diff --git a/deepmd/infer/deep_pot.py b/deepmd/infer/deep_pot.py
index 031c5de1bc..fc9a6a76ed 100644
--- a/deepmd/infer/deep_pot.py
+++ b/deepmd/infer/deep_pot.py
@@ -307,7 +307,10 @@ def _get_natoms_and_nframes(
             natoms = len(atom_types[0])
         else:
             natoms = len(atom_types)
-        coords = np.reshape(np.array(coords), [-1, natoms * 3])
+        if natoms == 0:
+            assert coords.size == 0
+        else:
+            coords = np.reshape(np.array(coords), [-1, natoms * 3])
         nframes = coords.shape[0]
         return natoms, nframes
 
@@ -415,7 +418,7 @@ def _prepare_feed_dict(
             atom_types = np.array(atom_types, dtype=int).reshape([-1, natoms])
         else:
             atom_types = np.array(atom_types, dtype=int).reshape([-1])
-        coords = np.reshape(np.array(coords), [-1, natoms * 3])
+        coords = np.reshape(np.array(coords), [nframes, natoms * 3])
         if cells is None:
             pbc = False
             # make cells to work around the requirement of pbc
diff --git a/deepmd/utils/batch_size.py b/deepmd/utils/batch_size.py
index 41d9fd4f64..2b3117d849 100644
--- a/deepmd/utils/batch_size.py
+++ b/deepmd/utils/batch_size.py
@@ -100,10 +100,12 @@ def execute(
         OutOfMemoryError
             OOM when batch size is 1
         """
+        if natoms > 0:
+            batch_nframes = self.current_batch_size // natoms
+        else:
+            batch_nframes = self.current_batch_size
         try:
-            n_batch, result = callable(
-                max(self.current_batch_size // natoms, 1), start_index
-            )
+            n_batch, result = callable(max(batch_nframes, 1), start_index)
         except OutOfMemoryError as e:
             # TODO: it's very slow to catch OOM error; I don't know what TF is doing here
             # but luckily we only need to catch once
diff --git a/source/api_c/include/deepmd.hpp b/source/api_c/include/deepmd.hpp
index 71ff5b3dcc..90c1c1c918 100644
--- a/source/api_c/include/deepmd.hpp
+++ b/source/api_c/include/deepmd.hpp
@@ -618,6 +618,7 @@ class DeepPot {
    * nframes x natoms x dim_aparam.
    * natoms x dim_aparam. Then all frames are assumed to be provided with the
    *same aparam.
+   * @warning Natoms should not be zero when computing multiple frames.
    **/
   template <typename VALUETYPE, typename ENERGYVTYPE>
   void compute(
@@ -630,7 +631,7 @@ class DeepPot {
       const std::vector<VALUETYPE> &fparam = std::vector<VALUETYPE>(),
       const std::vector<VALUETYPE> &aparam = std::vector<VALUETYPE>()) {
     unsigned int natoms = atype.size();
-    unsigned int nframes = coord.size() / natoms / 3;
+    unsigned int nframes = natoms > 0 ? coord.size() / natoms / 3 : 1;
     assert(nframes * natoms * 3 == coord.size());
     if (!box.empty()) {
       assert(box.size() == nframes * 9);
@@ -676,6 +677,7 @@ class DeepPot {
    * nframes x natoms x dim_aparam.
    * natoms x dim_aparam. Then all frames are assumed to be provided with the
    *same aparam.
+   * @warning Natoms should not be zero when computing multiple frames.
    **/
   template <typename VALUETYPE, typename ENERGYVTYPE>
   void compute(
@@ -690,7 +692,7 @@ class DeepPot {
       const std::vector<VALUETYPE> &fparam = std::vector<VALUETYPE>(),
       const std::vector<VALUETYPE> &aparam = std::vector<VALUETYPE>()) {
     unsigned int natoms = atype.size();
-    unsigned int nframes = coord.size() / natoms / 3;
+    unsigned int nframes = natoms > 0 ? coord.size() / natoms / 3 : 1;
     assert(nframes * natoms * 3 == coord.size());
     if (!box.empty()) {
       assert(box.size() == nframes * 9);
@@ -743,6 +745,7 @@ class DeepPot {
    * nframes x natoms x dim_aparam.
    * natoms x dim_aparam. Then all frames are assumed to be provided with the
    *same aparam.
+   * @warning Natoms should not be zero when computing multiple frames.
    **/
   template <typename VALUETYPE, typename ENERGYVTYPE>
   void compute(
@@ -758,7 +761,7 @@ class DeepPot {
       const std::vector<VALUETYPE> &fparam = std::vector<VALUETYPE>(),
       const std::vector<VALUETYPE> &aparam = std::vector<VALUETYPE>()) {
     unsigned int natoms = atype.size();
-    unsigned int nframes = coord.size() / natoms / 3;
+    unsigned int nframes = natoms > 0 ? coord.size() / natoms / 3 : 1;
     assert(nframes * natoms * 3 == coord.size());
     if (!box.empty()) {
       assert(box.size() == nframes * 9);
@@ -810,6 +813,7 @@ class DeepPot {
    * nframes x natoms x dim_aparam.
    * natoms x dim_aparam. Then all frames are assumed to be provided with the
    *same aparam.
+   * @warning Natoms should not be zero when computing multiple frames.
    **/
   template <typename VALUETYPE, typename ENERGYVTYPE>
   void compute(
@@ -827,7 +831,7 @@ class DeepPot {
       const std::vector<VALUETYPE> &fparam = std::vector<VALUETYPE>(),
       const std::vector<VALUETYPE> &aparam = std::vector<VALUETYPE>()) {
     unsigned int natoms = atype.size();
-    unsigned int nframes = coord.size() / natoms / 3;
+    unsigned int nframes = natoms > 0 ? coord.size() / natoms / 3 : 1;
     assert(nframes * natoms * 3 == coord.size());
     if (!box.empty()) {
       assert(box.size() == nframes * 9);
diff --git a/source/api_c/tests/test_deeppot_a_hpp.cc b/source/api_c/tests/test_deeppot_a_hpp.cc
index a423e0acc6..814122d538 100644
--- a/source/api_c/tests/test_deeppot_a_hpp.cc
+++ b/source/api_c/tests/test_deeppot_a_hpp.cc
@@ -478,6 +478,23 @@ TYPED_TEST(TestInferDeepPotAHPP, cpu_lmp_nlist_type_sel) {
   }
 }
 
