fix bug

x2paddle/op_mapper/paddle_op_mapper.py

@@ -556,14 +556,6 @@ class PaddleOpMapper(object):
                 'SizeTensor' in input_names and
                 len(op.input('SizeTensor')) > 0):
             node_list = list()
-            empty_name = self.get_name(op.type, 'empty')
-            empty_tensor = helper.make_tensor(
-                empty_name,
-                onnx_pb.TensorProto.FLOAT, (0, ),
-                np.array([]).astype('float32'),
-                raw=False)
-            empty_node = helper.make_node(
-                'Constant', [], outputs=[empty_name], value=empty_tensor)
             shape_name0 = self.get_name(op.type, 'shape')
             shape_node0 = helper.make_node(
                 'Shape', inputs=op.input('X'), outputs=[shape_name0])
@@ -578,8 +570,7 @@ class PaddleOpMapper(object):
                 'Slice',
                 inputs=[shape_name0, starts_name, ends_name],
                 outputs=[shape_name1])
-            node_list.extend(
-                [empty_node, shape_node0, starts_node, ends_node, shape_node1])
+            node_list.extend([shape_node0, starts_node, ends_node, shape_node1])
             if 'OutSize' in input_names and len(op.input('OutSize')) > 0:
                 cast_shape_name = self.get_name(op.type, "shape.cast")
                 cast_shape_node = helper.make_node(
@@ -617,7 +608,7 @@ class PaddleOpMapper(object):
                 outputs=[name_h_w],
                 value=helper.make_tensor(
                     name=name_h_w,
-                    data_type=onnx_pb.TensorProto.FLOAT,
+                    data_type=onnx_pb.TensorProto.INT64,
                     dims=[2],
                     vals=[height, width],
                     raw=False))
@@ -629,10 +620,24 @@ class PaddleOpMapper(object):
                 outputs=[shape_name4],
                 axis=0)
             node_list.append(shape_node4)
+            cast_shape_name3 = self.get_name(op.type, "shape.cast")
+            cast_shape_node3 = helper.make_node(
+                'Cast',
+                inputs=[shape_name3],
+                outputs=[cast_shape_name3],
+                to=onnx_pb.TensorProto.FLOAT)
+            node_list.append(cast_shape_node3)
+            cast_shape_name4 = self.get_name(op.type, "shape.cast")
+            cast_shape_node4 = helper.make_node(
+                'Cast',
+                inputs=[shape_name4],
+                outputs=[cast_shape_name4],
+                to=onnx_pb.TensorProto.FLOAT)
+            node_list.append(cast_shape_node4)
             outputs_h_w_scales = op.output('Out')[0] + "@out_hw_scales"
             node_h_w_scales = helper.make_node(
                 'Div',
-                inputs=[shape_name3, shape_name4],
+                inputs=[cast_shape_name3, cast_shape_name4],
                 outputs=[outputs_h_w_scales])
             node_list.append(node_h_w_scales)
             result_node = helper.make_node(