Unset ReserveSpace of batch_norm for inference program.

paddle/fluid/framework/op_desc.cc

@@ -447,6 +447,11 @@ void OpDesc::SetOutput(const std::string &param_name,
   this->outputs_[param_name] = args;
 }
 
+void OpDesc::RemoveOutput(const std::string &name) {
+  outputs_.erase(name);
+  need_update_ = true;
+}
+
 bool OpDesc::HasProtoAttr(const std::string &name) const {
   auto &op_info = OpInfoMap::Instance();
   if (op_info.Has(desc_.type())) {

paddle/fluid/framework/op_desc.h

@@ -65,6 +65,7 @@ class OpDesc {
 
   void SetOutput(const std::string &param_name,
                  const std::vector<std::string> &args);
+  void RemoveOutput(const std::string &name);
 
   bool HasAttr(const std::string &name) const {
     return attrs_.find(name) != attrs_.end();

paddle/fluid/pybind/protobuf.cc

@@ -235,6 +235,7 @@ void BindOpDesc(pybind11::module *m) {
               const std::vector<std::string> &vec_var_name) {
              self.SetOutput(name, vec_var_name);
            })
+      .def("remove_output", &pd::OpDesc::RemoveOutput)
       .def("input_arg_names", &pd::OpDesc::InputArgumentNames)
       .def("output_arg_names", &pd::OpDesc::OutputArgumentNames)
       .def("_rename_input", &pd::OpDesc::RenameInput)

python/paddle/fluid/dygraph/io.py

@@ -413,6 +413,23 @@ def _append_backward_desc(self, infer_program_desc):
         # Therefore, in order to reuse the method of backward.py, build the program here.
         program = _build_program_by_desc(program_desc_copy)
 
+        # 3. Add the outputs which is only used for training and not saved in
+        # inference program.
+        for block_idx in six.moves.range(program.num_blocks):
+            block = program.block(block_idx)
+            for op in block.ops:
+                if op.type == "batch_norm":
+                    if "ReserveSpace" not in op.output_names or len(
+                            op.output("ReserveSpace")) == 0:
+                        reserve_space = block.create_var(
+                            name=unique_name.generate_with_ignorable_key(
+                                ".".join(["reserve_space", 'tmp'])),
+                            dtype=block.var(op.input("X")[0]).dtype,
+                            type=core.VarDesc.VarType.LOD_TENSOR,
+                            persistable=False,
+                            stop_gradient=True)
+                        op.desc.set_output("ReserveSpace", [reserve_space.name])
+
         targets = []
         for out in self._output_descs:
             targets.append(program.global_block().var(out.name()))

python/paddle/fluid/framework.py

@@ -5020,6 +5020,9 @@ def _inference_optimize(self, prune_read_op=True):
                 op = block.op(j)
                 if op.has_attr('is_test'):
                     op._set_attr('is_test', True)
+                if op.type() == "batch_norm":
+                    # Remove the output ReserveSpace of batch_norm if exists.
+                    op.remove_output("ReserveSpace")
         res.blocks = [
             Block(res, i) for i in six.moves.range(res.desc.num_blocks())
         ]