+TYPED_TEST(TestInferDeepPotAHPP, cpu_build_nlist_empty_input) {
+  using VALUETYPE = TypeParam;
+  std::vector<VALUETYPE> coord;
+  std::vector<int> atype;
+  std::vector<VALUETYPE>& box = this->box;
+  unsigned int natoms = 0;
+  deepmd::hpp::DeepPot& dp = this->dp;
+  double ener;
+  std::vector<VALUETYPE> force, virial;
+
+  dp.compute(ener, force, virial, coord, atype, box);
+  // no errors will be fine
+  EXPECT_EQ(force.size(), natoms * 3);
+  EXPECT_EQ(virial.size(), 9);
+  EXPECT_LT(fabs(ener), EPSILON);
+}
+
 TYPED_TEST(TestInferDeepPotAHPP, print_summary) {
   deepmd::hpp::DeepPot& dp = this->dp;
   dp.print_summary("");
diff --git a/source/api_cc/src/DeepPot.cc b/source/api_cc/src/DeepPot.cc
index 785ed00cb8..23a0a7e663 100644
--- a/source/api_cc/src/DeepPot.cc
+++ b/source/api_cc/src/DeepPot.cc
@@ -574,7 +574,8 @@ void DeepPot::compute(ENERGYVTYPE& dener,
                       const std::vector<VALUETYPE>& fparam_,
                       const std::vector<VALUETYPE>& aparam_) {
   int nall = datype_.size();
-  int nframes = dcoord_.size() / nall / 3;
+  // if nall==0, unclear nframes, but 1 is ok
+  int nframes = nall > 0 ? (dcoord_.size() / nall / 3) : 1;
   int nloc = nall;
   atommap = deepmd::AtomMap(datype_.begin(), datype_.begin() + nloc);
   assert(nloc == atommap.get_type().size());
@@ -658,7 +659,8 @@ void DeepPot::compute(ENERGYVTYPE& dener,
                       const std::vector<VALUETYPE>& fparam_,
                       const std::vector<VALUETYPE>& aparam__) {
   int nall = datype_.size();
-  int nframes = dcoord_.size() / nall / 3;
+  // if nall==0, unclear nframes, but 1 is ok
+  int nframes = nall > 0 ? (dcoord_.size() / nall / 3) : 1;
   std::vector<VALUETYPE> fparam;
   std::vector<VALUETYPE> aparam_;
   validate_fparam_aparam(nframes, (aparam_nall ? nall : (nall - nghost)),
@@ -753,7 +755,8 @@ void DeepPot::compute_inner(ENERGYVTYPE& dener,
                             const std::vector<VALUETYPE>& fparam,
                             const std::vector<VALUETYPE>& aparam) {
   int nall = datype_.size();
-  int nframes = dcoord_.size() / nall / 3;
+  // if nall==0, unclear nframes, but 1 is ok
+  int nframes = nall > 0 ? (dcoord_.size() / nall / 3) : 1;
   int nloc = nall - nghost;
 
