diff --git a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py
index 518ef6a1bf7237d9e415485213317975555bcf01..ed920ad388ff0e01887404e70fe82565b4cd28fa 100644
--- a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py
+++ b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py
@@ -53,18 +53,11 @@ class TestLookupTableIdsIsSelectedRows(OpTest):
     def check_with_place(self, place):
         scope = core.Scope()
 
-        # create and initialize Grad Variable
+        # create and initialize Variable
         height = 10
         rows = [0, 4, 4, 7]
         row_numel = 12
 
-        ids_selected_rows = scope.var('Ids').get_selected_rows()
-        ids_selected_rows.set_height(height)
-        ids_selected_rows.set_rows(rows)
-        np_array = np.ones((len(rows), row_numel)).astype("float32")
-        ids_tensor = ids_selected_rows.get_tensor()
-        ids_tensor.set(np_array, place)
-
         # create and initialize W Variable
         W = scope.var('W').get_tensor()
         W_array = np.full((height, row_numel), 1.0).astype("float32")
@@ -72,20 +65,26 @@ class TestLookupTableIdsIsSelectedRows(OpTest):
             W_array[i] *= i
         W.set(W_array, place)
 
+        # create and initialize Ids Variable
+        ids_selected_rows = scope.var('Ids').get_selected_rows()
+        ids_selected_rows.set_height(len(rows))
+        ids_selected_rows.set_rows(rows)
+        np_array = np.ones((len(rows), row_numel)).astype("float32")
+        ids_tensor = ids_selected_rows.get_tensor()
+        ids_tensor.set(np_array, place)
+
+        # create Out Variable
         Out = scope.var('Out').get_selected_rows()
-        Out_array = np.full((len(rows), row_numel), -1.0).astype("float32")
-        Out.set_height(height)
-        Out.set_rows(rows)
-        Out_tensor = Out.get_tensor()
-        Out_tensor.set(Out_array, place)
 
-        # create and run concat_rows_op operator
+        # create and run lookup_table operator
         concat_rows_op = Operator("lookup_table", W='W', Ids='Ids', Out='Out')
         concat_rows_op.run(scope, place)
 
-        # get and compare result
+        # get result from Out
+        Out_tensor = Out.get_tensor()
         result_array = np.array(Out_tensor)
 
+        # all(): return True if all elements of the iterable are true (or if the iterable is empty)
         for idx, row in enumerate(rows):
             assert (row == result_array[idx]).all()