diff --git a/paddle/fluid/API.spec b/paddle/fluid/API.spec
index 868dbfa4ef1835052be278ab1ed79a95260437d3..0d48919869511834b95171ac3176b7f8ec6eeb94 100755
--- a/paddle/fluid/API.spec
+++ b/paddle/fluid/API.spec
@@ -134,14 +134,14 @@ paddle.fluid.layers.dynamic_gru (ArgSpec(args=['input', 'size', 'param_attr', 'b
 paddle.fluid.layers.gru_unit (ArgSpec(args=['input', 'hidden', 'size', 'param_attr', 'bias_attr', 'activation', 'gate_activation', 'origin_mode'], varargs=None, keywords=None, defaults=(None, None, 'tanh', 'sigmoid', False)), ('document', '33974b9bfa69f2f1eb85e6f956dff04e'))
 paddle.fluid.layers.linear_chain_crf (ArgSpec(args=['input', 'label', 'param_attr', 'length'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'b28bdb43160e9667be2a3457d19d9f5b'))
 paddle.fluid.layers.crf_decoding (ArgSpec(args=['input', 'param_attr', 'label', 'length'], varargs=None, keywords=None, defaults=(None, None)), ('document', '933b7e268c4ffa3d5c3ef953a5ee9f0b'))
-paddle.fluid.layers.cos_sim (ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None), ('document', '07bb25484c98d529fbe67338422724af'))
-paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100)), ('document', '789a141e97fd0b37241f630935936d08'))
+paddle.fluid.layers.cos_sim (ArgSpec(args=['X', 'Y'], varargs=None, keywords=None, defaults=None), ('document', '48ec1ba2d75c4e2faf8d9a47350462ae'))
+paddle.fluid.layers.cross_entropy (ArgSpec(args=['input', 'label', 'soft_label', 'ignore_index'], varargs=None, keywords=None, defaults=(False, -100)), ('document', 'd1985a930a59c3bd41a7c1d72594f5b9'))
 paddle.fluid.layers.bpr_loss (ArgSpec(args=['input', 'label', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6263dfdeb6c670fa0922c9cbc8fb1bf4'))
 paddle.fluid.layers.square_error_cost (ArgSpec(args=['input', 'label'], varargs=None, keywords=None, defaults=None), ('document', 'bbb9e708bab250359864fefbdf48e9d9'))
 paddle.fluid.layers.chunk_eval (ArgSpec(args=['input', 'label', 'chunk_scheme', 'num_chunk_types', 'excluded_chunk_types', 'seq_length'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'b02844e0ad4bd713c5fe6802aa13219c'))
 paddle.fluid.layers.sequence_conv (ArgSpec(args=['input', 'num_filters', 'filter_size', 'filter_stride', 'padding', 'padding_start', 'bias_attr', 'param_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(3, 1, True, None, None, None, None, None)), ('document', '2bf23e7884c380c3b27f2709aa322cb9'))
-paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None, 'NCHW')), ('document', 'b9be3712a46e196c7329eed52ed91d05'))
-paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None, 'NCDHW')), ('document', 'a7e4573745c40b8b1d726709f209b6e4'))
+paddle.fluid.layers.conv2d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None, 'NCHW')), ('document', 'e91c63b8ac8c35982c0ac518537e44bf'))
+paddle.fluid.layers.conv3d (ArgSpec(args=['input', 'num_filters', 'filter_size', 'stride', 'padding', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(1, 0, 1, None, None, None, True, None, None, 'NCDHW')), ('document', 'feff9c8ebb4d4d0be5345f9042f57c8e'))
 paddle.fluid.layers.sequence_pool (ArgSpec(args=['input', 'pool_type', 'is_test', 'pad_value'], varargs=None, keywords=None, defaults=(False, 0.0)), ('document', 'e90a93251c52dc4e6fb34fb3991b3f82'))
