fix error

python/paddle/fluid/tests/book/high-level-api/label_semantic_roles/test_label_semantic_roles_newapi.py

@@ -215,21 +215,21 @@ def infer(use_cuda, inference_program, save_path):
     lod = [[3, 4, 2]]
     base_shape = [1]
     # The range of random integers is [low, high]
-    word = fluid.create_random_lodtensor(
+    word = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    pred = fluid.create_random_lodtensor(
+    pred = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=PRED_DICT_LEN - 1)
-    ctx_n2 = fluid.create_random_lodtensor(
+    ctx_n2 = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    ctx_n1 = fluid.create_random_lodtensor(
+    ctx_n1 = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    ctx_0 = fluid.create_random_lodtensor(
+    ctx_0 = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    ctx_p1 = fluid.create_random_lodtensor(
+    ctx_p1 = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    ctx_p2 = fluid.create_random_lodtensor(
+    ctx_p2 = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=WORD_DICT_LEN - 1)
-    mark = fluid.create_random_lodtensor(
+    mark = fluid.create_random_int_lodtensor(
         lod, base_shape, place, low=0, high=MARK_DICT_LEN - 1)
 
     results = inferencer.infer(

python/paddle/fluid/tests/book/test_label_semantic_roles.py

@@ -261,21 +261,21 @@ def infer(use_cuda, save_dirname=None):
         lod = [[3, 4, 2]]
         base_shape = [1]
         # The range of random integers is [low, high]
-        word = fluid.create_random_lodtensor(
+        word = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        pred = fluid.create_random_lodtensor(
+        pred = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=pred_dict_len - 1)
-        ctx_n2 = fluid.create_random_lodtensor(
+        ctx_n2 = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        ctx_n1 = fluid.create_random_lodtensor(
+        ctx_n1 = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        ctx_0 = fluid.create_random_lodtensor(
+        ctx_0 = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        ctx_p1 = fluid.create_random_lodtensor(
+        ctx_p1 = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        ctx_p2 = fluid.create_random_lodtensor(
+        ctx_p2 = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=word_dict_len - 1)
-        mark = fluid.create_random_lodtensor(
+        mark = fluid.create_random_int_lodtensor(
             lod, base_shape, place, low=0, high=mark_dict_len - 1)
 
         # Construct feed as a dictionary of {feed_target_name: feed_target_data}