diff --git a/debug/accuracy_tools/msprobe/pytorch/monitor/anomaly_detect.py b/debug/accuracy_tools/msprobe/pytorch/monitor/anomaly_detect.py
index fbfcac10f506799041a16b5b745573860d7c26ec..128e71d253f311ff3f2bac8528d18a206f9abe00 100644
--- a/debug/accuracy_tools/msprobe/pytorch/monitor/anomaly_detect.py
+++ b/debug/accuracy_tools/msprobe/pytorch/monitor/anomaly_detect.py
@@ -379,7 +379,7 @@ class CSVWriterWithAD(BaseWriterWithAD):
                 input_and_output = [MonitorConst.ACTV_IN, MonitorConst.ACTV_OUT]
             else:
                 input_and_output = [MonitorConst.ACTVGRAD_IN, MonitorConst.ACTVGRAD_OUT]
-            ops_ = [MonitorConst.DOT.join(i[::-1]) for i in itertools.product(ops, input_and_output)]
+            ops_ = [MonitorConst.DOT.join(i) for i in itertools.product(input_and_output, ops)]
             csv_header = ["module_name", "step", *ops_]
         else:
             csv_header = ["param_name", "step", *ops]
diff --git a/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/config/xy_config.json b/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/config/xy_config.json
index d299be07870f58199185ad19cff7cb086fba6827..8540929ad2d4163f0064d165b5b9cb2da4261ab0 100644
--- a/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/config/xy_config.json
+++ b/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/config/xy_config.json
@@ -4,5 +4,5 @@
     "xy_distribution": true,
     "all_xy": true,
     "format": "csv",
-    "ops": ["norm"]
+    "ops": ["norm", "nans"]
 }
\ No newline at end of file
diff --git a/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/test_module_hook.py b/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/test_module_hook.py
index 6bf8582c02f5a31eb29e71e19462b11419f4782d..e31e4829c8395fb5736dde76795a971d732ac34a 100644
--- a/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/test_module_hook.py
+++ b/debug/accuracy_tools/msprobe/test/pytorch_ut/monitor/test_module_hook.py
@@ -73,13 +73,13 @@ class TestModuleHook(unittest.TestCase):
         self.assertTrue(os.path.exists(actv_grad_0_csv))
         # validate columns and lines
         actv_0 = pd.read_csv(actv_0_csv)
-        expect_columns = ['vpp_stage', 'module_name', 'step', 'input.norm', 'output.norm']
+        expect_columns = ['vpp_stage', 'module_name', 'step', 'input.norm', 'input.nans', 'output.norm', 'output.nans']
         self.assertListEqual(list(actv_0.columns), expect_columns)
-        self.assertEqual(actv_0.shape, tuple([2, 5]))
+        self.assertEqual(actv_0.shape, tuple([2, 7]))
         actv_grad_0 = pd.read_csv(actv_grad_0_csv)
-        expect_columns = ['vpp_stage', 'module_name', 'step', 'input_grad.norm', 'output_grad.norm']
+        expect_columns = ['vpp_stage', 'module_name', 'step', 'input_grad.norm', 'input_grad.nans', 'output_grad.norm', 'output_grad.nans']
         self.assertListEqual(list(actv_grad_0.columns), expect_columns)
-        self.assertEqual(actv_0.shape, tuple([2, 5]))
+        self.assertEqual(actv_0.shape, tuple([2, 7]))
 
     def test_wg_distribution(self):
         self.get_dist_mock(False)