diff --git a/source/api_cc/include/commonPD.h b/source/api_cc/include/commonPD.h
deleted file mode 100644
index 952902225b..0000000000
--- a/source/api_cc/include/commonPD.h
+++ /dev/null
@@ -1,138 +0,0 @@
-// SPDX-License-Identifier: LGPL-3.0-or-later
-#include <string>
-#include <vector>
-
-#include "paddle/include/paddle_inference_api.h"
-
-namespace deepmd {
-/**
- * @brief Check TensorFlow status. Exit if not OK.
- * @param[in] status TensorFlow status.
- **/
-// void check_status(const tensorflow::Status& status);
-
-/**
- * @brief Get the value of a tensor.
- * @param[in] session TensorFlow session.
- * @param[in] name The name of the tensor.
- * @param[in] scope The scope of the tensor.
- * @return The value of the tensor.
- **/
-template <typename VT>
-VT predictor_get_scalar(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                        const std::string& name_);
-
-/**
- * @brief Get the vector of a tensor.
- * @param[out] o_vec The output vector.
- * @param[in] session TensorFlow session.
- * @param[in] name The name of the tensor.
- * @param[in] scope The scope of the tensor.
- **/
-// template <typename VT>
-// void session_get_vector(std::vector<VT>& o_vec,
-//                         tensorflow::Session* session,
-//                         const std::string name_,
-//                         const std::string scope = "");
-
-/**
- * @brief Get the type of a tensor.
- * @param[in] session TensorFlow session.
- * @param[in] name The name of the tensor.
- * @param[in] scope The scope of the tensor.
- * @return The type of the tensor as int.
- **/
-paddle_infer::DataType predictor_get_dtype(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                        const std::string& name_);
-
-/**
- * @brief Get input tensors.
- * @param[out] input_tensors Input tensors.
- * @param[in] dcoord_ Coordinates of atoms.
- * @param[in] ntypes Number of atom types.
- * @param[in] datype_ Atom types.
- * @param[in] dbox Box matrix.
- * @param[in] cell_size Cell size.
- * @param[in] fparam_ Frame parameters.
- * @param[in] aparam_ Atom parameters.
- * @param[in] atommap Atom map.
- * @param[in] scope The scope of the tensors.
- * @param[in] aparam_nall Whether the atomic dimesion of atomic parameters is
- * nall.
- */
-template <typename MODELTYPE, typename VALUETYPE>
-int predictor_input_tensors(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    const double& cell_size,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall = false);
-
-/**
- * @brief Get input tensors.
- * @param[out] input_tensors Input tensors.
- * @param[in] dcoord_ Coordinates of atoms.
- * @param[in] ntypes Number of atom types.
- * @param[in] datype_ Atom types.
- * @param[in] dlist Neighbor list.
- * @param[in] fparam_ Frame parameters.
- * @param[in] aparam_ Atom parameters.
- * @param[in] atommap Atom map.
- * @param[in] nghost Number of ghost atoms.
- * @param[in] ago Update the internal neighbour list if ago is 0.
- * @param[in] scope The scope of the tensors.
- * @param[in] aparam_nall Whether the atomic dimesion of atomic parameters is
- * nall.
- */
-template <typename MODELTYPE, typename VALUETYPE>
-int predictor_input_tensors(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    InputNlist& dlist,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall = false);
-
-/**
- * @brief Get input tensors for mixed type.
- * @param[out] input_tensors Input tensors.
- * @param[in] nframes Number of frames.
- * @param[in] dcoord_ Coordinates of atoms.
- * @param[in] ntypes Number of atom types.
- * @param[in] datype_ Atom types.
- * @param[in] dlist Neighbor list.
- * @param[in] fparam_ Frame parameters.
- * @param[in] aparam_ Atom parameters.
- * @param[in] atommap Atom map.
- * @param[in] nghost Number of ghost atoms.
- * @param[in] ago Update the internal neighbour list if ago is 0.
