diff --git a/paddle/pybind/protobuf.cc b/paddle/pybind/protobuf.cc
index d05eb946448e52ae65fc691304b544f4a55f71fe..21b91b3825d366af85b33b6ae834272bf591a1fe 100644
--- a/paddle/pybind/protobuf.cc
+++ b/paddle/pybind/protobuf.cc
@@ -157,7 +157,10 @@ void BindBlockDesc(py::module &m) {
       .def_property_readonly("parent", &BlockDescBind::Parent)
       .def("append_op", &BlockDescBind::AppendOp,
            py::return_value_policy::reference)
-      .def("append_allocated_op", &BlockDescBind::AppendAllocatedOp)
+      .def("append_allocated_op",
+           [](BlockDescBind &self, OpDescBind *op_desc) {
+             self.AppendAllocatedOp(std::unique_ptr<OpDescBind>(op_desc));
+           })
       .def("prepend_op", &BlockDescBind::PrependOp,
            py::return_value_policy::reference)
       .def("var",
diff --git a/python/paddle/v2/fluid/backward.py b/python/paddle/v2/fluid/backward.py
index 5eb77949482a9c0fc8fec0c5c1ecfccff7eb09cb..0600223732cb80361b264080ba5e92d02ed01189 100644
--- a/python/paddle/v2/fluid/backward.py
+++ b/python/paddle/v2/fluid/backward.py
@@ -1,6 +1,7 @@
 from paddle.v2.fluid import framework as framework
 from . import core
 import collections
+import pdb
 
 __all__ = ['append_backward_ops']
 
@@ -15,7 +16,8 @@ def rename_arg(op_desc_list, old_name, new_name, begin_idx=None, end_idx=None):
         op_desc_list[i].rename_output(old_name, new_name)
 
 
-def backward_impl(block,
+def backward_impl(target,
+                  block,
                   target_block,
                   no_grad_set,
                   grad_info_map,
@@ -29,8 +31,8 @@ def backward_impl(block,
             sub_block_idx = each_op.block_attr("sub_block")
             sub_block = program.block(sub_block_idx)
             grad_sub_block = program.create_block(parent_idx=sub_block_idx)
-            backward_impl(sub_block, grad_sub_block, no_grad_set, grad_info_map,
-                          callback)
+            backward_impl(target, sub_block, grad_sub_block, no_grad_set,
+                          grad_info_map, callback)
             grad_sub_block_list.append(grad_sub_block)
         grad_op_desc = core.get_grad_op_desc(each_op.desc,
                                              no_grad_set[block.idx],
@@ -46,6 +48,7 @@ def backward_impl(block,
     for pos, op_desc in enumerate(grad_op_descs):
         for var_name in op_desc.input_arg_names():
             if len(var_inputs[var_name]) > 1:
+                pdb.set_trace()
                 pending_sum_ops.append((core.OpDesc(
                     type="sum_op",
                     inputs=var_inputs[var_name],
@@ -55,7 +58,7 @@ def backward_impl(block,
         for var_name in op_desc.output_arg_names():
             if len(var_inputs[var_name]) == 0:
                 # it's the first time we get the variable
-                var_inputs[var_name] = var_name
+                var_inputs[var_name] = [var_name]
             else:
                 if len(var_inputs[var_name] == 1):
                     new_name = var_name + "@RENAME@" + \
@@ -73,8 +76,9 @@ def backward_impl(block,
                 var_inputs[var_name].append(new_name)
     for var_name, inputs in var_inputs.iteritems():
         if len(inputs) > 1:
-            pending_sum_ops.append((core.OpDesc(
-                type="sum_op", inputs=inputs, outputs=var_name, attrs={}),
+            pdb.set_trace()
+            pending_sum_ops.append((core.OpDesc("sum_op", {"X": inputs},
+                                                {"Out": var_name}, {}),
                                     len(grad_op_descs)))
     # TODO: remove op in no grad set
 
@@ -84,6 +88,7 @@ def backward_impl(block,
     # create new gradient variables in the target block desc
     for op_desc in grad_op_descs:
         for grad_var_name in op_desc.output_arg_names():
+            grad_var_name = grad_var_name.encode("ascii")
             if target_block.desc.has_var(
                     grad_var_name) or grad_var_name == core.get_empty_var_name(
                     ):
@@ -93,6 +98,16 @@ def backward_impl(block,
                 continue
             grad_info_map[grad_to_var[grad_var_name]] = (grad_var_name,
                                                          target_block)
+    if target_block.idx == 0:
+        grad_target_name = (target.name + "@GRAD")
+        target_block.desc.var(grad_target_name)
+        grad_op_descs.insert(
+            0,
+            core.OpDesc(u"fill_constant", {}, {
+                u"Out": [unicode(grad_target_name, "ascii")]
+            }, {u"shape": (1),
+                u"value": 1.0,
+                u"dtype": core.DataType.FP32}))
     # insert backward operators to target_block
     for op_desc in grad_op_descs:
         target_block.desc.append_allocated_op(op_desc)
@@ -118,18 +133,22 @@ def append_backward_ops(loss, parameter_list=None, no_grad_set=None):
     assert isinstance(loss, framework.Variable)
 
     if no_grad_set is None:
+        no_grad_set = dict()
         program = loss.block.program
         assert isinstance(program, framework.Program)
-        no_grad_set = list()
         for block in program.blocks:
             assert isinstance(block, framework.Block)
+            block_no_grad_set = set()
             for var in block.vars.itervalues():
                 assert isinstance(var, framework.Variable)
                 if var.stop_gradient:
-                    no_grad_set.append(var.name)
-        no_grad_set = set(no_grad_set)
+                    block_no_grad_set.add(var.name)
+            no_grad_set[block.idx] = block_no_grad_set
 
-    param_grad_map = loss.block.program.append_backward(loss, no_grad_set)
+    grad_info_map = dict()
+    root_block = loss.block.program.block(0)
+    backward_impl(loss, root_block, root_block, no_grad_set, grad_info_map)
+    pdb.set_trace()
     if parameter_list is not None:
         parameters = parameter_list
     else:
@@ -137,9 +156,9 @@ def append_backward_ops(loss, parameter_list=None, no_grad_set=None):
         parameters = [param.name for param in params]
     params_and_grads = []
     for param in parameters:
-        if param not in param_grad_map:
+        if param not in grad_info_map:
             raise ValueError("param %s is not in map" % param)
-        grad_info = param_grad_map[param]
+        grad_info = grad_info_map[param]
         grad_block = loss.block.program.block(grad_info[1])
         if not grad_block.has_var(grad_info[0]):
             raise ValueError("grad block[{0}] did not have grad var {1}".format(