Move gen_sparse_dataset function from basic statistic test to sklearn…

…ex/tests/utils/base.py

sklearnex/basic_statistics/tests/test_basic_statistics.py

@@ -28,16 +28,10 @@
 )
 from sklearnex import config_context
 from sklearnex.basic_statistics import BasicStatistics
+from sklearnex.tests.utils import gen_sparse_dataset
 
 
-# Generate random sparse data using scipy.sparse.random or scipy.sparse.random_array
-def gen_sparse_data(row_count, column_count, **kwargs):
-    if hasattr(sp, "random_array"):
-        return sp.random_array((row_count, column_count), **kwargs)
-    else:
-        return sp.random(row_count, column_count, **kwargs)
-
-
+# Compute the basic statistics on sparse data on CPU or GPU depending on the queue
 def compute_sparse_result(X_sparse, options, queue):
     if queue is not None and queue.sycl_device.is_gpu:
         with config_context(target_offload="gpu"):
@@ -168,7 +162,7 @@ def test_single_option_on_random_sparse_data(
 
     gen = np.random.default_rng(seed)
 
-    X_sparse = gen_sparse_data(
+    X_sparse = gen_sparse_dataset(
         row_count,
         column_count,
         density=0.01,
@@ -243,7 +237,7 @@ def test_multiple_options_on_random_sparse_data(queue, row_count, column_count,
 
     gen = np.random.default_rng(seed)
 
-    X_sparse = gen_sparse_data(
+    X_sparse = gen_sparse_dataset(
         row_count,
         column_count,
         density=0.05,
@@ -324,7 +318,7 @@ def test_all_option_on_random_sparse_data(queue, row_count, column_count, dtype)
 
     gen = np.random.default_rng(seed)
 
-    X_sparse = gen_sparse_data(
+    X_sparse = gen_sparse_dataset(
         row_count,
         column_count,
         density=0.05,

sklearnex/tests/utils/__init__.py

@@ -25,6 +25,7 @@
     _get_processor_info,
     call_method,
     gen_dataset,
+    gen_sparse_dataset,
     gen_models_info,
     sklearn_clone_dict,
 )
@@ -39,6 +40,7 @@
     "call_method",
     "gen_models_info",
     "gen_dataset",
+    "gen_sparse_dataset",
     "sklearn_clone_dict",
     "DummyEstimator",
 ]

sklearnex/tests/utils/base.py

@@ -339,6 +339,27 @@ def gen_dataset(
     return output
 
 
+def gen_sparse_dataset(row_count, column_count, **kwargs):
+    """Generate sparse dataset for pytest testing.
+
+    Parameters
+    ----------
+    row_count : number of rows in dataset
+
+    column_count: number of columns in dataset
+
+    kwargs: keyword arguments for scipy.sparse.random_array or scipy.sparse.random
+
+    Returns
+    -------
+    scipy.sparse random matrix or array depending on scipy version
+    """
+    if hasattr(sp, "random_array"):
+        return sp.random_array((row_count, column_count), **kwargs)
+    else:
+        return sp.random(row_count, column_count, **kwargs)
+
+
 DTYPES = [
     np.int8,
     np.int16,