- * @param[in] scope The scope of the tensors.
- * @param[in] aparam_nall Whether the atomic dimesion of atomic parameters is
- * nall.
- */
-template <typename MODELTYPE, typename VALUETYPE>
-int predictor_input_tensors_mixed_type(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    const double& cell_size,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall = false);
-
-}  // namespace deepmd
diff --git a/source/api_cc/src/DeepPotPD.cc b/source/api_cc/src/DeepPotPD.cc
index ed6a423811..63b436980c 100644
--- a/source/api_cc/src/DeepPotPD.cc
+++ b/source/api_cc/src/DeepPotPD.cc
@@ -39,8 +39,11 @@ void DeepPotPD::init(const std::string& model,
               << std::endl;
     return;
   }
+  // NOTE: There is no custom operators need to be loaded now.
   // deepmd::load_op_library();
-  int gpu_num = 1; // Only support 1 GPU now.
+
+  // NOTE: Only support 1 GPU now.
+  int gpu_num = 1;
   if (gpu_num > 0) {
     gpu_id = gpu_rank % gpu_num;
   } else {
@@ -74,14 +77,13 @@ void DeepPotPD::init(const std::string& model,
     config->DisableGpu();
     std::cout << "load model from: " << model << " to cpu " << std::endl;
   } else {
-    std::cout << "load model from: " << model << " to gpu " << gpu_id
-              << std::endl;
+    std::cout << "load model from: " << model << " to gpu " << gpu_id << std::endl;
   }
 
+  // NOTE: Both set to 1 now.
   // get_env_nthreads(num_intra_nthreads,
   //                  num_inter_nthreads);  // need to be fixed as
   //                                        // DP_INTRA_OP_PARALLELISM_THREADS
-  // both set to 1 now.
   // num_intra_nthreads = 1;
   num_inter_nthreads = 1;
   if (num_inter_nthreads) {
@@ -90,7 +92,6 @@ void DeepPotPD::init(const std::string& model,
 
   predictor = paddle_infer::CreatePredictor(*config);
 
-
   // initialize hyper params from model buffers
   ntypes_spin = 0;
   DeepPotPD::get_buffer<int>("buffer_has_message_passing", do_message_passing);
@@ -172,7 +173,7 @@ void DeepPotPD::compute(ENERGYVTYPE& ener,
     }
     if (do_message_passing == 1 && nghost == 0) {
       throw deepmd::deepmd_exception(
-        "do_message_passing == 1 && nghost == 0"
+        "(do_message_passing == 1 && nghost == 0) is not supported yet."
       );
     }
   }
diff --git a/source/api_cc/src/common.cc b/source/api_cc/src/common.cc
index aef3204569..1fb38fd292 100644
--- a/source/api_cc/src/common.cc
+++ b/source/api_cc/src/common.cc
@@ -34,12 +34,6 @@
 using namespace tensorflow;
 #endif
 
-#ifdef BUILD_PADDLE
-#include "commonPD.h"
-#include "google/protobuf/io/zero_copy_stream_impl.h"
-#include "google/protobuf/text_format.h"
-#endif
-
 static std::vector<std::string> split(const std::string& input_,
                                       const std::string& delimiter) {
   std::string input = input_;
@@ -928,476 +922,6 @@ int deepmd::session_get_dtype(tensorflow::Session* session,
 }
 #endif
 
-#ifdef BUILD_PADDLE
-template <typename MODELTYPE, typename VALUETYPE>
-int deepmd::predictor_input_tensors(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    const double& cell_size,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam__,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall) {
