warning removal from BS examples

uxlfoundation · Dec 4, 2024 · 60aeaa6 · 60aeaa6
1 parent 8e4cde0
commit 60aeaa6
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Showing 3 changed files with 14 additions and 14 deletions.
diff --git a/examples/sklearnex/basic_statistics_spmd.py b/examples/sklearnex/basic_statistics_spmd.py
@@ -60,5 +60,5 @@ def generate_data(par, size, seed=777):
 bss = BasicStatisticsSpmd(["mean", "standard_deviation"])
 bss.fit(dpt_data, dpt_weights)
 
-print(f"Computed mean on rank {rank}:\n", bss.mean)
-print(f"Computed std on rank {rank}:\n", bss.standard_deviation)
+print(f"Computed mean on rank {rank}:\n", bss.mean_)
+print(f"Computed std on rank {rank}:\n", bss.standard_deviation_)
diff --git a/examples/sklearnex/incremental_basic_statistics.py b/examples/sklearnex/incremental_basic_statistics.py
@@ -30,16 +30,16 @@
 X_3 = np.array([[1, 1], [1, 2], [2, 3]])
 result = incbs.partial_fit(X_3)
 
-print(f"Mean:\n{result.mean}")
-print(f"Max:\n{result.max}")
-print(f"Sum:\n{result.sum}")
+print(f"Mean:\n{result.mean_}")
+print(f"Max:\n{result.max_}")
+print(f"Sum:\n{result.sum_}")
 
 # We put the whole data to fit method, it is split automatically and then
 # partial_fit is called for each batch.
 incbs = IncrementalBasicStatistics(result_options=["mean", "max", "sum"], batch_size=3)
 X = np.array([[0, 1], [0, 1], [1, 2], [1, 1], [1, 2], [2, 3]])
 result = incbs.fit(X)
 
-print(f"Mean:\n{result.mean}")
-print(f"Max:\n{result.max}")
-print(f"Sum:\n{result.sum}")
+print(f"Mean:\n{result.mean_}")
+print(f"Max:\n{result.max_}")
+print(f"Sum:\n{result.sum_}")
diff --git a/examples/sklearnex/incremental_basic_statistics_dpctl.py b/examples/sklearnex/incremental_basic_statistics_dpctl.py
@@ -36,16 +36,16 @@
 X_3 = dpt.asarray([[1, 1], [1, 2], [2, 3]], sycl_queue=queue)
 result = incbs.partial_fit(X_3)
 
-print(f"Mean:\n{result.mean}")
-print(f"Max:\n{result.max}")
-print(f"Sum:\n{result.sum}")
+print(f"Mean:\n{result.mean_}")
+print(f"Max:\n{result.max_}")
+print(f"Sum:\n{result.sum_}")
 
 # We put the whole data to fit method, it is split automatically and then
 # partial_fit is called for each batch.
 incbs = IncrementalBasicStatistics(result_options=["mean", "max", "sum"], batch_size=3)
 X = dpt.asarray([[0, 1], [0, 1], [1, 2], [1, 1], [1, 2], [2, 3]], sycl_queue=queue)
 result = incbs.fit(X)
 
-print(f"Mean:\n{result.mean}")
-print(f"Max:\n{result.max}")
-print(f"Sum:\n{result.sum}")
+print(f"Mean:\n{result.mean_}")
+print(f"Max:\n{result.max_}")
+print(f"Sum:\n{result.sum_}")