diff --git a/x2paddle/decoder/caffe_decoder.py b/x2paddle/decoder/caffe_decoder.py
index b0f23befeafcbb4967f838dc9621449abd1b71f8..2135ee59a1c3f0a5b3c4a45464c7a4763fa46c64 100644
--- a/x2paddle/decoder/caffe_decoder.py
+++ b/x2paddle/decoder/caffe_decoder.py
@@ -99,6 +99,23 @@ class CaffeGraph(Graph):
                 print('The filter layer:' + layer.name)
         return filtered_layers
 
+    def generate_input_layer(self, dims, index):
+        dim_str = ''
+        for dim in dims:
+            dim_str += 'dim: {}\n'.format(str(dim))
+        input_str = 'layer {\n'
+        input_str += 'name: \"{}\"\n '.format(str(self.model.input[index]))
+        input_str += 'type: "Input"\n'
+        input_str += 'top: \"{}\"\n'.format(str(self.model.input[index]))
+        input_str += 'input_param {\n'
+        input_str += 'shape {\n'
+        input_str += dim_str
+        input_str += '}}}'
+        input_str = str.encode(input_str)
+        net = self.caffe_pb.NetParameter()
+        text_format.Merge(input_str, net)
+        return net.layers or net.layer
+
     def input2layers(self, input_layers=[]):
         inputs_num = len(self.model.input)
         if inputs_num != 0:
@@ -109,44 +126,12 @@ class CaffeGraph(Graph):
                                 (input_dims_num))
                 for i in range(inputs_num):
                     dims = self.model.input_dim[i * 4:(i + 1) * 4]
-                    dim_str = ''
-                    for dim in dims:
-                        dim_str += 'dim: {}\n'.format(str(dim))
-                    input_str = 'layer {\n'
-                    input_str += 'name: \"{}\"\n '.format(
-                        str(self.model.input[i]))
-                    input_str += 'type: "Input"\n'
-                    input_str += 'top: \"{}\"\n'.format(str(
-                        self.model.input[i]))
-                    input_str += 'input_param {\n'
-                    input_str += 'shape {\n'
-                    input_str += dim_str
-                    input_str += '}}}'
-                    input_str = str.encode(input_str)
-                    net = self.caffe_pb.NetParameter()
-                    text_format.Merge(input_str, net)
-                    l = net.layers or net.layer
+                    l = self.generate_input_layer(dims, i)
                     input_layers.append(l[0])
             else:
                 for i in range(inputs_num):
                     dims = self.model.input_shape[i].dim[0:4]
-                    dim_str = ''
-                    for dim in dims:
-                        dim_str += 'dim: {}\n'.format(str(dim))
-                    input_str = 'layer {\n'
-                    input_str += 'name: \"{}\"\n '.format(
-                        str(self.model.input[i]))
-                    input_str += 'type: "Input"\n'
-                    input_str += 'top: \"{}\"\n'.format(str(
-                        self.model.input[i]))
-                    input_str += 'input_param {\n'
-                    input_str += 'shape {\n'
-                    input_str += dim_str
-                    input_str += '}}}'
-                    input_str = str.encode(input_str)
-                    net = self.caffe_pb.NetParameter()
-                    text_format.Merge(input_str, net)
-                    l = net.layers or net.layer
+                    l = self.generate_input_layer(dims, i)
                     input_layers.append(l[0])
 
     def transform_input_layers(self, layers, input_layers=[]):
@@ -157,21 +142,7 @@ class CaffeGraph(Graph):
                     raise Error('invalid input_dim[%d] param in prototxt' %
                                 (input_dims_num))
                 dims = self.model.input_dim[0:4]
-                dim_str = ''
-                for dim in dims:
-                    dim_str += 'dim: {}\n'.format(str(dim))
-                input_str = 'layer {\n'
-                input_str += 'name: \"{}\"\n '.format(str(self.model.input[i]))
-                input_str += 'type: "Input"\n'
-                input_str += 'top: \"{}\"\n'.format(str(self.model.input[i]))
-                input_str += 'input_param {\n'
-                input_str += 'shape {\n'
-                input_str += dim_str
-                input_str += '}}}'
-                input_str = str.encode(input_str)
-                net = self.caffe_pb.NetParameter()
-                text_format.Merge(input_str, net)
-                l = net.layers or net.layer
+                l = self.generate_input_layer(dims, i)
                 input_layers.append(l[0])
 
     def get_layer_type(self, layer):