 paddle.fluid.layers.sequence_softmax (ArgSpec(args=['input', 'use_cudnn', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', 'eaa9d0bbd3d4e017c8bc4ecdac483711'))
 paddle.fluid.layers.softmax (ArgSpec(args=['input', 'use_cudnn', 'name', 'axis'], varargs=None, keywords=None, defaults=(False, None, -1)), ('document', '7ccaea1b93fe4f7387a6036692986c6b'))
@@ -149,12 +149,12 @@ paddle.fluid.layers.pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'po
 paddle.fluid.layers.pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'pool_stride', 'pool_padding', 'global_pooling', 'use_cudnn', 'ceil_mode', 'name', 'exclusive', 'data_format'], varargs=None, keywords=None, defaults=(-1, 'max', 1, 0, False, True, False, None, True, 'NCDHW')), ('document', 'db0035a3132b1dfb12e53c57591fb9f6'))
 paddle.fluid.layers.adaptive_pool2d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '52343203de40afe29607397e13aaf0d2'))
 paddle.fluid.layers.adaptive_pool3d (ArgSpec(args=['input', 'pool_size', 'pool_type', 'require_index', 'name'], varargs=None, keywords=None, defaults=('max', False, None)), ('document', '55db6ae7275fb9678a6814aebab81a9c'))
-paddle.fluid.layers.batch_norm (ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu', 'use_global_stats'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, None, None, None, False, False, False)), ('document', 'b88a2a2d5de3e6d845d134782fb54857'))
-paddle.fluid.layers.instance_norm (ArgSpec(args=['input', 'epsilon', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None)), ('document', '5e2d18e85599ede7e71b06ed64d0f69e'))
+paddle.fluid.layers.batch_norm (ArgSpec(args=['input', 'act', 'is_test', 'momentum', 'epsilon', 'param_attr', 'bias_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var', 'fuse_with_relu', 'use_global_stats'], varargs=None, keywords=None, defaults=(None, False, 0.9, 1e-05, None, None, 'NCHW', False, None, None, None, False, False, False)), ('document', '1400433bae7876d0407ae205be39b7a1'))
+paddle.fluid.layers.instance_norm (ArgSpec(args=['input', 'epsilon', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None)), ('document', '23d6fba8ad8495f67a66d8878be5b0be'))
 paddle.fluid.layers.data_norm (ArgSpec(args=['input', 'act', 'epsilon', 'param_attr', 'data_layout', 'in_place', 'name', 'moving_mean_name', 'moving_variance_name', 'do_model_average_for_mean_and_var'], varargs=None, keywords=None, defaults=(None, 1e-05, None, 'NCHW', False, None, None, None, False)), ('document', '2460b30fb87037555208fa8ac6fc1787'))
 paddle.fluid.layers.beam_search_decode (ArgSpec(args=['ids', 'scores', 'beam_size', 'end_id', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '83e08f21af41ac8bac37aeab1f86fdd0'))
-paddle.fluid.layers.conv2d_transpose (ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None, 'NCHW')), ('document', '0ca6c549ac2b63096bdc7832a08b4431'))
-paddle.fluid.layers.conv3d_transpose (ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None, 'NCDHW')), ('document', '709d7ca3a94f52a253d15b06aafb1bd0'))
+paddle.fluid.layers.conv2d_transpose (ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None, 'NCHW')), ('document', 'ed24c2d0f82cd9a3b40488157285a584'))
