try to get numpy array from ModelRes

core/general-client/include/general_model.h

@@ -69,9 +69,15 @@ class ModelRes {
   const std::vector<int64_t>& get_int64_by_name(const std::string& name) {
     return _int64_value_map[name];
   }
+  std::vector<int64_t>&& get_int64_by_name_with_rv(const std::string& name) {
+    return std::move(_int64_value_map[name]);
+  }
   const std::vector<float>& get_float_by_name(const std::string& name) {
     return _float_value_map[name];
   }
+  std::vector<float>&& get_float_by_name_with_rv(const std::string& name) {
+    return std::move(_float_value_map[name]);
+  }
   const std::vector<int>& get_shape(const std::string& name) {
     return _shape_map[name];
   }
@@ -121,10 +127,18 @@ class PredictorRes {
                                                 const std::string& name) {
     return _models[model_idx].get_int64_by_name(name);
   }
+  std::vector<int64_t>&& get_int64_by_name_with_rv(const int model_idx,
+                                                   const std::string& name) {
+    return std::move(_models[model_idx].get_int64_by_name_with_rv(name));
+  }
   const std::vector<float>& get_float_by_name(const int model_idx,
                                               const std::string& name) {
     return _models[model_idx].get_float_by_name(name);
   }
+  std::vector<float>&& get_float_by_name_with_rv(const int model_idx,
+                                                 const std::string& name) {
+    return std::move(_models[model_idx].get_float_by_name_with_rv(name));
+  }
   const std::vector<int>& get_shape(const int model_idx,
                                     const std::string& name) {
     return _models[model_idx].get_shape(name);

core/general-client/src/pybind_general_model.cpp

@@ -32,14 +32,26 @@ PYBIND11_MODULE(serving_client, m) {
       .def(py::init())
       .def("get_int64_by_name",
            [](PredictorRes &self, int model_idx, std::string &name) {
-             return self.get_int64_by_name(model_idx, name);
-           },
-           py::return_value_policy::reference)
+             // https://github.com/pybind/pybind11/issues/1042
+             std::vector<int64_t> *ptr = new std::vector<int64_t>(
+                 std::move(self.get_int64_by_name_with_rv(model_idx, name)));
+             auto capsule = py::capsule(ptr, [](void *p) {
+               delete reinterpret_cast<std::vector<int64_t> *>(p);
+             });
+             return py::array(ptr->size(), ptr->data(), capsule);
+           })
       .def("get_float_by_name",
            [](PredictorRes &self, int model_idx, std::string &name) {
-             return self.get_float_by_name(model_idx, name);
-           },
-           py::return_value_policy::reference)
+             std::vector<float> *ptr = new std::vector<float>(
+                 std::move(self.get_float_by_name_with_rv(model_idx, name)));
+             auto capsule = py::capsule(ptr, [](void *p) {
+               delete reinterpret_cast<std::vector<float> *>(p);
+             });
+             return py::array(ptr->size(), ptr->data(), capsule);
+             // return self.get_float_by_name(model_idx, name);
+           })
+      //,
+      // py::return_value_policy::reference)
       .def("get_shape",
            [](PredictorRes &self, int model_idx, std::string &name) {
              return self.get_shape(model_idx, name);

python/paddle_serving_client/__init__.py

@@ -319,7 +319,7 @@ class Client(object):
                 if self.fetch_names_to_type_[name] == int_type:
                     result_map[name] = result_batch.get_int64_by_name(mi, name)
                     shape = result_batch.get_shape(mi, name)
-                    result_map[name] = np.array(result_map[name], dtype='int64')
+                    # result_map[name] = np.array(result_map[name], dtype='int64')
                     result_map[name].shape = shape
                     if name in self.lod_tensor_set:
                         result_map["{}.lod".format(name)] = np.array(
@@ -327,8 +327,8 @@ class Client(object):
                 elif self.fetch_names_to_type_[name] == float_type:
                     result_map[name] = result_batch.get_float_by_name(mi, name)
                     shape = result_batch.get_shape(mi, name)
-                    result_map[name] = np.array(
-                        result_map[name], dtype='float32')
+                    # result_map[name] = np.array(
+                    # result_map[name], dtype='float32')
                     result_map[name].shape = shape
                     if name in self.lod_tensor_set:
                         result_map["{}.lod".format(name)] = np.array(