diff --git a/deepmd/infer/deep_pot.py b/deepmd/infer/deep_pot.py
index b863a7ddc2..546c0f3c7e 100644
--- a/deepmd/infer/deep_pot.py
+++ b/deepmd/infer/deep_pot.py
@@ -56,7 +56,7 @@ def __new__(cls, model_file: str, *args, **kwargs):
 
                 return super().__new__(DeepPotTF)
             elif backend == DPBackend.PyTorch:
-                from deepmd_pt.infer.deep_eval import DeepPot as DeepPotPT
+                from deepmd.pt.infer.deep_eval import DeepPot as DeepPotPT
 
                 return super().__new__(DeepPotPT)
             else:
diff --git a/deepmd/pt/utils/ase_calc.py b/deepmd/pt/utils/ase_calc.py
index 8d5fe8bce9..6bcb9cdc5e 100644
--- a/deepmd/pt/utils/ase_calc.py
+++ b/deepmd/pt/utils/ase_calc.py
@@ -1,65 +1,6 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
-from typing import (
-    ClassVar,
-)
+from deepmd.calculator import DP as DPCalculator
 
-import dpdata
-import numpy as np
-from ase import (
-    Atoms,
-)
-from ase.calculators.calculator import (
-    Calculator,
-    PropertyNotImplementedError,
-)
-
-from deepmd.pt.infer.deep_eval import (
-    DeepPot,
-)
-
-
-class DPCalculator(Calculator):
-    implemented_properties: ClassVar[list] = [
-        "energy",
-        "free_energy",
-        "forces",
-        "virial",
-        "stress",
-    ]
-
-    def __init__(self, model):
-        Calculator.__init__(self)
-        self.dp = DeepPot(model)
-        self.type_map = self.dp.type_map
-
-    def calculate(self, atoms: Atoms, properties, system_changes) -> None:
-        Calculator.calculate(self, atoms, properties, system_changes)
-        system = dpdata.System(atoms, fmt="ase/structure")
-        type_trans = np.array(
-            [self.type_map.index(i) for i in system.data["atom_names"]]
-        )
-        input_coords = system.data["coords"]
-        input_cells = system.data["cells"]
-        input_types = list(type_trans[system.data["atom_types"]])
-        model_predict = self.dp.eval(input_coords, input_cells, input_types)
-        self.results = {
-            "energy": model_predict[0].item(),
-            "free_energy": model_predict[0].item(),
-            "forces": model_predict[1].reshape(-1, 3),
-            "virial": model_predict[2].reshape(3, 3),
-        }
-
-        # convert virial into stress for lattice relaxation
-        if "stress" in properties:
-            if sum(atoms.get_pbc()) > 0 or (atoms.cell is not None):
-                # the usual convention (tensile stress is positive)
-                # stress = -virial / volume
-                stress = (
-                    -0.5
-                    * (self.results["virial"].copy() + self.results["virial"].copy().T)
-                    / atoms.get_volume()
-                )
-                # Voigt notation
-                self.results["stress"] = stress.flat[[0, 4, 8, 5, 2, 1]]
-            else:
-                raise PropertyNotImplementedError
+__all__ = [
+    "DPCalculator",
+]
diff --git a/source/tests/pt/test_calculator.py b/source/tests/pt/test_calculator.py
index e8382b22b8..a35538250b 100644
--- a/source/tests/pt/test_calculator.py
+++ b/source/tests/pt/test_calculator.py
@@ -66,6 +66,7 @@ def test_calculator(self):
             # positions=[tuple(item) for item in coordinate],
             cell=cell,
             calculator=self.calculator,
+            pbc=True,
         )
         e0, f0 = ase_atoms0.get_potential_energy(), ase_atoms0.get_forces()
         s0, v0 = (
@@ -79,6 +80,7 @@ def test_calculator(self):
             # positions=[tuple(item) for item in coordinate],
             cell=cell,
             calculator=self.calculator,
+            pbc=True,
         )
         e1, f1 = ase_atoms1.get_potential_energy(), ase_atoms1.get_forces()
         s1, v1 = (