diff --git a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/examples/run_mtl.py b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/examples/run_mtl.py
index e20b223631fb32a06bb583c614854a13325b687d..e2ee2d098dacf28255cc5ba999daeebb38534e61 100644
--- a/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/examples/run_mtl.py
+++ b/TensorFlow/built-in/recommendation/DeepCTR_Series_for_TensorFlow/examples/run_mtl.py
@@ -61,16 +61,16 @@ def main():
     custom_op.name = "NpuOptimizer"
     custom_op.parameter_map["precision_mode"].s = tf.compat.as_bytes(args.precision_mode)
 
-    if args.profiling:
-        custom_op.parameter_map["profiling_mode"].b = True
-        custom_op.parameter_map["profiling_options"].s = tf.compat.as_bytes(
-            '{"output":"' + args.profiling_dump_path + '", \
-                          "training_trace":"on", \
-                          "task_trace":"on", \
-                          "aicpu":"on", \
-                          "aic_metrics":"PipeUtilization",\
-                          "fp_point":"concatenate_1/concat", \
-                          "bp_point":"training/Adam/gradients/gradients/AddN_38"}')
+    #if args.profiling:
+    #    custom_op.parameter_map["profiling_mode"].b = True
+    #    custom_op.parameter_map["profiling_options"].s = tf.compat.as_bytes(
+    #        '{"output":"' + args.profiling_dump_path + '", \
+    #                      "training_trace":"on", \
+    #                      "task_trace":"on", \
+    #                      "aicpu":"on", \
+    #                      "aic_metrics":"PipeUtilization",\
+    #                      "fp_point":"concatenate_1/concat", \
+    #                      "bp_point":"training/Adam/gradients/gradients/AddN_38"}')
 
     npu_keras_sess = set_keras_session_npu_config(config=sess_config)
     column_names = ['age', 'class_worker', 'det_ind_code', 'det_occ_code', 'education', 'wage_per_hour', 'hs_college',