diff --git a/deepmd/dpmodel/fitting/dipole_fitting.py b/deepmd/dpmodel/fitting/dipole_fitting.py
index b29c6de3df..20e732823b 100644
--- a/deepmd/dpmodel/fitting/dipole_fitting.py
+++ b/deepmd/dpmodel/fitting/dipole_fitting.py
@@ -108,10 +108,8 @@ def __init__(
         c_differentiable: bool = True,
         type_map: Optional[List[str]] = None,
         old_impl=False,
-        # not used
         seed: Optional[Union[int, List[int]]] = None,
     ):
-        # seed, uniform_seed are not included
         if tot_ener_zero:
             raise NotImplementedError("tot_ener_zero is not implemented")
         if spin is not None:
@@ -143,6 +141,7 @@ def __init__(
             mixed_types=mixed_types,
             exclude_types=exclude_types,
             type_map=type_map,
+            seed=seed,
         )
         self.old_impl = False
 
diff --git a/deepmd/dpmodel/fitting/dos_fitting.py b/deepmd/dpmodel/fitting/dos_fitting.py
index 5a5eb8840a..0d4cee68e2 100644
--- a/deepmd/dpmodel/fitting/dos_fitting.py
+++ b/deepmd/dpmodel/fitting/dos_fitting.py
@@ -45,7 +45,6 @@ def __init__(
         mixed_types: bool = False,
         exclude_types: List[int] = [],
         type_map: Optional[List[str]] = None,
-        # not used
         seed: Optional[Union[int, List[int]]] = None,
     ):
         if bias_dos is not None:
@@ -69,6 +68,7 @@ def __init__(
             mixed_types=mixed_types,
             exclude_types=exclude_types,
             type_map=type_map,
+            seed=seed,
         )
 
     @classmethod
diff --git a/deepmd/dpmodel/fitting/ener_fitting.py b/deepmd/dpmodel/fitting/ener_fitting.py
index 9e639c1de2..60f23f9628 100644
--- a/deepmd/dpmodel/fitting/ener_fitting.py
+++ b/deepmd/dpmodel/fitting/ener_fitting.py
@@ -46,7 +46,6 @@ def __init__(
         mixed_types: bool = False,
         exclude_types: List[int] = [],
         type_map: Optional[List[str]] = None,
-        # not used
         seed: Optional[Union[int, List[int]]] = None,
     ):
         super().__init__(
@@ -70,6 +69,7 @@ def __init__(
             mixed_types=mixed_types,
             exclude_types=exclude_types,
             type_map=type_map,
+            seed=seed,
         )
 
     @classmethod
diff --git a/deepmd/dpmodel/fitting/invar_fitting.py b/deepmd/dpmodel/fitting/invar_fitting.py
index fa5e3f0802..2e469eefe1 100644
--- a/deepmd/dpmodel/fitting/invar_fitting.py
+++ b/deepmd/dpmodel/fitting/invar_fitting.py
@@ -5,6 +5,7 @@
     Dict,
     List,
     Optional,
+    Union,
 )
 
 import numpy as np
@@ -134,8 +135,8 @@ def __init__(
         mixed_types: bool = True,
         exclude_types: List[int] = [],
         type_map: Optional[List[str]] = None,
+        seed: Optional[Union[int, List[int]]] = None,
     ):
-        # seed, uniform_seed are not included
         if tot_ener_zero:
             raise NotImplementedError("tot_ener_zero is not implemented")
         if spin is not None:
@@ -172,6 +173,7 @@ def __init__(
             if atom_ener is None or len([x for x in atom_ener if x is not None]) == 0
             else [x is not None for x in atom_ener],
             type_map=type_map,
+            seed=seed,
         )
 
     def serialize(self) -> dict:
diff --git a/deepmd/dpmodel/fitting/polarizability_fitting.py b/deepmd/dpmodel/fitting/polarizability_fitting.py
index dd85a00392..9f046af6cc 100644
--- a/deepmd/dpmodel/fitting/polarizability_fitting.py
+++ b/deepmd/dpmodel/fitting/polarizability_fitting.py
@@ -114,10 +114,8 @@ def __init__(
         scale: Optional[List[float]] = None,
         shift_diag: bool = True,
         type_map: Optional[List[str]] = None,
-        # not used
         seed: Optional[Union[int, List[int]]] = None,
     ):
-        # seed, uniform_seed are not included
         if tot_ener_zero:
             raise NotImplementedError("tot_ener_zero is not implemented")
         if spin is not None:
@@ -167,6 +165,7 @@ def __init__(
             mixed_types=mixed_types,
             exclude_types=exclude_types,
             type_map=type_map,
+            seed=seed,
         )
         self.old_impl = False