+paddle.fluid.layers.conv3d_transpose (ArgSpec(args=['input', 'num_filters', 'output_size', 'filter_size', 'padding', 'stride', 'dilation', 'groups', 'param_attr', 'bias_attr', 'use_cudnn', 'act', 'name', 'data_format'], varargs=None, keywords=None, defaults=(None, None, 0, 1, 1, None, None, None, True, None, None, 'NCDHW')), ('document', 'efb1e3bc87339cb26faa2edae210e8b0'))
 paddle.fluid.layers.sequence_expand (ArgSpec(args=['x', 'y', 'ref_level', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '10e122eb755c2bd1f78ef2332b28f1a0'))
 paddle.fluid.layers.sequence_expand_as (ArgSpec(args=['x', 'y', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '858c432e7cbd8bb952cc2eb555457d50'))
 paddle.fluid.layers.sequence_pad (ArgSpec(args=['x', 'pad_value', 'maxlen', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'df08b9c499ab3a90f95d08ab5b6c6c62'))
@@ -170,7 +170,7 @@ paddle.fluid.layers.reduce_any (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'
 paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'f2dfd65b859de9844e7261e7a4503f63'))
 paddle.fluid.layers.sequence_last_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '1af2e3a887e4f914f9d6650406186ab6'))
 paddle.fluid.layers.sequence_slice (ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '39fbc5437be389f6c0c769f82fc1fba2'))
-paddle.fluid.layers.dropout (ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name', 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, 'downgrade_in_infer')), ('document', '4fd396b6cf16bb4ef2a56d695d0ad941'))
+paddle.fluid.layers.dropout (ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name', 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, 'downgrade_in_infer')), ('document', '392dd4bad607fd853f71fec71801044f'))
 paddle.fluid.layers.split (ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '78cf3a7323d1a7697658242e13f63759'))
 paddle.fluid.layers.ctc_greedy_decoder (ArgSpec(args=['input', 'blank', 'input_length', 'padding_value', 'name'], varargs=None, keywords=None, defaults=(None, 0, None)), ('document', '9abb7bb8d267e017620a39a146dc47ea'))
 paddle.fluid.layers.edit_distance (ArgSpec(args=['input', 'label', 'normalized', 'ignored_tokens', 'input_length', 'label_length'], varargs=None, keywords=None, defaults=(True, None, None, None)), ('document', '77cbfb28cd2fc589f589c7013c5086cd'))
@@ -297,7 +297,7 @@ paddle.fluid.layers.prroi_pool (ArgSpec(args=['input', 'rois', 'output_channels'
 paddle.fluid.layers.teacher_student_sigmoid_loss (ArgSpec(args=['input', 'label', 'soft_max_up_bound', 'soft_max_lower_bound'], varargs=None, keywords=None, defaults=(15.0, -15.0)), ('document', '07cb0d95a646dba1b9cc7cdce89e59f0'))
 paddle.fluid.layers.huber_loss (ArgSpec(args=['input', 'label', 'delta'], varargs=None, keywords=None, defaults=None), ('document', '11bb8e62cc9256958eff3991fe4834da'))
 paddle.fluid.layers.kldiv_loss (ArgSpec(args=['x', 'target', 'reduction', 'name'], varargs=None, keywords=None, defaults=('mean', None)), ('document', '18bc95c62d3300456c3c7da5278b47bb'))
-paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', 'a41a93253c937697e900e19af172490d'))
+paddle.fluid.layers.npair_loss (ArgSpec(args=['anchor', 'positive', 'labels', 'l2_reg'], varargs=None, keywords=None, defaults=(0.002,)), ('document', '3828c4bd81c25af0ab955f52d453c587'))
 paddle.fluid.layers.pixel_shuffle (ArgSpec(args=['x', 'upscale_factor'], varargs=None, keywords=None, defaults=None), ('document', '7e5cac851fd9bad344230e1044b6a565'))