   std::vector<std::pair<std::string, Tensor>> input_tensors;
@@ -841,7 +844,8 @@ void DeepPot::compute(ENERGYVTYPE& dener,
                       const std::vector<VALUETYPE>& dbox,
                       const std::vector<VALUETYPE>& fparam_,
                       const std::vector<VALUETYPE>& aparam_) {
-  int nframes = dcoord_.size() / 3 / datype_.size();
+  // if datype.size is 0, not clear nframes; but 1 is just ok
+  int nframes = datype_.size() > 0 ? (dcoord_.size() / 3 / datype_.size()) : 1;
   atommap = deepmd::AtomMap(datype_.begin(), datype_.end());
   int nloc = datype_.size();
   std::vector<VALUETYPE> fparam;
@@ -930,7 +934,8 @@ void DeepPot::compute(ENERGYVTYPE& dener,
                       const std::vector<VALUETYPE>& fparam_,
                       const std::vector<VALUETYPE>& aparam__) {
   int nall = datype_.size();
-  int nframes = dcoord_.size() / 3 / nall;
+  // if nall==0, unclear nframes, but 1 is ok
+  int nframes = nall > 0 ? (dcoord_.size() / nall / 3) : 1;
   int nloc = nall - nghost;
   std::vector<VALUETYPE> fparam;
   std::vector<VALUETYPE> aparam_;
diff --git a/source/api_cc/src/common.cc b/source/api_cc/src/common.cc
index fad7e374ab..5994e9446f 100644
--- a/source/api_cc/src/common.cc
+++ b/source/api_cc/src/common.cc
@@ -380,7 +380,8 @@ int deepmd::session_input_tensors(
     const deepmd::AtomMap& atommap,
     const std::string scope,
     const bool aparam_nall) {
-  int nframes = dcoord_.size() / 3 / datype_.size();
+  // 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());
@@ -445,10 +446,13 @@ int deepmd::session_input_tensors(
   std::vector<VALUETYPE> dcoord(dcoord_);
   atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall);
   std::vector<VALUETYPE> aparam_(aparam__);
-  atommap.forward<VALUETYPE>(
-      aparam_.begin(), aparam__.begin(),
-      aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-      (aparam_nall ? nall : nloc));
+  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));
+  }
+  // if == 0, aparam__.size should also be 0, so no need to forward
 
