#12253: Add test for optional output tensor in BN

tests/ttnn/unit_tests/operations/test_batch_norm.py

@@ -407,3 +407,23 @@ def test_batch_norm_qid(input_shapes, device):
     torch_result = torch.nn.functional.batch_norm(input=in_data, running_mean=mean_data, running_var=var_data)
     comp_BN_Output = compare_results_batch_norm([tt_output], [torch_result])
     assert comp_BN_Output
+
+
+@pytest.mark.parametrize(
+    "input_shapes",
+    [
+        torch.Size([2, 3, 120, 120]),
+    ],
+)
+def test_batch_norm_output_Default(input_shapes, device):
+    N, H, W, C = input_shapes
+    _, tt_output_tensor = data_gen_with_range_batch_norm(input_shapes, 5, 10, device, is_input=True)
+    in_data, input_tensor = data_gen_with_range_batch_norm(input_shapes, 5, 10, device, is_input=True)
+    mean_data, mean_tensor = data_gen_with_range_batch_norm(input_shapes, 4, 10, device)
+    var_data, var_tensor = data_gen_with_range_batch_norm(input_shapes, 4, 20, device)
+
+    ttnn.batch_norm(input_tensor, running_mean=mean_tensor, running_var=var_tensor, queue_id=0, output=tt_output_tensor)
+    tt_output = ttnn.to_torch(tt_output_tensor)
+    torch_result = torch.nn.functional.batch_norm(input=in_data, running_mean=mean_data, running_var=var_data)
+    comp_BN_Output = compare_results_batch_norm([tt_output], [torch_result])
+    assert comp_BN_Output