-  // if datype.size is 0, not clear nframes; but 1 is just ok
-  int nframes = datype_.size() > 0 ? (dcoord_.size() / 3 / datype_.size()) : 1;
-  int nall = datype_.size();
-  int nloc = nall;
-  assert(nall * 3 * nframes == dcoord_.size());
-  bool b_pbc = (dbox.size() == nframes * 9);
-
-  std::vector<int> datype = atommap.get_type();
-  std::vector<int> type_count(ntypes, 0);
-  for (unsigned ii = 0; ii < datype.size(); ++ii) {
-    type_count[datype[ii]]++;
-  }
-  datype.insert(datype.end(), datype_.begin() + nloc, datype_.end());
-
-  // 准备输入Tensor句柄
-  auto input_names = predictor->GetInputNames();
-  auto coord_handle = predictor->GetInputHandle(input_names[0]);
-  auto type_handle = predictor->GetInputHandle(input_names[1]);
-  auto natoms_handle = predictor->GetInputHandle(input_names[2]);
-  auto box_handle = predictor->GetInputHandle(input_names[3]);
-  auto mesh_handle = predictor->GetInputHandle(input_names[4]);
-
-  // 设置输入 Tensor 的维度信息
-  std::vector<int> coord_shape = {nframes, nall * 3};
-  std::vector<int> atype_shape = {nframes, nall};
-  std::vector<int> box_shape = {nframes, 9};
-  std::vector<int> mesh_shape;
-  if (b_pbc) {
-    mesh_shape = std::vector<int>({6});
-  } else {
-    mesh_shape = std::vector<int>({0});
-  }
-
-  std::vector<int> natoms_shape = {2 + ntypes};
-
-  coord_handle->Reshape(coord_shape);
-  type_handle->Reshape(atype_shape);
-  natoms_handle->Reshape(natoms_shape);
-  box_handle->Reshape(box_shape);
-  mesh_handle->Reshape(mesh_shape);
-
-  paddle_infer::DataType model_type;
-  if (std::is_same<MODELTYPE, double>::value) {
-    model_type = paddle_infer::DataType::FLOAT64;
-  } else if (std::is_same<MODELTYPE, float>::value) {
-    model_type = paddle_infer::DataType::FLOAT32;
-  } else {
-    throw deepmd::deepmd_exception("unsupported data type");
-  }
-
-  std::vector<VALUETYPE> dcoord(dcoord_);
-  atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall);
-  std::vector<VALUETYPE> aparam_(aparam__);
-  if ((aparam_nall ? nall : nloc) > 0) {
-    atommap.forward<VALUETYPE>(
-        aparam_.begin(), aparam__.begin(),
-        aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-        (aparam_nall ? nall : nloc));
-  }
-
-  // 发送输入数据到Tensor句柄
-  coord_handle->CopyFromCpu(dcoord.data());
-  if (b_pbc) {
-    box_handle->CopyFromCpu(dbox.data());
-  } else {
-    std::vector<VALUETYPE> zero = dbox;
-    std::fill(zero.begin(), zero.end(), 0);
-    box_handle->CopyFromCpu(zero.data());
-  }
-  std::vector<int> datype_rep(nframes * nall, 0);
-  for (int ii = 0; ii < nframes; ++ii) {
-    for (int jj = 0; jj < nall; ++jj) {
-      datype_rep[ii * nall + jj] = datype[jj];
-    }
-  }
-  type_handle->CopyFromCpu(datype_rep.data());
-  std::vector<int> mesh;
-  if (b_pbc) {
-    mesh = std::vector<int>(6);
-    mesh[1 - 1] = 0;
-    mesh[2 - 1] = 0;
-    mesh[3 - 1] = 0;
-    mesh[4 - 1] = 0;
-    mesh[5 - 1] = 0;
-    mesh[6 - 1] = 0;
-  } else {
-    mesh = std::vector<int>(0);
-  }
-  mesh_handle->CopyFromCpu(mesh.data());
-  std::vector<int> natoms = {nloc, nall};
-  for (int ii = 0; ii < ntypes; ++ii) {
-    natoms.push_back(type_count[ii]);
-  }
-  natoms_handle->CopyFromCpu(natoms.data());