   for (int ii = 0; ii < nframes; ++ii) {
     for (int jj = 0; jj < nall * 3; ++jj) {
@@ -520,7 +524,8 @@ int deepmd::session_input_tensors(
     const int ago,
     const std::string scope,
     const bool aparam_nall) {
-  int nframes = dcoord_.size() / 3 / datype_.size();
+  // 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());
@@ -581,10 +586,13 @@ int deepmd::session_input_tensors(
   std::vector<VALUETYPE> dcoord(dcoord_);
   atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall);
   std::vector<VALUETYPE> aparam_(aparam__);
-  atommap.forward<VALUETYPE>(
-      aparam_.begin(), aparam__.begin(),
-      aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-      (aparam_nall ? nall : nloc));
+  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));
+  }
+  // if == 0, aparam__.size should also be 0, so no need to forward
 
   for (int ii = 0; ii < nframes; ++ii) {
     for (int jj = 0; jj < nall * 3; ++jj) {
@@ -717,10 +725,13 @@ int deepmd::session_input_tensors_mixed_type(
   std::vector<VALUETYPE> dcoord(dcoord_);
   atommap.forward<VALUETYPE>(dcoord.begin(), dcoord_.begin(), 3, nframes, nall);
   std::vector<VALUETYPE> aparam_(aparam__);
-  atommap.forward<VALUETYPE>(
-      aparam_.begin(), aparam__.begin(),
-      aparam__.size() / nframes / (aparam_nall ? nall : nloc), nframes,
-      (aparam_nall ? nall : nloc));
+  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));
+  }
+  // if == 0, aparam__.size should also be 0, so no need to forward
 
