diff --git a/python/paddle/fluid/debuger.py b/python/paddle/fluid/debuger.py
index b7a906654a7ed60d610fc2e9801bf6108e555dcb..97fa182c4007cc730c06e9f95259a2509e01ecdf 100644
--- a/python/paddle/fluid/debuger.py
+++ b/python/paddle/fluid/debuger.py
@@ -16,6 +16,7 @@ import sys
 import re
 from graphviz import GraphPreviewGenerator
 import proto.framework_pb2 as framework_pb2
+import paddle.fluid.core as core
 
 _vartype2str_ = [
     "UNK",
@@ -52,9 +53,11 @@ reprtpl = "{ttype} {name} ({reprs})"
 
 
 def repr_lodtensor(proto):
-    if not proto.lod_tensor: return
-    level = proto.lod_tensor.lod_level
-    reprs = repr_tensor(proto.lod_tensor.tensor)
+    if proto.type.type != framework_pb2.VarType.LOD_TENSOR:
+        return
+
+    level = proto.type.lod_tensor.lod_level
+    reprs = repr_tensor(proto.type.lod_tensor.tensor)
     return reprtpl.format(
         ttype="LoDTensor" if level > 0 else "Tensor",
         name=proto.name,
@@ -62,20 +65,24 @@ def repr_lodtensor(proto):
 
 
 def repr_selected_rows(proto):
-    if not proto.selected_rows: return
+    if proto.type.type != framework_pb2.VarType.SELECTED_ROWS:
+        return
+
     return reprtpl.format(
         ttype="SelectedRows",
         name=proto.name,
-        reprs=repr_tensor(proto.selected_rows))
+        reprs=repr_tensor(proto.type.selected_rows))
 
 
 def repr_tensor_array(proto):
-    if not proto.tensor_array: return
+    if proto.type.type != framework_pb2.VarType.LOD_TENSOR_ARRAY:
+        return
+
     return reprtpl.format(
         ttype="TensorArray",
         name=proto.name,
-        reprs="level=%d, %s" % (proto.tensor_array.lod_level,
-                                repr_tensor(proto.lod_tensor)))
+        reprs="level=%d, %s" % (proto.type.tensor_array.lod_level,
+                                repr_tensor(proto.type.lod_tensor.tensor)))
 
 
 type_handlers = [
@@ -119,6 +126,7 @@ def pprint_block_codes(block_desc, show_backward=False):
     def is_var_backward(var_desc):
         return "@GRAD" in var_desc.name
 
+    #print(type(block_desc))
     if type(block_desc) is not framework_pb2.BlockDesc:
         block_desc = framework_pb2.BlockDesc.FromString(
             block_desc.serialize_to_string())
diff --git a/python/paddle/fluid/tests/unittests/test_debugger.py b/python/paddle/fluid/tests/unittests/test_debugger.py
new file mode 100644
index 0000000000000000000000000000000000000000..2b7bbf9218f9b8fd8f5b29ac3cbc2f9680f471eb
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/test_debugger.py
@@ -0,0 +1,58 @@
+#   Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import unittest
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid import debuger
+from paddle.fluid.framework import Program
+
+
+class TestDebugger(unittest.TestCase):
+    def test_debug_str(self):
+        p = Program()
+        b = p.current_block()
+
+        #selected_rows
+        b.create_var(
+            name='selected_rows',
+            dtype="float32",
+            shape=[5, 10],
+            type=core.VarDesc.VarType.SELECTED_ROWS)
+
+        #tensor array
+        b.create_var(
+            name='tensor_array',
+            shape=[5, 10],
+            type=core.VarDesc.VarType.LOD_TENSOR_ARRAY)
+
+        #operator
+        mul_x = b.create_parameter(
+            dtype="float32", shape=[5, 10], lod_level=0, name="mul.x")
+        mul_y = b.create_var(
+            dtype="float32", shape=[10, 8], lod_level=0, name="mul.y")
+        mul_out = b.create_var(
+            dtype="float32", shape=[5, 8], lod_level=0, name="mul.out")
+        b.append_op(
+            type="mul",
+            inputs={"X": mul_x,
+                    "Y": mul_y},
+            outputs={"Out": mul_out},
+            attrs={"x_num_col_dims": 1})
+
+        print(debuger.pprint_program_codes(p.desc))
+
+
+if __name__ == '__main__':
+    unittest.main()