-
-  return nloc;
-}
-
-template <typename MODELTYPE, typename VALUETYPE>
-int deepmd::predictor_input_tensors(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    InputNlist& dlist,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam__,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall) {
-  // if datype.size is 0, not clear nframes; but 1 is just ok
-  int nframes = datype_.size() > 0 ? (dcoord_.size() / 3 / datype_.size()) : 1;
-  int nall = datype_.size();
-  int nloc = nall - nghost;
-  assert(nall * 3 * nframes == dcoord_.size());
-  assert(dbox.size() == nframes * 9);
-
-  std::vector<int> datype = atommap.get_type();
-  // for (int i=0; i<datype.size(); ++i)
-  //   printf("datype[%d] = %d\n", i, datype[i]);
-  std::vector<int> type_count(ntypes, 0);
-  for (unsigned ii = 0; ii < datype.size(); ++ii) {
-    type_count[datype[ii]]++;
-  }
-  datype.insert(datype.end(), datype_.begin() + nloc, datype_.end());
-
-  // 准备输入Tensor句柄
-  auto input_names = predictor->GetInputNames();
-  // for (auto &ss: input_names)
-  // {
-  //   std::cout << "input_name: " << " " << ss << std::endl;
-  // }
-  auto coord_handle = predictor->GetInputHandle(input_names[0]);
-  auto type_handle = predictor->GetInputHandle(input_names[1]);
-  // auto natoms_handle = predictor->GetInputHandle(input_names[2]);
-  auto box_handle = predictor->GetInputHandle(input_names[2]);
-  // auto mesh_handle = predictor->GetInputHandle(input_names[4]);
-
-  // 设置输入 Tensor 的维度信息
-  std::vector<int> coord_shape = {nframes, nall, 3};
-  std::vector<int> coord_shape_flat = {nframes, nall * 3};
-
-  std::vector<int> atype_shape = {nframes, nall};
-  std::vector<int> atype_shape_flat = {nframes, nall};
-
-  std::vector<int> box_shape = {nframes, 3, 3};
-  std::vector<int> box_shape_flat = {nframes * 9};
-  // std::vector<int> mesh_shape = std::vector<int>({16});
-  // std::vector<int> natoms_shape = {2 + ntypes};
-
-  paddle_infer::DataType model_type;
-  if (std::is_same<MODELTYPE, double>::value) {
-    model_type = paddle_infer::DataType::FLOAT64;
-  } else if (std::is_same<MODELTYPE, float>::value) {
-    model_type = paddle_infer::DataType::FLOAT32;
-  } else {
-    throw deepmd::deepmd_exception("unsupported data type");
-  }
-
-  coord_handle->Reshape(coord_shape_flat);
-  box_handle->Reshape(box_shape_flat);
-  type_handle->Reshape(atype_shape_flat);
-  // printf("coord.shape = [");
-  // for (auto &d: coord_shape)
-  // {
-  //   printf("%d, ", d);
-  // }
-  // printf("]\n");
-
-  // printf("type.shape = [");
-  // for (auto &d: atype_shape)
-  // {
-  //   printf("%d, ", d);
-  // }
-  // printf("]\n");
-
-  // printf("box.shape = [");
-  // for (auto &d: box_shape)
-  // {
-  //   printf("%d, ", d);
-  // }
-  // printf("]\n");
-  // mesh_handle->Reshape(mesh_shape);
-  // natoms_handle->Reshape(natoms_shape);
-
-  std::vector<VALUETYPE> dcoord(dcoord_);
-  atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall); //012
-  std::vector<VALUETYPE> aparam_(aparam__);
-  if ((aparam_nall ? nall : nloc) > 0) {
-    atommap.forward<VALUETYPE>(
-        aparam_.begin(), aparam__.begin(),
