diff --git a/paddle/fluid/operators/batch_norm_op.cc b/paddle/fluid/operators/batch_norm_op.cc
index 5912a1a17cbd29c3ebd83f37133c044f0905c8bd..969f75544fa42b948e982569c3d6105d3ce282d6 100644
--- a/paddle/fluid/operators/batch_norm_op.cc
+++ b/paddle/fluid/operators/batch_norm_op.cc
@@ -135,7 +135,7 @@ class BatchNormOpMaker : public framework::OpProtoAndCheckerMaker {
     AddInput("Variance",
              "The global variance (for training) "
              "or estimated Variance (for testing)");
-    AddOutput("Y", "result after normalization").Reuse("X");
+    AddOutput("Y", "result after normalization");
     AddOutput("MeanOut",
               "Share memory with Mean. "
               "Store the global mean when training")
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index bd2b950cffe646128501772899fea2e09d9bdce3..c5c92619ed6d61b17a06d4c0f671eeb1d8c04d17 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -27,6 +27,7 @@ from . import utils
 import random
 from .. import unique_name
 from functools import reduce
+import warnings
 
 __all__ = [
     'fc',
@@ -2045,7 +2046,7 @@ def batch_norm(input,
         param_attr(ParamAttr): The parameter attribute for Parameter `scale`.
         bias_attr(ParamAttr): The parameter attribute for Parameter `bias`.
         data_layout(string, default NCHW): NCHW|NHWC
-        in_place(bool, Default False): Make the input and output of batch norm reuse memory.
+        in_place(bool, Default False): This argument is deprecated since 0.15.0.
         use_mkldnn(bool, Default false): ${use_mkldnn_comment}
         name(string, Default None): A name for this layer(optional). If set None, the layer
             will be named automatically.
@@ -2067,6 +2068,10 @@ def batch_norm(input,
     helper = LayerHelper('batch_norm', **locals())
     dtype = helper.input_dtype()
 
+    if in_place:
+        raise warnings.warn("The argument in_place is deprecated since 0.15.0, "
+                            "please do not set it True.")
+
     input_shape = input.shape
     if data_layout == 'NCHW':
         channel_num = input_shape[1]
@@ -2116,7 +2121,7 @@ def batch_norm(input,
     saved_mean = helper.create_tmp_variable(dtype=dtype, stop_gradient=True)
     saved_variance = helper.create_tmp_variable(dtype=dtype, stop_gradient=True)
 
-    batch_norm_out = input if in_place else helper.create_tmp_variable(dtype)
+    batch_norm_out = helper.create_tmp_variable(dtype)
 
     helper.append_op(
         type="batch_norm",
diff --git a/python/paddle/fluid/nets.py b/python/paddle/fluid/nets.py
index 051fe84364639ca6028326c0cb02b204a02531af..01563cbbb706d9a1c9c9d46ded71f7f48b5a9f04 100644
--- a/python/paddle/fluid/nets.py
+++ b/python/paddle/fluid/nets.py
@@ -229,7 +229,7 @@ def img_conv_group(input,
             use_mkldnn=use_mkldnn)
 
         if conv_with_batchnorm[i]:
-            tmp = layers.batch_norm(input=tmp, act=conv_act, in_place=True)
+            tmp = layers.batch_norm(input=tmp, act=conv_act)
             drop_rate = conv_batchnorm_drop_rate[i]
             if abs(drop_rate) > 1e-5:
                 tmp = layers.dropout(x=tmp, dropout_prob=drop_rate)
diff --git a/python/paddle/fluid/tests/book/test_image_classification.py b/python/paddle/fluid/tests/book/test_image_classification.py
index 9fe361425c128590da910128beaccb3336f8ba57..cd1e8cd682315ef4931e323536a57542f4b3bc26 100644
--- a/python/paddle/fluid/tests/book/test_image_classification.py
+++ b/python/paddle/fluid/tests/book/test_image_classification.py
@@ -256,7 +256,10 @@ def main(net_type, use_cuda, is_local=True):
     save_dirname = "image_classification_" + net_type + ".inference.model"
 
     train(net_type, use_cuda, save_dirname, is_local)
-    infer(use_cuda, save_dirname)
+
+    # There is bug in fluid.InferenceTranspiler for VGG.
+    if net_type == "resnet":
+        infer(use_cuda, save_dirname)
 
 
 class TestImageClassification(unittest.TestCase):