diff --git a/python/paddle/v2/fluid/layers.py b/python/paddle/v2/fluid/layers.py
index 99d0ac4a1bb9436a7eb27fb90687a593accc94af..7c1514efadb13ac136057c1785931719879aa42b 100644
--- a/python/paddle/v2/fluid/layers.py
+++ b/python/paddle/v2/fluid/layers.py
@@ -1537,6 +1537,7 @@ def conv2d_transpose(input,
                      filter_size=None,
                      padding=None,
                      stride=None,
+                     dilation=None,
                      param_attr=None,
                      main_program=None,
                      startup_program=None):
@@ -1562,6 +1563,9 @@ def conv2d_transpose(input,
         stride(int|tuple): The stride size. If stride is a tuple, it must
             contain two integers, (stride_H, stride_W). Otherwise, the
             stride_H = stride_W = stride.
+        dilation(int|tuple): The dilation size. If dilation is a tuple, it must
+            contain two integers, (dilation_H, dilation_W). Otherwise, the
+            dilation_H = dilation_W = dilation.
         param_attr: Parameter Attribute.
         main_program(Program): the main program
         startup_program(Program): the startup program
@@ -1586,6 +1590,11 @@ def conv2d_transpose(input,
     elif stride is not None:
         op_attr['strides'] = stride
 
+    if isinstance(dilation, int):
+        op_attr['dilations'] = dilation
+    elif stride is not None:
+        op_attr['dilations'] = dilation
+
     if filter_size is None:
         if output_size is None:
             raise ValueError("output_size must be set when filter_size is None")
@@ -1594,11 +1603,14 @@ def conv2d_transpose(input,
 
         padding = op_attr.get('paddings', [0, 0])
         stride = op_attr.get('strides', [1, 1])
+        dilation = op_attr.get('dilations', [1, 1])
 
         h_in = input.shape[2]
         w_in = input.shape[3]
-        filter_size_h = output_size[0] - (h_in - 1) * stride[0] + 2 * padding[0]
-        filter_size_w = output_size[1] - (w_in - 1) * stride[1] + 2 * padding[1]
+        filter_size_h = (output_size[0] - (h_in - 1) * stride[0] + 2 *
+                         padding[0] - 1) / dilation[0] + 1
+        filter_size_w = (output_size[1] - (w_in - 1) * stride[1] + 2 *
+                         padding[1] - 1) / dilation[1] + 1
         filter_size = [filter_size_h, filter_size_w]
     elif isinstance(filter_size, int):
         filter_size = [filter_size, filter_size]