diff --git a/PaddleNLP/language_representations_kit/BERT/README.md b/PaddleNLP/language_representations_kit/BERT/README.md
index 626f382aa37994b72ffc92921bf6b7a77f761278..7ed1d28bca0f5454995b6e67951894b7430c20bc 100644
--- a/PaddleNLP/language_representations_kit/BERT/README.md
+++ b/PaddleNLP/language_representations_kit/BERT/README.md
@@ -70,7 +70,7 @@
 ```
 
 ## 安装
-本项目依赖于 Paddle Fluid **1.5.1** 及以上版本，请参考[安装指南](http://www.paddlepaddle.org/#quick-start)进行安装。如果需要进行 TensorFlow 模型到 Paddle Fluid 参数的转换，则需要同时安装 TensorFlow 1.12。
+本项目依赖于 Paddle Fluid **1.6.0** 及以上版本，请参考[安装指南](http://www.paddlepaddle.org/#quick-start)进行安装。如果需要进行 TensorFlow 模型到 Paddle Fluid 参数的转换，则需要同时安装 TensorFlow 1.12。
 
 ## 预训练
 
diff --git a/PaddleNLP/language_representations_kit/BERT/model/classifier.py b/PaddleNLP/language_representations_kit/BERT/model/classifier.py
index 8b9fea2b7171b8e6dd123a4eb27fbf75b563328c..03bfb7aa1504253399b5bdd4d1f4fe9c41cad27b 100644
--- a/PaddleNLP/language_representations_kit/BERT/model/classifier.py
+++ b/PaddleNLP/language_representations_kit/BERT/model/classifier.py
@@ -26,13 +26,13 @@ def create_model(args, bert_config, num_labels, is_prediction=False):
     input_fields = {
         'names': ['src_ids', 'pos_ids', 'sent_ids', 'input_mask', 'labels'],
         'shapes': [[None, None], [None, None], [None, None],
-                   [-1, args.max_seq_len, 1], [-1, 1]],
+                   [None, args.max_seq_len, 1], [None, 1]],
         'dtypes': ['int64', 'int64', 'int64', 'float32', 'int64'],
         'lod_levels': [0, 0, 0, 0, 0],
     }
 
     inputs = [
-        fluid.layers.data(
+        fluid.data(
             name=input_fields['names'][i],
             shape=input_fields['shapes'][i],
             dtype=input_fields['dtypes'][i],
diff --git a/PaddleNLP/language_representations_kit/BERT/optimization.py b/PaddleNLP/language_representations_kit/BERT/optimization.py
index c0795018a883832b49660024aaa0ccac489c4a11..0771ab77922dea90104ff67ab201bfb307212637 100644
--- a/PaddleNLP/language_representations_kit/BERT/optimization.py
+++ b/PaddleNLP/language_representations_kit/BERT/optimization.py
@@ -73,9 +73,10 @@ def optimization(loss,
              .noam_decay(1/(warmup_steps *(learning_rate ** 2)),
            warmup_steps)
         else:
-            printf(
-                "WARNING: noam decay should have postive warmup steps, using "
-                "constant learning rate instead!")
+            print(
+                "WARNING: noam decay of learning rate should have postive warmup "
+                "steps but given {}, using constant learning rate instead!"
+                .format(warmup_steps))
             scheduled_lr = fluid.layers.create_global_var(
                 name=fluid.unique_name.generate("learning_rate"),
                 shape=[1],
@@ -83,8 +84,20 @@ def optimization(loss,
                 dtype='float32',
                 persistable=True)
     elif scheduler == 'linear_warmup_decay':
-        scheduled_lr = linear_warmup_decay(learning_rate, warmup_steps,
-                                           num_train_steps)
+        if warmup_steps > 0:
+            scheduled_lr = linear_warmup_decay(learning_rate, warmup_steps,
+                                               num_train_steps)
+        else:
+            print(
+                "WARNING: linear warmup decay of learning rate should have "
+                "postive warmup steps but given {}, use constant learning rate "
+                "instead!".format(warmup_steps))
+            scheduled_lr = fluid.layers.create_global_var(
+                name=fluid.unique_name.generate("learning_rate"),
+                shape=[1],
+                value=learning_rate,
+                dtype='float32',
+                persistable=True)
     else:
         raise ValueError("Unkown learning rate scheduler, should be "
                          "'noam_decay' or 'linear_warmup_decay'")
diff --git a/PaddleNLP/language_representations_kit/BERT/run_squad.py b/PaddleNLP/language_representations_kit/BERT/run_squad.py
index af0a706ca4296cb4f5899aee205288b01825bb00..fc3659b61eeb7d06c252a61f83c99fbe3adfea97 100644
--- a/PaddleNLP/language_representations_kit/BERT/run_squad.py
+++ b/PaddleNLP/language_representations_kit/BERT/run_squad.py
@@ -111,7 +111,7 @@ def create_model(bert_config, is_training=False):
         input_fields = {
             'names': ['src_ids', 'pos_ids', 'sent_ids', 'input_mask', 'start_positions', 'end_positions'],
             'shapes': [[None, None], [None, None], [None, None],
-                    [-1, args.max_seq_len, 1], [-1, 1], [-1, 1]],
+                    [None, args.max_seq_len, 1], [None, 1], [None, 1]],
             'dtypes': [
                 'int64', 'int64', 'int64', 'float32', 'int64', 'int64'],
             'lod_levels': [0, 0, 0, 0, 0, 0],
@@ -120,13 +120,13 @@ def create_model(bert_config, is_training=False):
         input_fields = {
             'names': ['src_ids', 'pos_ids', 'sent_ids', 'input_mask', 'unique_id'],
             'shapes': [[None, None], [None, None], [None, None],
-                    [-1, args.max_seq_len, 1], [-1, 1]],
+                    [None, args.max_seq_len, 1], [None, 1]],
             'dtypes': [
                 'int64', 'int64', 'int64', 'float32', 'int64'],
             'lod_levels': [0, 0, 0, 0, 0],
         }
 
-    inputs = [fluid.layers.data(name=input_fields['names'][i],
+    inputs = [fluid.data(name=input_fields['names'][i],
                       shape=input_fields['shapes'][i],
                       dtype=input_fields['dtypes'][i],
                       lod_level=input_fields['lod_levels'][i]) for i in range(len(input_fields['names']))]
diff --git a/PaddleNLP/language_representations_kit/BERT/train.py b/PaddleNLP/language_representations_kit/BERT/train.py
index 686e5281a11795ed7f08c6ecf9a5662cf809e112..f9a1fb49ef4fda9957f27e90b7a18cea6f6d4e4b 100644
--- a/PaddleNLP/language_representations_kit/BERT/train.py
+++ b/PaddleNLP/language_representations_kit/BERT/train.py
@@ -105,7 +105,7 @@ def create_model(bert_config):
         'lod_levels': [0, 0, 0, 0, 0, 0, 0],
     }
 
-    inputs = [fluid.layers.data(name=input_fields['names'][i],
+    inputs = [fluid.data(name=input_fields['names'][i],
                       shape=input_fields['shapes'][i],
                       dtype=input_fields['dtypes'][i],
                       lod_level=input_fields['lod_levels'][i]) for i in range(len(input_fields['names']))]