   for (int ii = 0; ii < nframes; ++ii) {
     for (int jj = 0; jj < nall * 3; ++jj) {
diff --git a/source/op/map_aparam.cc b/source/op/map_aparam.cc
index 0dc8a3743e..d0ff08032d 100644
--- a/source/op/map_aparam.cc
+++ b/source/op/map_aparam.cc
@@ -49,8 +49,8 @@ class MapAparamOp : public OpKernel {
     int nframes = aparam_tensor.shape().dim_size(0);
     int nloc = natoms(0);
     int nall = natoms(1);
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
-    int numb_aparam = aparam_tensor.shape().dim_size(1) / nall;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
+    int numb_aparam = nall > 0 ? aparam_tensor.shape().dim_size(1) / nall : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == nlist_tensor.shape().dim_size(0)),
diff --git a/source/op/pairwise.cc b/source/op/pairwise.cc
index d60bc3bccc..8ed140a14a 100644
--- a/source/op/pairwise.cc
+++ b/source/op/pairwise.cc
@@ -85,7 +85,7 @@ class PairwiseIdxOp : public OpKernel {
       nloc_qmmm.push_back(nloc_qmmm_ii);
       nghost_qm.push_back(nghost_qm_ii);
       nghost_qmmm.push_back(nghost_qmmm_ii);
-      nframes_qmmm.push_back(backward_qmmm_map.size() / nall);
+      nframes_qmmm.push_back(nall > 0 ? backward_qmmm_map.size() / nall : 0);
     }
     int max_nloc_qm = 1, max_nloc_qmmm = 1, max_nghost_qm = 0,
         max_nghost_qmmm = 0;
diff --git a/source/op/prod_force.cc b/source/op/prod_force.cc
index a2631b8c1d..d8ced591b9 100644
--- a/source/op/prod_force.cc
+++ b/source/op/prod_force.cc
@@ -58,8 +58,8 @@ class ProdForceOp : public OpKernel {
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
     int nall = natoms(1);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
diff --git a/source/op/prod_force_grad.cc b/source/op/prod_force_grad.cc
index fed8616534..2d14022279 100644
--- a/source/op/prod_force_grad.cc
+++ b/source/op/prod_force_grad.cc
@@ -65,8 +65,8 @@ class ProdForceGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_force_grad_multi_device.cc b/source/op/prod_force_grad_multi_device.cc
index ffcd8f0b8b..bbcef6bd91 100644
--- a/source/op/prod_force_grad_multi_device.cc
+++ b/source/op/prod_force_grad_multi_device.cc
@@ -70,8 +70,8 @@ class ProdForceSeAGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
@@ -180,8 +180,8 @@ class ProdForceSeRGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_force_multi_device.cc b/source/op/prod_force_multi_device.cc
index 935b5b9f2f..3eaf005f9a 100644
--- a/source/op/prod_force_multi_device.cc
+++ b/source/op/prod_force_multi_device.cc
@@ -89,8 +89,8 @@ class ProdForceSeAOp : public OpKernel {
     int nloc = natoms[0];
     int nall = natoms[1];
     int nframes = net_deriv_tensor.shape().dim_size(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
                 errors::InvalidArgument("number of samples should match"));
@@ -187,8 +187,8 @@ class ProdForceSeROp : public OpKernel {
     int nloc = natoms[0];
     int nall = natoms[1];
     int nframes = net_deriv_tensor.shape().dim_size(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
                 errors::InvalidArgument("number of samples should match"));
diff --git a/source/op/prod_force_se_a_grad.cc b/source/op/prod_force_se_a_grad.cc
index 1c859158e0..21dd4fe00a 100644
--- a/source/op/prod_force_se_a_grad.cc
+++ b/source/op/prod_force_se_a_grad.cc
@@ -63,8 +63,8 @@ class ProdForceSeAGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_force_se_a_mask.cc b/source/op/prod_force_se_a_mask.cc
index c2270f4234..32fcf54a79 100644
--- a/source/op/prod_force_se_a_mask.cc
+++ b/source/op/prod_force_se_a_mask.cc
@@ -49,7 +49,7 @@ class ProdForceSeAMaskOp : public OpKernel {
     int nloc = total_atom_num;
     int nall = total_atom_num;
     int ndescrpt = nall * 4;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
diff --git a/source/op/prod_force_se_a_mask_grad.cc b/source/op/prod_force_se_a_mask_grad.cc
index 54eafecc19..6f841b1c7d 100644
--- a/source/op/prod_force_se_a_mask_grad.cc
+++ b/source/op/prod_force_se_a_mask_grad.cc
@@ -55,7 +55,7 @@ class ProdForceSeAMaskGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = total_atom_num;
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
     int nnei = total_atom_num;
 
