allclose(np_y_pred, y, atol=tol)
 
 
 @pytest.mark.parametrize("dataframe,queue", get_dataframes_and_queues())
@@ -124,14 +126,15 @@ def test_sklearnex_partial_fit_multitarget_on_gold_data(
 
     X_df = _convert_to_dataframe(X, sycl_queue=queue, target_df=dataframe)
     y_pred = inclin.predict(X_df)
+    np_y_pred = _as_numpy(y_pred)
 
     assert inclin.n_features_in_ == 2
-    tol = 7e-6 if y_pred.dtype == np.float32 else 1e-7
+    tol = 7e-6 if dtype == np.float32 else 1e-7
     assert_allclose(inclin.coef_, [1.0, 2.0], atol=tol)
     if fit_intercept:
         assert_allclose(inclin.intercept_, 3.0, atol=tol)
 
-    assert_allclose(_as_numpy(y_pred), y, atol=tol)
+    assert_allclose(np_y_pred, y, atol=tol)
 
 
 @pytest.mark.parametrize("dataframe,queue", get_dataframes_and_queues())
diff --git a/sklearnex/preview/decomposition/tests/test_incremental_pca.py b/sklearnex/preview/decomposition/tests/test_incremental_pca.py
index 786ae4fef0..67929bfac8 100644
--- a/sklearnex/preview/decomposition/tests/test_incremental_pca.py
+++ b/sklearnex/preview/decomposition/tests/test_incremental_pca.py
@@ -74,7 +74,7 @@ def check_pca_on_gold_data(incpca, dtype, whiten, transformed_data):
     )
 
     tol = 1e-7
-    if transformed_data.dtype == np.float32:
+    if dtype == np.float32:
         tol = 7e-6 if whiten else 1e-6
 
     assert incpca.n_samples_seen_ == expected_n_samples_seen_
@@ -112,7 +112,7 @@ def check_pca_on_gold_data(incpca, dtype, whiten, transformed_data):
 
 
 def check_pca(incpca, dtype, whiten, data, transformed_data):
-    tol = 3e-3 if transformed_data.dtype == np.float32 else 2e-6
+    tol = 3e-3 if dtype == np.float32 else 2e-6
 
     n_components = incpca.n_components_