diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py
index 267393d611d6fad1a77a6c1e0a45be4be1e34731..5b173694dd0e4a52c0179f12f5edd74e2c41cb8c 100644
--- a/python/paddle/trainer/config_parser.py
+++ b/python/paddle/trainer/config_parser.py
@@ -2400,6 +2400,14 @@ class CropLayer(LayerBase):
         image_conf.img_size_y = input_layer.height
         image_conf.channels = input_layer.size / (input_layer.width *
                                                   input_layer.height)
+        # only support for 4-dims inputs and NCHW order
+        if (len(self.config.inputs) == 2):
+            self.set_layer_height_width(
+                self.get_input_layer(1).height, self.get_input_layer(1).width)
+            self.set_layer_size(self.get_input_layer(1).size)
+        else:
+            self.set_layer_height_width(shape[-2], shape[-1])
+            self.set_layer_size(reduce(lambda x, y: x * y, shape[1:]))
 
 
 @config_layer('batch_norm')
@@ -3849,6 +3857,26 @@ class SwitchOrderLayer(LayerBase):
             name, 'switch_order', 0, inputs=inputs, **xargs)
         self.config.reshape_conf.height_axis.extend(reshape['height'])
         self.config.reshape_conf.width_axis.extend(reshape['width'])
+        input_layer = self.get_input_layer(0)
+        if reshape is None:
+            self.set_layer_size(input_layer.size)
+        else:
+            in_h = input_layer.height
+            in_w = input_layer.width
+            out_dims = None
+            if input_layer.has_depth():
+                in_d = input_layer.depth
+                in_c = input_layer.size / in_h / in_w / in_d
+                # batch_size, depth, height, width, channel
+                out_dims = [0, in_d, in_h, in_w, in_c]
+            else:
+                in_c = input_layer.size / in_h / in_w
+                # batch_size, height, width, channel
+                out_dims = [0, in_h, in_w, in_c]
+            # Because (reshape['width'][0] > 0) always be true.
+            # So out_dims[0] won't be used.
+            size = reduce(lambda x, y: x * y, out_dims[reshape['width'][0]:])
+            self.set_layer_size(size)
 
 
 @config_layer('scale_sub_region')
diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index 6dc380e87dabce4637f77deabf1399bdf201a5c2..f6dc58b9c0ed0b14ad9db098892af14274aed0c1 100644
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -6873,6 +6873,7 @@ def crop_layer(input, offset, axis=2, shape=None, name=None, layer_attr=None):
 
     :param input: The input of this layer. If two inputs are given, the second one
                   will be regarded as the reference.
+                  And the input must be 4-dims and in NCHW order.
     :type input: LayerOutput | Sequence
     :param offset: The crop offset.
     :type offset: Sequence