diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_transformer.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_transformer.py
index 954a40779d0ffcdbbf02b722ea0609bcda555f67..588d2b1f207308fac25eec9c758cbbba9d00b87e 100644
--- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_transformer.py
+++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_transformer.py
@@ -29,7 +29,7 @@ trainer_count = 1
 place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda() else fluid.CPUPlace(
 )
 SEED = 10
-step_num = 10
+STEP_NUM = 10
 
 
 def train_static(args, batch_generator):
@@ -109,7 +109,7 @@ def train_static(args, batch_generator):
                 else:
                     logging.info(
                         "step_idx: %d, epoch: %d, batch: %d, avg loss: %f, "
-                        "normalized loss: %f, ppl: %f, speed: %.2f step/s" %
+                        "normalized loss: %f, ppl: %f, speed: %.2f steps/s" %
                         (step_idx, pass_id, batch_id, total_avg_cost,
                          total_avg_cost - loss_normalizer,
                          np.exp([min(total_avg_cost, 100)]),
@@ -118,7 +118,7 @@ def train_static(args, batch_generator):
             batch_id += 1
             step_idx += 1
             total_batch_num = total_batch_num + 1
-            if step_idx == step_num:
+            if step_idx == STEP_NUM:
                 if args.save_dygraph_model_path:
                     model_path = os.path.join(args.save_static_model_path,
                                               "transformer")
@@ -193,7 +193,8 @@ def train_dygraph(args, batch_generator):
                     else:
                         logging.info(
                             "step_idx: %d, epoch: %d, batch: %d, avg loss: %f, "
-                            "normalized loss: %f, ppl: %f, speed: %.2f step/s" %
+                            "normalized loss: %f, ppl: %f, speed: %.2f steps/s"
+                            %
                             (step_idx, pass_id, batch_id, total_avg_cost,
                              total_avg_cost - loss_normalizer,
                              np.exp([min(total_avg_cost, 100)]),
@@ -202,7 +203,7 @@ def train_dygraph(args, batch_generator):
                         avg_batch_time = time.time()
                 batch_id += 1
                 step_idx += 1
-                if step_idx == step_num:
+                if step_idx == STEP_NUM:
                     if args.save_dygraph_model_path:
                         model_dir = os.path.join(args.save_dygraph_model_path)
                         if not os.path.exists(model_dir):
@@ -277,14 +278,14 @@ def predict_dygraph(args, batch_generator):
                     speed = args.print_step / (time.time() - avg_batch_time)
                     speed_list.append(speed)
                     logging.info(
-                        "Dygraph Predict: step_idx: %d, 1st seq_id: %d, 1st seq_score: %.2f, speed: %.3f step/s"
+                        "Dygraph Predict: step_idx: %d, 1st seq_id: %d, 1st seq_score: %.2f, speed: %.3f steps/s"
                         % (step_idx, seq_ids[0][0][0], seq_scores[0][0], speed))
                     avg_batch_time = time.time()
 
             step_idx += 1
-            if step_idx == step_num:
+            if step_idx == STEP_NUM:
                 break
-        logging.info("Dygraph Predict:  avg_speed: %.4f step/s" %
+        logging.info("Dygraph Predict:  avg_speed: %.4f steps/s" %
                      (np.mean(speed_list)))
         return seq_ids, seq_scores
 
@@ -353,14 +354,14 @@ def predict_static(args, batch_generator):
                 speed = args.print_step / (time.time() - avg_batch_time)
                 speed_list.append(speed)
                 logging.info(
-                    "Static Predict: step_idx: %d, 1st seq_id: %d, 1st seq_score: %.2f, speed: %.3f step/s"
+                    "Static Predict: step_idx: %d, 1st seq_id: %d, 1st seq_score: %.2f, speed: %.3f steps/s"
                     % (step_idx, seq_ids[0][0][0], seq_scores[0][0], speed))
                 avg_batch_time = time.time()
 
         step_idx += 1
-        if step_idx == step_num:
+        if step_idx == STEP_NUM:
             break
-    logging.info("Static Predict:  avg_speed: %.4f step/s" %
+    logging.info("Static Predict:  avg_speed: %.4f steps/s" %
                  (np.mean(speed_list)))
 
     return seq_ids, seq_scores
diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py
index 669106b45b4f93e36617050e07f86cf01390fabe..27b24e120d74898cfd1d56855e7983cb1bc29b08 100644
--- a/python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py
+++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/transformer_dygraph_model.py
@@ -608,8 +608,8 @@ class Transformer(Layer):
         } for i in range(self.n_layer)]
 
         for i in range(max_len):
-            trg_pos = layers.zeros_like(
-                trg_word) + i  # TODO: modified for dygraph2static
+            trg_pos = layers.fill_constant(
+                shape=trg_word.shape, dtype="int64", value=i)
             caches = map_structure(merge_batch_beams,
                                    caches)  # TODO: modified for dygraph2static
             logits = self.decoder(trg_word, trg_pos, None, trg_src_attn_bias,