-        aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-        (aparam_nall ? nall : nloc));
-  }
-
-  // const std::string filename = "/workspace/hesensen/deepmd_backend/deepmd_paddle_new/examples/water/lmp/coord_torch.log";
-  // std::ifstream inputFile(filename);
-  // VALUETYPE number;
-  // int iii = 0;
-  // while (inputFile >> number) {
-  //     dcoord[iii] = number;
-  //     ++iii;
-  // }
-  // printf("dcoord finished, iii = %d\n", iii);
-  // inputFile.close();
-
-  // 发送输入数据到Tensor句柄
-  coord_handle->CopyFromCpu(dcoord.data());
-  coord_handle->Reshape(coord_shape);
-  box_handle->CopyFromCpu(dbox.data());
-  box_handle->Reshape(box_shape);
-  // for (int i = 0; i < dcoord.size(); ++i)
-  // {
-  //   printf("dcoord[%d] = %.6lf\n", i, dcoord[i]);
-  // }
-  std::vector<int> datype_rep(nframes * nall, 0);
-  for (int ii = 0; ii < nframes; ++ii) {
-    for (int jj = 0; jj < nall; ++jj) {
-      datype_rep[ii * nall + jj] = datype[jj];
-    }
-  }
-  // const std::string filename1 = "/workspace/hesensen/deepmd_backend/deepmd_paddle_new/examples/water/lmp/type_torch.log";
-  // std::ifstream inputFile1(filename1);
-  // int number_int;
-  // iii = 0;
-  // while (inputFile1 >> number_int) {
-  //     datype_rep[iii] = number_int;
-  //     ++iii;
-  // }
-  // printf("atype finishied, iii = %d\n", iii);
-  // inputFile1.close();
-
-  type_handle->CopyFromCpu(datype_rep.data());
-  // for (int i = 0; i < datype_rep.size(); ++i)
-  // {
-  //   printf("%d\n", datype_rep[i]);
-  // }
-  type_handle->Reshape(atype_shape);
-  // std::vector<int> mesh(mesh_shape[0], 0);
-  // for (int ii = 0; ii < 16; ++ii) {
-  //   mesh[ii] = 0;
-  // }
-  // const int stride = sizeof(int*) / sizeof(int);
-  // assert(stride * sizeof(int) == sizeof(int*));
-  // assert(stride <= 4);
-  // mesh[0] = ago;
-  // mesh[1] = dlist.inum;
-  // mesh[2] = 0;
-  // mesh[3] = 0;
-  // memcpy(&mesh[4], &(dlist.ilist), sizeof(int*));
-  // memcpy(&mesh[8], &(dlist.numneigh), sizeof(int*));
-  // memcpy(&mesh[12], &(dlist.firstneigh), sizeof(int**));
-  // mesh_handle->CopyFromCpu(mesh.data());
-
-  // std::vector<int> natoms = {nloc, nall};
-  // for (int ii = 0; ii < ntypes; ++ii) {
-  //   natoms.push_back(type_count[ii]);
-  // }
-  // natoms_handle->CopyFromCpu(natoms.data());
-  // printf("finished predictor_input_tensors\n");
-  // printf("nloc = %d\n", nloc);
-  return nloc;
-}
-
-template <typename MODELTYPE, typename VALUETYPE>
-int deepmd::predictor_input_tensors_mixed_type(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<VALUETYPE>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<VALUETYPE>& dbox,
-    const double& cell_size,
-    const std::vector<VALUETYPE>& fparam_,
-    const std::vector<VALUETYPE>& aparam__,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall) {
-  int nall = datype_.size() / nframes;
-  int nloc = nall;
-  assert(nall * 3 * nframes == dcoord_.size());
-  bool b_pbc = (dbox.size() == nframes * 9);
-
-  std::vector<int> datype(datype_);
-  atommap.forward<int>(datype.begin(), datype_.begin(), 1, nframes, nall);
-
-  auto input_names = predictor->GetInputNames();
-  auto coord_handle = predictor->GetInputHandle(input_names[0]);
-  auto type_handle = predictor->GetInputHandle(input_names[1]);
