update sampling layers (#901)

Author: zsdonghao

tensorlayer/layers/image_resampling.py

@@ -59,19 +59,31 @@ def __init__(
 
         if not isinstance(size, (list, tuple)) and len(size) == 2:
             raise AssertionError()
-
         if len(self.inputs.get_shape()) == 3:
             if is_scale:
-                size_h = size[0] * tf.shape(self.inputs)[0]
-                size_w = size[1] * tf.shape(self.inputs)[1]
+                input_shape = self.inputs.shape.as_list()
+                if input_shape[0] is not None:
+                    size_h = size[0] * input_shape[0]
+                else:
+                    size_h = size[0] * tf.shape(self.inputs)[0]
+                if input_shape[1] is not None:
+                    size_w = size[1] * input_shape[1]
+                else:
+                    size_w = size[1] * tf.shape(self.inputs)[1]
                 size = [size_h, size_w]
 
         elif len(self.inputs.get_shape()) == 4:
             if is_scale:
-                size_h = size[0] * tf.shape(self.inputs)[1]
-                size_w = size[1] * tf.shape(self.inputs)[2]
+                input_shape = self.inputs.shape.as_list()
+                if input_shape[1] is not None:
+                    size_h = size[0] * input_shape[1]
+                else:
+                    size_h = size[0] * tf.shape(self.inputs)[1]
+                if input_shape[2] is not None:
+                    size_w = size[1] * input_shape[2]
+                else:
+                    size_w = size[1] * tf.shape(self.inputs)[2]
                 size = [size_h, size_w]
-
         else:
             raise Exception("Donot support shape %s" % tf.shape(self.inputs))
 
@@ -135,14 +147,28 @@ def __init__(
 
         if len(self.inputs.get_shape()) == 3:
             if is_scale:
-                size_h = size[0] * tf.shape(self.inputs)[0]
-                size_w = size[1] * tf.shape(self.inputs)[1]
+                input_shape = self.inputs.shape.as_list()
+                if input_shape[0] is not None:
+                    size_h = size[0] * input_shape[0]
+                else:
+                    size_h = size[0] * tf.shape(self.inputs)[0]
+                if input_shape[1] is not None:
+                    size_w = size[1] * input_shape[1]
+                else:
+                    size_w = size[1] * tf.shape(self.inputs)[1]
                 size = [size_h, size_w]
 
         elif len(self.inputs.get_shape()) == 4:
             if is_scale:
-                size_h = size[0] * tf.shape(self.inputs)[1]
-                size_w = size[1] * tf.shape(self.inputs)[2]
+                input_shape = self.inputs.shape.as_list()
+                if input_shape[1] is not None:
+                    size_h = size[0] * input_shape[1]
+                else:
+                    size_h = size[0] * tf.shape(self.inputs)[1]
+                if input_shape[2] is not None:
+                    size_w = size[1] * input_shape[2]
+                else:
+                    size_w = size[1] * tf.shape(self.inputs)[2]
                 size = [size_h, size_w]
 
         else: