fix an infer bug of understand_sentiment (#2164) (#2165)

* fix a infer bug of understand_sentiment.

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)
 ```

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)
 ```

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)
 ```

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)
 ```

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"

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"

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"