-  auto box_handle = predictor->GetInputHandle(input_names[3]);
-  auto mesh_handle = predictor->GetInputHandle(input_names[4]);
-  auto natoms_handle = predictor->GetInputHandle(input_names[2]);
-
-  // 设置输入 Tensor 的维度信息
-  std::vector<int> coord_shape = {nframes, nall * 3};
-  std::vector<int> atype_shape = {nframes, nall};
-  std::vector<int> box_shape = {nframes, 9};
-  std::vector<int> mesh_shape;
-  if (b_pbc) {
-    mesh_shape = std::vector<int>({7});
-  } else {
-    mesh_shape = std::vector<int>({1});
-  }
-  std::vector<int> natoms_shape = {2 + ntypes};
-
-  coord_handle->Reshape(coord_shape);
-  type_handle->Reshape(atype_shape);
-  box_handle->Reshape(box_shape);
-  mesh_handle->Reshape(mesh_shape);
-  natoms_handle->Reshape(natoms_shape);
-
-  paddle_infer::DataType model_type;
-  if (std::is_same<MODELTYPE, double>::value) {
-    model_type = paddle_infer::DataType::FLOAT64;
-  } else if (std::is_same<MODELTYPE, float>::value) {
-    model_type = paddle_infer::DataType::FLOAT32;
-  } else {
-    throw deepmd::deepmd_exception("unsupported data type");
-  }
-
-  std::vector<VALUETYPE> dcoord(dcoord_);
-  atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall);
-  std::vector<VALUETYPE> aparam_(aparam__);
-  if ((aparam_nall ? nall : nloc) > 0) {
-    atommap.forward<VALUETYPE>(
-        aparam_.begin(), aparam__.begin(),
-        aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-        (aparam_nall ? nall : nloc));
-  }
-  // coord
-  coord_handle->CopyFromCpu(dcoord.data());
-
-  // box
-  if (b_pbc) {
-    box_handle->CopyFromCpu(dbox.data());
-  } else {
-    std::vector<VALUETYPE> zero = dbox;
-    std::fill(zero.begin(), zero.end(), 0);
-    box_handle->CopyFromCpu(zero.data());
-  }
-
-  // datype
-  std::vector<int> datype_rep(nframes * nall, 0);
-  for (int ii = 0; ii < nframes; ++ii) {
-    for (int jj = 0; jj < nall; ++jj) {
-      datype_rep[ii * nall + jj] = datype[jj];
-    }
-  }
-  type_handle->CopyFromCpu(datype_rep.data());
-  // mesh
-  std::vector<int> mesh;
-  if (b_pbc) {
-    mesh = std::vector<int>(7, 0);
-    mesh[1 - 1] = 0;
-    mesh[2 - 1] = 0;
-    mesh[3 - 1] = 0;
-    mesh[4 - 1] = 0;
-    mesh[5 - 1] = 0;
-    mesh[6 - 1] = 0;
-    mesh[7 - 1] = 0;
-  } else {
-    mesh = std::vector<int>(1, 0);
-    mesh[1 - 1] = 0;
-  }
-  mesh_handle->CopyFromCpu(mesh.data());
-  //natoms
-  std::vector<int> natoms_pad = {nloc, nall, nall};
-  if (ntypes > 1) {
-    for (int ii = 0; ii < ntypes; ++ii) {
-      natoms_pad.push_back(0);
-    }
-  }
-  natoms_handle->CopyFromCpu(natoms_pad.data());
-
-  // if (fparam_.size() > 0) {
-  //   input_tensors.push_back({prefix + "t_fparam", fparam_tensor});
-  // }
-  // if (aparam_.size() > 0) {
-  //   input_tensors.push_back({prefix + "t_aparam", aparam_tensor});
-  // }
-  return nloc;
-}
-
-#endif
-
-#ifdef BUILD_PADDLE
-template <typename VT>
-VT deepmd::predictor_get_scalar(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::string& name_) {
-  if (std::is_same<VT, std::string>::value) {
-    /*
-    NOTE: Convert from ascii code(int64) to std::string,
-    A workaround for string data type is not supported in Paddle yet.
