diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/README.cn.md b/doc/fluid/user_guides/nlp_case/understand_sentiment/README.cn.md
index 0ddf0365651b4fb6ae14ceab02afb18263971f7d..e1904dfa0890e80a48b41195ebd8adf931d460bd 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/README.cn.md
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/README.cn.md
@@ -394,7 +394,7 @@ inference_scope = fluid.core.Scope()
 
 ```python
 reviews_str = [
-    'read the book forget the movie', 'this is a great movie', 'this is very bad'
+    b'read the book forget the movie', b'this is a great movie', b'this is very bad'
 ]
 reviews = [c.split() for c in reviews_str]
 
@@ -404,6 +404,7 @@ for c in reviews:
     lod.append([word_dict.get(words, UNK) for words in c])
 
 base_shape = [[len(c) for c in lod]]
+lod = np.array(sum(lod, []), dtype=np.int64)
 
 tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
 ```
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/README.md b/doc/fluid/user_guides/nlp_case/understand_sentiment/README.md
index fa80ac7d8a5500fe4781b0e79e30ae4a2745a6ae..12aadc03a97a0b60bf46f21d527bbefd80c7227b 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/README.md
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/README.md
@@ -383,7 +383,7 @@ Then we use `create_lod_tensor` to create the tensor of the detail level. For a
 
 ```python
 reviews_str = [
-    'read the book forget the movie', 'this is a great movie', 'this is very bad'
+    b'read the book forget the movie', b'this is a great movie', b'this is very bad'
 ]
 reviews = [c.split() for c in reviews_str]
 
@@ -393,6 +393,7 @@ for c in reviews:
     lod.append([word_dict.get(words, UNK) for words in c])
 
 base_shape = [[len(c) for c in lod]]
+lod = np.array(sum(lod, []), dtype=np.int64)
 
 tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
 ```
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/index.cn.html b/doc/fluid/user_guides/nlp_case/understand_sentiment/index.cn.html
index 29ff80587b6ef8cbc8504ef30282fc286557938f..19fe031db4707ab8a89268b51d8848644a57cc95 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/index.cn.html
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/index.cn.html
@@ -436,7 +436,7 @@ inference_scope = fluid.core.Scope()
 
 ```python
 reviews_str = [
-    'read the book forget the movie', 'this is a great movie', 'this is very bad'
+    b'read the book forget the movie', b'this is a great movie', b'this is very bad'
 ]
 reviews = [c.split() for c in reviews_str]
 
@@ -446,6 +446,7 @@ for c in reviews:
     lod.append([word_dict.get(words, UNK) for words in c])
 
 base_shape = [[len(c) for c in lod]]
+lod = np.array(sum(lod, []), dtype=np.int64)
 
 tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
 ```
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/index.html b/doc/fluid/user_guides/nlp_case/understand_sentiment/index.html
index 679cdd76545f63cdb5bad135434e6e7a35014681..865141cc8f42537de9e5f1e957ac3e99ab339472 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/index.html
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/index.html
@@ -425,7 +425,7 @@ Then we use `create_lod_tensor` to create the tensor of the detail level. For a
 
 ```python
 reviews_str = [
-    'read the book forget the movie', 'this is a great movie', 'this is very bad'
+    b'read the book forget the movie', b'this is a great movie', b'this is very bad'
 ]
 reviews = [c.split() for c in reviews_str]
 
@@ -435,6 +435,7 @@ for c in reviews:
     lod.append([word_dict.get(words, UNK) for words in c])
 
 base_shape = [[len(c) for c in lod]]
+lod = np.array(sum(lod, []), dtype=np.int64)
 
 tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
 ```
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_conv.py b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_conv.py
index 74547461500e5532e44208ef2d589984a20320e8..456b127b92c6814fa44e7bc579e6e2f95110cb33 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_conv.py
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_conv.py
@@ -205,8 +205,8 @@ def infer(use_cuda, params_dirname=None):
         # length 3, 4 and 2, respectively.
         # Note that lod info should be a list of lists.
         reviews_str = [
-            'read the book forget the movie', 'this is a great movie',
-            'this is very bad'
+            b'read the book forget the movie', b'this is a great movie',
+            b'this is very bad'
         ]
         reviews = [c.split() for c in reviews_str]
 
@@ -216,6 +216,7 @@ def infer(use_cuda, params_dirname=None):
             lod.append([np.int64(word_dict.get(words, UNK)) for words in c])
 
         base_shape = [[len(c) for c in lod]]
+        lod = np.array(sum(lod, []), dtype=np.int64)
 
         tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
         assert feed_target_names[0] == "words"
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_dyn_rnn.py b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_dyn_rnn.py
index 78f3d64b43dc50efe195615016d5e92f2d40e9e5..b782f6435a68c0f01fae9e03568a8dc9946bee70 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_dyn_rnn.py
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_dyn_rnn.py
@@ -194,8 +194,8 @@ def infer(use_cuda, params_dirname=None):
         # length 3, 4 and 2, respectively.
         # Note that lod info should be a list of lists.
         reviews_str = [
-            'read the book forget the movie', 'this is a great movie',
-            'this is very bad'
+            b'read the book forget the movie', b'this is a great movie',
+            b'this is very bad'
         ]
         reviews = [c.split() for c in reviews_str]
 
@@ -205,6 +205,7 @@ def infer(use_cuda, params_dirname=None):
             lod.append([np.int64(word_dict.get(words, UNK)) for words in c])
 
         base_shape = [[len(c) for c in lod]]
+        lod = np.array(sum(lod, []), dtype=np.int64)
 
         tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
         assert feed_target_names[0] == "words"
diff --git a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_stacked_lstm.py b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_stacked_lstm.py
index 5878c7f738557e756e816b78d24af0c16b2b48bd..6db40f42a3fbda12c764d76151db21a1c3e4df04 100644
--- a/doc/fluid/user_guides/nlp_case/understand_sentiment/train_stacked_lstm.py
+++ b/doc/fluid/user_guides/nlp_case/understand_sentiment/train_stacked_lstm.py
@@ -216,8 +216,8 @@ def infer(use_cuda, params_dirname=None):
         # length 3, 4 and 2, respectively.
         # Note that lod info should be a list of lists.
         reviews_str = [
-            'read the book forget the movie', 'this is a great movie',
-            'this is very bad'
+            b'read the book forget the movie', b'this is a great movie',
+            b'this is very bad'
         ]
         reviews = [c.split() for c in reviews_str]
 
@@ -227,6 +227,7 @@ def infer(use_cuda, params_dirname=None):
             lod.append([np.int64(word_dict.get(words, UNK)) for words in c])
 
         base_shape = [[len(c) for c in lod]]
+        lod = np.array(sum(lod, []), dtype=np.int64)
 
         tensor_words = fluid.create_lod_tensor(lod, base_shape, place)
         assert feed_target_names[0] == "words"