     // check the sizes
diff --git a/source/op/prod_force_se_r_grad.cc b/source/op/prod_force_se_r_grad.cc
index fbaf667675..f0b4b18323 100644
--- a/source/op/prod_force_se_r_grad.cc
+++ b/source/op/prod_force_se_r_grad.cc
@@ -57,8 +57,8 @@ class ProdForceSeRGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_virial.cc b/source/op/prod_virial.cc
index dfac86b8cf..2719c6c670 100644
--- a/source/op/prod_virial.cc
+++ b/source/op/prod_virial.cc
@@ -63,8 +63,8 @@ class ProdVirialOp : public OpKernel {
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
     int nall = natoms(1);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
diff --git a/source/op/prod_virial_grad.cc b/source/op/prod_virial_grad.cc
index 2c179a2793..b06e273453 100644
--- a/source/op/prod_virial_grad.cc
+++ b/source/op/prod_virial_grad.cc
@@ -70,8 +70,8 @@ class ProdVirialGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_virial_grad_multi_device.cc b/source/op/prod_virial_grad_multi_device.cc
index d3e7025e6e..215c26f184 100644
--- a/source/op/prod_virial_grad_multi_device.cc
+++ b/source/op/prod_virial_grad_multi_device.cc
@@ -76,8 +76,8 @@ class ProdVirialSeAGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
@@ -206,8 +206,8 @@ class ProdVirialSeRGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_virial_multi_device.cc b/source/op/prod_virial_multi_device.cc
index 445770e85a..23b312b797 100644
--- a/source/op/prod_virial_multi_device.cc
+++ b/source/op/prod_virial_multi_device.cc
@@ -70,9 +70,9 @@ class ProdVirialSeAOp : public OpKernel {
     const int* natoms = natoms_tensor.flat<int>().data();
     int nloc = natoms[0];
     int nall = natoms[1];
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
     int nframes = net_deriv_tensor.shape().dim_size(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
                 errors::InvalidArgument("number of samples should match"));
@@ -169,9 +169,9 @@ class ProdVirialSeROp : public OpKernel {
     const int* natoms = natoms_tensor.flat<int>().data();
     int nloc = natoms[0];
     int nall = natoms[1];
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
     int nframes = net_deriv_tensor.shape().dim_size(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
     // check the sizes
     OP_REQUIRES(context, (nframes == in_deriv_tensor.shape().dim_size(0)),
                 errors::InvalidArgument("number of samples should match"));
diff --git a/source/op/prod_virial_se_a_grad.cc b/source/op/prod_virial_se_a_grad.cc
index c914bfddaf..a22401d654 100644
--- a/source/op/prod_virial_se_a_grad.cc
+++ b/source/op/prod_virial_se_a_grad.cc
@@ -68,8 +68,8 @@ class ProdVirialSeAGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/prod_virial_se_r_grad.cc b/source/op/prod_virial_se_r_grad.cc
index 90e6588b99..b874c828df 100644
--- a/source/op/prod_virial_se_r_grad.cc
+++ b/source/op/prod_virial_se_r_grad.cc
@@ -62,8 +62,8 @@ class ProdVirialSeRGradOp : public OpKernel {
 
     int nframes = net_deriv_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int ndescrpt = net_deriv_tensor.shape().dim_size(1) / nloc;
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int ndescrpt = nloc > 0 ? net_deriv_tensor.shape().dim_size(1) / nloc : 0;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/soft_min_force.cc b/source/op/soft_min_force.cc
index 7db6936025..a2970f4c3a 100644
--- a/source/op/soft_min_force.cc
+++ b/source/op/soft_min_force.cc
@@ -54,7 +54,7 @@ class SoftMinForceOp : public OpKernel {
     int nframes = du_tensor.shape().dim_size(0);
     int nloc = natoms(0);
     int nall = natoms(1);
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == sw_deriv_tensor.shape().dim_size(0)),
diff --git a/source/op/soft_min_force_grad.cc b/source/op/soft_min_force_grad.cc
index be53d74e26..752ad4f93d 100644
--- a/source/op/soft_min_force_grad.cc
+++ b/source/op/soft_min_force_grad.cc
@@ -62,7 +62,7 @@ class SoftMinForceGradOp : public OpKernel {
 
     int nframes = du_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/op/soft_min_virial.cc b/source/op/soft_min_virial.cc
index a37940f651..91a94e01c3 100644
--- a/source/op/soft_min_virial.cc
+++ b/source/op/soft_min_virial.cc
@@ -60,7 +60,7 @@ class SoftMinVirialOp : public OpKernel {
     int nframes = du_tensor.shape().dim_size(0);
     int nloc = natoms(0);
     int nall = natoms(1);
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == sw_deriv_tensor.shape().dim_size(0)),
diff --git a/source/op/soft_min_virial_grad.cc b/source/op/soft_min_virial_grad.cc
index ef8f026f23..bc9cb96a63 100644
--- a/source/op/soft_min_virial_grad.cc
+++ b/source/op/soft_min_virial_grad.cc
@@ -67,7 +67,7 @@ class SoftMinVirialGradOp : public OpKernel {
 
     int nframes = du_tensor.shape().dim_size(0);
     int nloc = natoms(0);
-    int nnei = nlist_tensor.shape().dim_size(1) / nloc;
+    int nnei = nloc > 0 ? nlist_tensor.shape().dim_size(1) / nloc : 0;
 