-    */
-    auto scalar_tensor = predictor->GetOutputHandle(name_);
-    if (scalar_tensor->shape().size() == 0) {
-      return VT();
-    }
-    const auto& shape = scalar_tensor->shape();
-    const int& str_len = std::accumulate(std::begin(shape), std::end(shape), 1,
-                                         std::multiplies<>{});
-    if (str_len == 0) {
-      return VT();
-    }
-    int32_t* scalar_ptr = (int32_t*)malloc(str_len * sizeof(int32_t));
-    scalar_tensor->CopyToCpu(scalar_ptr);
-    VT ret;
-    for (int ii = 0; ii < str_len; ++ii) {
-      ret += (char)scalar_ptr[ii];
-    }
-    free(scalar_ptr);
-    return ret;
-  } else {
-    /* Vanillia process for other data type below*/
-    auto scalar_tensor = predictor->GetOutputHandle(name_);
-    // VT* scalar_ptr = (VT*)malloc(1 * sizeof(VT));
-    std::unique_ptr<VT> scalar_ptr(new VT);
-    scalar_tensor->CopyToCpu(scalar_ptr.get());
-    return (*scalar_ptr);
-  }
-}
-
-
-// template <typename VT>
-// void deepmd::session_get_vector(std::vector<VT>& o_vec,
-//                                 Session* session,
-//                                 const std::string name_,
-//                                 const std::string scope) {
-//   std::string name = name_;
-//   if (scope != "") {
-//     name = scope + "/" + name;
-//   }
-//   std::vector<Tensor> output_tensors;
-//   deepmd::check_status(
-//       session->Run(std::vector<std::pair<std::string, Tensor>>({}),
-//                    {name.c_str()}, {}, &output_tensors));
-//   Tensor output_rc = output_tensors[0];
-//   assert(1 == output_rc.shape().dims());
-//   int dof = output_rc.shape().dim_size(0);
-//   o_vec.resize(dof);
-//   auto orc = output_rc.flat<VT>();
-//   for (int ii = 0; ii < dof; ++ii) {
-//     o_vec[ii] = orc(ii);
-//   }
-// }
-
-paddle_infer::DataType deepmd::predictor_get_dtype(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::string& name_) {
-  auto scalar_tensor = predictor->GetOutputHandle(name_);
-  return scalar_tensor->type();
-}
-
-#endif
-
 template <typename VT>
 void deepmd::select_map(std::vector<VT>& out,
                         const std::vector<VT>& in,
@@ -1502,19 +1026,6 @@ template void deepmd::session_get_vector<int>(std::vector<int>&,
                                               const std::string);
 #endif
 
-#ifdef BUILD_PADDLE
-template int deepmd::predictor_get_scalar<int>(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                                             const std::string &name_);
-
-template bool deepmd::predictor_get_scalar<bool>(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                                               const std::string &name_);
-
-// template void deepmd::session_get_vector<int>(std::vector<int>&,
-//                                               Session*,
-//                                               const std::string,
-//                                               const std::string);
-#endif
-
 template void deepmd::select_map<int>(std::vector<int>& out,
                                       const std::vector<int>& in,
                                       const std::vector<int>& idx_map,
@@ -1554,12 +1065,6 @@ template void deepmd::session_get_vector<float>(std::vector<float>&,
                                                 const std::string);
 #endif
 
-#ifdef BUILD_PADDLE
-template float deepmd::predictor_get_scalar<float>(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                                                 const std::string &name_);
-
-#endif
-
 template void deepmd::select_map<float>(std::vector<float>& out,
                                         const std::vector<float>& in,
                                         const std::vector<int>& idx_map,
@@ -1599,11 +1104,6 @@ template void deepmd::session_get_vector<double>(std::vector<double>&,
                                                  const std::string);
 #endif
 
-#ifdef BUILD_PADDLE
-template double deepmd::predictor_get_scalar<double>(const std::shared_ptr<paddle_infer::Predictor>& predictor,
-                                                 const std::string& name_);
-#endif
-
 template void deepmd::select_map<double>(std::vector<double>& out,
                                          const std::vector<double>& in,
                                          const std::vector<int>& idx_map,
@@ -1673,46 +1173,6 @@ template void deepmd::select_map_inv<deepmd::STRINGTYPE>(