 paddle.fluid.layers.fsp_matrix (ArgSpec(args=['x', 'y'], varargs=None, keywords=None, defaults=None), ('document', '20992b20d19c2e5983f366150827b4a6'))
 paddle.fluid.layers.continuous_value_model (ArgSpec(args=['input', 'cvm', 'use_cvm'], varargs=None, keywords=None, defaults=(True,)), ('document', 'c03490ffaa1b78258747157c313db4cd'))
@@ -907,7 +907,7 @@ paddle.fluid.nets.simple_img_conv_pool (ArgSpec(args=['input', 'num_filters', 'f
 paddle.fluid.nets.sequence_conv_pool (ArgSpec(args=['input', 'num_filters', 'filter_size', 'param_attr', 'act', 'pool_type', 'bias_attr'], varargs=None, keywords=None, defaults=(None, 'sigmoid', 'max', None)), ('document', 'd6a1e527b53f5cc15594fee307dfc5cf'))
 paddle.fluid.nets.glu (ArgSpec(args=['input', 'dim'], varargs=None, keywords=None, defaults=(-1,)), ('document', 'b87bacfc70dd3477ed25ef14aa01389a'))
 paddle.fluid.nets.scaled_dot_product_attention (ArgSpec(args=['queries', 'keys', 'values', 'num_heads', 'dropout_rate'], varargs=None, keywords=None, defaults=(1, 0.0)), ('document', 'b1a07a0000eb9103e3a143ca8c13de5b'))
-paddle.fluid.nets.img_conv_group (ArgSpec(args=['input', 'conv_num_filter', 'pool_size', 'conv_padding', 'conv_filter_size', 'conv_act', 'param_attr', 'conv_with_batchnorm', 'conv_batchnorm_drop_rate', 'pool_stride', 'pool_type', 'use_cudnn'], varargs=None, keywords=None, defaults=(1, 3, None, None, False, 0.0, 1, 'max', True)), ('document', '591a48aa9d871896aa8548c977c4c120'))
+paddle.fluid.nets.img_conv_group (ArgSpec(args=['input', 'conv_num_filter', 'pool_size', 'conv_padding', 'conv_filter_size', 'conv_act', 'param_attr', 'conv_with_batchnorm', 'conv_batchnorm_drop_rate', 'pool_stride', 'pool_type', 'use_cudnn'], varargs=None, keywords=None, defaults=(1, 3, None, None, False, 0.0, 1, 'max', True)), ('document', '6033b78da39b8b0ed302fbb0f67da502'))
 paddle.fluid.optimizer.SGDOptimizer ('paddle.fluid.optimizer.SGDOptimizer', ('document', 'c3c8dd3193d991adf8bda505560371d6'))
 paddle.fluid.optimizer.SGDOptimizer.__init__ (ArgSpec(args=['self', 'learning_rate', 'regularization', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.optimizer.SGDOptimizer.apply_gradients (ArgSpec(args=['self', 'params_grads'], varargs=None, keywords=None, defaults=None), ('document', '80ea99c9af7ef5fac7e57fb302103610'))
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index c36931083ad234dcc8e6ac0b61fc211d42260d70..58178d8b72f6f8dc3c19f332308ab0c2e63ad53a 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -1607,8 +1607,8 @@ def cos_sim(X, Y):
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name='x', shape=[3, 7], dtype='float32', append_batch_size=False)
-            y = fluid.layers.data(name='y', shape=[1, 7], dtype='float32', append_batch_size=False)
+            x = fluid.data(name='x', shape=[3, 7], dtype='float32')
+            y = fluid.data(name='y', shape=[1, 7], dtype='float32')
             out = fluid.layers.cos_sim(x, y)
     """
     helper = LayerHelper('cos_sim', **locals())
@@ -1678,7 +1678,7 @@ def dropout(x,
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
+            x = fluid.data(name="data", shape=[None, 32, 32], dtype="float32")
             droped = fluid.layers.dropout(x, dropout_prob=0.5)
     """
 
