fix: remove model_def_script from AtomicModel (#3449)

After #3438, `model_def_script` is no more saved in AtomicModel.

---------

Signed-off-by: Jinzhe Zeng <jinzhe.zeng@rutgers.edu>

deepmd/dpmodel/atomic_model/make_base_atomic_model.py

@@ -178,10 +178,6 @@ def do_grad_(self, var_name: str, base: str) -> bool:
                 return self.fitting_output_def()[var_name].c_differentiable
             return self.fitting_output_def()[var_name].r_differentiable
 
-        def get_model_def_script(self) -> str:
-            # TODO: implement this method; saved to model
-            raise NotImplementedError
-
     setattr(BAM, fwd_method_name, BAM.fwd)
     delattr(BAM, "fwd")
 

deepmd/dpmodel/model/base_model.py

@@ -172,3 +172,10 @@ class BaseModel(make_base_model()):
     deepmd.dpmodel.model.base_model.BaseBaseModel
         Backend-independent BaseModel class.
     """
+
+    def __init__(self) -> None:
+        self.model_def_script = ""
+
+    def get_model_def_script(self) -> str:
+        """Get the model definition script."""
+        return self.model_def_script

deepmd/dpmodel/model/make_model.py

@@ -73,6 +73,7 @@ def __init__(
             atomic_model_: Optional[T_AtomicModel] = None,
             **kwargs,
         ):
+            BaseModel.__init__(self)
             if atomic_model_ is not None:
                 self.atomic_model: T_AtomicModel = atomic_model_
             else:
@@ -452,10 +453,6 @@ def get_nnei(self) -> int:
             """Returns the total number of selected neighboring atoms in the cut-off radius."""
             return self.atomic_model.get_nnei()
 
-        def get_model_def_script(self) -> str:
-            """Get the model definition script."""
-            return self.atomic_model.get_model_def_script()
-
         def get_sel(self) -> List[int]:
             """Returns the number of selected atoms for each type."""
             return self.atomic_model.get_sel()

deepmd/pt/model/atomic_model/base_atomic_model.py

@@ -58,9 +58,6 @@ def reinit_pair_exclude(
         else:
             self.pair_excl = PairExcludeMask(self.get_ntypes(), self.pair_exclude_types)
 
-    def get_model_def_script(self) -> str:
-        return self.model_def_script
-
     def atomic_output_def(self) -> FittingOutputDef:
         old_def = self.fitting_output_def()
         if self.atom_excl is None:

deepmd/pt/model/atomic_model/dp_atomic_model.py

@@ -55,7 +55,6 @@ def __init__(
         **kwargs,
     ):
         torch.nn.Module.__init__(self)
-        self.model_def_script = ""
         ntypes = len(type_map)
         self.type_map = type_map
         self.ntypes = ntypes

deepmd/pt/model/atomic_model/linear_atomic_model.py

@@ -360,7 +360,6 @@ def __init__(
     ):
         models = [dp_model, zbl_model]
         super().__init__(models, type_map, **kwargs)
-        self.model_def_script = ""
 
         self.sw_rmin = sw_rmin
         self.sw_rmax = sw_rmax

deepmd/pt/model/atomic_model/pairtab_atomic_model.py

@@ -78,7 +78,6 @@ def __init__(
         **kwargs,
     ):
         torch.nn.Module.__init__(self)
-        self.model_def_script = ""
         self.tab_file = tab_file
         self.rcut = rcut
         self.tab = self._set_pairtab(tab_file, rcut)

deepmd/pt/model/model/make_model.py

@@ -469,11 +469,6 @@ def get_nnei(self) -> int:
             """Returns the total number of selected neighboring atoms in the cut-off radius."""
             return self.atomic_model.get_nnei()
 
-        @torch.jit.export
-        def get_model_def_script(self) -> str:
-            """Get the model definition script."""
-            return self.atomic_model.get_model_def_script()
-
         def atomic_output_def(self) -> FittingOutputDef:
             """Get the output def of the atomic model."""
             return self.atomic_model.atomic_output_def()

deepmd/pt/model/model/model.py

@@ -17,6 +17,7 @@ class BaseModel(torch.nn.Module, make_base_model()):
     def __init__(self, *args, **kwargs):
         """Construct a basic model for different tasks."""
         torch.nn.Module.__init__(self)
+        self.model_def_script = ""
 
     def compute_or_load_stat(
         self,
@@ -39,3 +40,8 @@ def compute_or_load_stat(
             The path to the statistics files.
         """
         raise NotImplementedError
+
+    @torch.jit.export
+    def get_model_def_script(self) -> str:
+        """Get the model definition script."""
+        return self.model_def_script