     const int& stride);
 #endif
 
-#ifdef BUILD_PADDLE
-template std::string deepmd::predictor_get_scalar<std::string>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor, const std::string &name_);
-
-// template void deepmd::session_get_vector<std::string>(
-//     std::vector<std::string>&,
-//     const std::shared_ptr<paddle_infer::Predictor>& predictor,
-//     const std::string);
-
-template void deepmd::select_map<std::string>(
-    std::vector<std::string>& out,
-    const std::vector<std::string>& in,
-    const std::vector<int>& idx_map,
-    const int& stride,
-    const int& nframes,
-    const int& nall1,
-    const int& nall2);
-
-template void deepmd::select_map<std::string>(
-    typename std::vector<std::string>::iterator out,
-    const typename std::vector<std::string>::const_iterator in,
-    const std::vector<int>& idx_map,
-    const int& stride,
-    const int& nframes,
-    const int& nall1,
-    const int& nall2);
-
-template void deepmd::select_map_inv<std::string>(
-    std::vector<std::string>& out,
-    const std::vector<std::string>& in,
-    const std::vector<int>& idx_map,
-    const int& stride);
-
-template void deepmd::select_map_inv<std::string>(
-    typename std::vector<std::string>::iterator out,
-    const typename std::vector<std::string>::const_iterator in,
-    const std::vector<int>& idx_map,
-    const int& stride);
-#endif
-
 void deepmd::read_file_to_string(std::string model, std::string& file_content) {
   // generated by GitHub Copilot
   std::ifstream file(model);
@@ -1907,158 +1367,6 @@ template int deepmd::session_input_tensors_mixed_type<float, float>(
     const bool aparam_nall);
 #endif
 
-#ifdef BUILD_PADDLE
-template int deepmd::predictor_input_tensors<double, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    const double& cell_size,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors<float, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    const double& cell_size,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-
-template int deepmd::predictor_input_tensors<double, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    const double& cell_size,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors<float, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    const double& cell_size,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-
-template int deepmd::predictor_input_tensors<double, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    InputNlist& dlist,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors<float, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    InputNlist& dlist,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall);
-
-template int deepmd::predictor_input_tensors<double, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    InputNlist& dlist,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors<float, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    InputNlist& dlist,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const int nghost,
-    const int ago,
-    const bool aparam_nall);
-
-template int deepmd::predictor_input_tensors_mixed_type<double, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    const double& cell_size,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors_mixed_type<float, double>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<double>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<double>& dbox,
-    const double& cell_size,
-    const std::vector<double>& fparam_,
-    const std::vector<double>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-
-template int deepmd::predictor_input_tensors_mixed_type<double, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    const double& cell_size,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-template int deepmd::predictor_input_tensors_mixed_type<float, float>(
-    const std::shared_ptr<paddle_infer::Predictor>& predictor,
-    const int& nframes,
-    const std::vector<float>& dcoord_,
-    const int& ntypes,
-    const std::vector<int>& datype_,
-    const std::vector<float>& dbox,
-    const double& cell_size,
-    const std::vector<float>& fparam_,
-    const std::vector<float>& aparam_,
-    const deepmd::AtomMap& atommap,
-    const bool aparam_nall);
-#endif
-
 void deepmd::print_summary(const std::string& pre) {
   int num_intra_nthreads, num_inter_nthreads;
   deepmd::get_env_nthreads(num_intra_nthreads, num_inter_nthreads);