@@ -1764,8 +1764,8 @@ def cross_entropy(input, label, soft_label=False, ignore_index=kIgnoreIndex):
 
             import paddle.fluid as fluid
             class_num = 7
-            x = fluid.layers.data(name='x', shape=[3, 10], dtype='float32')
-            label = fluid.layers.data(name='label', shape=[1], dtype='int64')
+            x = fluid.data(name='x', shape=[None, 3, 10], dtype='float32')
+            label = fluid.data(name='label', shape=[None, 1], dtype='int64')
             predict = fluid.layers.fc(input=x, size=class_num, act='softmax')
             cost = fluid.layers.cross_entropy(input=predict, label=label)
     """
@@ -2432,7 +2432,7 @@ def conv2d(input,
         .. code-block:: python
 
           import paddle.fluid as fluid
-          data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32')
+          data = fluid.data(name='data', shape=[None, 3, 32, 32], dtype='float32')
           conv2d = fluid.layers.conv2d(input=data, num_filters=2, filter_size=3, act="relu")
     """
 
@@ -2692,7 +2692,7 @@ def conv3d(input,
         .. code-block:: python
 
           import paddle.fluid as fluid
-          data = fluid.layers.data(name='data', shape=[3, 12, 32, 32], dtype='float32')
+          data = fluid.data(name='data', shape=[None, 3, 12, 32, 32], dtype='float32')
           conv3d = fluid.layers.conv3d(input=data, num_filters=2, filter_size=3, act="relu")
     """
 
@@ -3790,7 +3790,7 @@ def batch_norm(input,
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name='x', shape=[3, 7, 3, 7], dtype='float32', append_batch_size=False)
+            x = fluid.data(name='x', shape=[3, 7, 3, 7], dtype='float32')
             hidden1 = fluid.layers.fc(input=x, size=200, param_attr='fc1.w')
             hidden2 = fluid.layers.batch_norm(input=hidden1)
     """
@@ -3956,7 +3956,7 @@ def instance_norm(input,
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name='x', shape=[3, 7, 3, 7], dtype='float32', append_batch_size=False)
+            x = fluid.data(name='x', shape=[3, 7, 3, 7], dtype='float32')
             hidden1 = fluid.layers.fc(input=x, size=200, param_attr='fc1.w')
             hidden2 = fluid.layers.instance_norm(input=hidden1)
     """
@@ -4580,7 +4580,7 @@ def conv2d_transpose(input,
        .. code-block:: python
 
           import paddle.fluid as fluid
-          data = fluid.layers.data(name='data', shape=[3, 32, 32], dtype='float32')
+          data = fluid.data(name='data', shape=[None, 3, 32, 32], dtype='float32')
           conv2d_transpose = fluid.layers.conv2d_transpose(input=data, num_filters=2, filter_size=3)
     """
     assert param_attr is not False, "param_attr should not be False in conv2d_transpose."
@@ -4852,7 +4852,7 @@ def conv3d_transpose(input,
        .. code-block:: python
 
           import paddle.fluid as fluid
-          data = fluid.layers.data(name='data', shape=[3, 12, 32, 32], dtype='float32')
+          data = fluid.data(name='data', shape=[None, 3, 12, 32, 32], dtype='float32')
           conv3d_transpose = fluid.layers.conv3d_transpose(input=data, num_filters=2, filter_size=3)
     """
     assert param_attr is not False, "param_attr should not be False in conv3d_transpose."
@@ -14560,12 +14560,12 @@ def npair_loss(anchor, positive, labels, l2_reg=0.002):
     .. code-block:: python
 
        import paddle.fluid as fluid
-       anchor = fluid.layers.data(
-                     name = 'anchor', shape = [18, 6], dtype = 'float32', append_batch_size=False)
-       positive = fluid.layers.data(
-                     name = 'positive', shape = [18, 6], dtype = 'float32', append_batch_size=False)
-       labels = fluid.layers.data(
-                     name = 'labels', shape = [18], dtype = 'float32', append_batch_size=False)
+       anchor = fluid.data(
+                     name = 'anchor', shape = [18, 6], dtype = 'float32')
+       positive = fluid.data(
+                     name = 'positive', shape = [18, 6], dtype = 'float32')
+       labels = fluid.data(
+                     name = 'labels', shape = [18], dtype = 'float32')
 
        npair_loss = fluid.layers.npair_loss(anchor, positive, labels, l2_reg = 0.002)
   '''
diff --git a/python/paddle/fluid/nets.py b/python/paddle/fluid/nets.py
index 14bf9e874043e92e02741dba892993d0748dcba7..cb61f6dfd53103055ae4dff9472d0867af8357c3 100644
--- a/python/paddle/fluid/nets.py
+++ b/python/paddle/fluid/nets.py
@@ -191,7 +191,7 @@ def img_conv_group(input,
         .. code-block:: python
 
             import paddle.fluid as fluid
-            img = fluid.layers.data(name='img', shape=[1, 28, 28], dtype='float32')
+            img = fluid.data(name='img', shape=[None, 1, 28, 28], dtype='float32')
             conv_pool = fluid.nets.img_conv_group(input=img,
                                                   conv_padding=1,
                                                   conv_num_filter=[3, 3],