     // check the sizes
     OP_REQUIRES(context, (nframes == grad_shape.dim_size(0)),
diff --git a/source/tests/test_deeppot_a.py b/source/tests/test_deeppot_a.py
index 006b391e49..12f677e618 100644
--- a/source/tests/test_deeppot_a.py
+++ b/source/tests/test_deeppot_a.py
@@ -13,6 +13,7 @@
 from deepmd.env import (
     GLOBAL_NP_FLOAT_PRECISION,
     MODEL_VERSION,
+    tf,
 )
 from deepmd.infer import (
     DeepPot,
@@ -302,6 +303,23 @@ def test_2frame_atm(self):
         expected_sv = np.sum(expected_v.reshape([nframes, -1, 9]), axis=1)
         np.testing.assert_almost_equal(vv.ravel(), expected_sv.ravel(), default_places)
 
+    # TODO: needs to fix
+    @unittest.skipIf(tf.test.is_gpu_available(), reason="Segfault in GPUs")
+    def test_zero_input(self):
+        nframes = 1
+        ee, ff, vv = self.dp.eval(
+            np.zeros([nframes, 0, 3]), self.box, np.zeros([0]), atomic=False
+        )
+        # check shape of the returns
+        natoms = 0
+        self.assertEqual(ee.shape, (nframes, 1))
+        self.assertEqual(ff.shape, (nframes, natoms, 3))
+        self.assertEqual(vv.shape, (nframes, 9))
+        # check values
+        np.testing.assert_almost_equal(ff.ravel(), 0, default_places)
+        np.testing.assert_almost_equal(ee.ravel(), 0, default_places)
+        np.testing.assert_almost_equal(vv.ravel(), 0, default_places)
+
 
 class TestDeepPotANoPBC(unittest.TestCase):
     @classmethod
diff --git a/source/tests/test_deeppot_r.py b/source/tests/test_deeppot_r.py
index c1746efa01..44c6e3c167 100644
--- a/source/tests/test_deeppot_r.py
+++ b/source/tests/test_deeppot_r.py
@@ -9,6 +9,7 @@
 
 from deepmd.env import (
     GLOBAL_NP_FLOAT_PRECISION,
+    tf,
 )
 from deepmd.infer import (
     DeepPot,
@@ -430,6 +431,23 @@ def test_2frame_atm(self):
         expected_sv = np.sum(expected_v.reshape([nframes, -1, 9]), axis=1)
         np.testing.assert_almost_equal(vv.ravel(), expected_sv.ravel(), default_places)
 
+    # TODO: needs to fix
+    @unittest.skipIf(tf.test.is_gpu_available(), reason="Segfault in GPUs")
+    def test_zero_input(self):
+        nframes = 1
+        ee, ff, vv = self.dp.eval(
+            np.zeros([nframes, 0, 3]), self.box, np.zeros([0]), atomic=False
+        )
+        # check shape of the returns
+        natoms = 0
+        self.assertEqual(ee.shape, (nframes, 1))
+        self.assertEqual(ff.shape, (nframes, natoms, 3))
+        self.assertEqual(vv.shape, (nframes, 9))
+        # check values
+        np.testing.assert_almost_equal(ff.ravel(), 0, default_places)
+        np.testing.assert_almost_equal(ee.ravel(), 0, default_places)
+        np.testing.assert_almost_equal(vv.ravel(), 0, default_places)
+
 
 class TestDeepPotRLargeBoxNoPBC(unittest.TestCase):
     @classmethod