Add compression API to BaseModel and AtomicModel (#4298)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

- **New Features**
- Introduced `enable_compression` method across multiple classes to
allow configuration of compression settings for descriptors.
- Enhanced robustness of output definitions and serialization processes
in the `DPAtomicModel` class.
- Added `enable_compression` method to `LinearEnergyAtomicModel` for
improved model compression capabilities.

- **Bug Fixes**
- Improved error handling in the `fitting_output_def` method to ensure
fallback functionality when the fitting network is unavailable.

These updates enhance the functionality and reliability of the model
management features.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

deepmd/dpmodel/atomic_model/dp_atomic_model.py

@@ -86,6 +86,37 @@ def need_sorted_nlist_for_lower(self) -> bool:
         """Returns whether the atomic model needs sorted nlist when using `forward_lower`."""
         return self.descriptor.need_sorted_nlist_for_lower()
 
+    def enable_compression(
+        self,
+        min_nbor_dist: float,
+        table_extrapolate: float = 5,
+        table_stride_1: float = 0.01,
+        table_stride_2: float = 0.1,
+        check_frequency: int = -1,
+    ) -> None:
+        """Call descriptor enable_compression().
+
+        Parameters
+        ----------
+        min_nbor_dist
+            The nearest distance between atoms
+        table_extrapolate
+            The scale of model extrapolation
+        table_stride_1
+            The uniform stride of the first table
+        table_stride_2
+            The uniform stride of the second table
+        check_frequency
+            The overflow check frequency
+        """
+        self.descriptor.enable_compression(
+            min_nbor_dist,
+            table_extrapolate,
+            table_stride_1,
+            table_stride_2,
+            check_frequency,
+        )
+
     def forward_atomic(
         self,
         extended_coord: np.ndarray,

deepmd/dpmodel/atomic_model/linear_atomic_model.py

@@ -149,6 +149,38 @@ def _sort_rcuts_sels(self) -> tuple[list[float], list[int]]:
         )
         return [p[0] for p in zipped], [p[1] for p in zipped]
 
+    def enable_compression(
+        self,
+        min_nbor_dist: float,
+        table_extrapolate: float = 5,
+        table_stride_1: float = 0.01,
+        table_stride_2: float = 0.1,
+        check_frequency: int = -1,
+    ) -> None:
+        """Compress model.
+
+        Parameters
+        ----------
+        min_nbor_dist
+            The nearest distance between atoms
+        table_extrapolate
+            The scale of model extrapolation
+        table_stride_1
+            The uniform stride of the first table
+        table_stride_2
+            The uniform stride of the second table
+        check_frequency
+            The overflow check frequency
+        """
+        for model in self.models:
+            model.enable_compression(
+                min_nbor_dist,
+                table_extrapolate,
+                table_stride_1,
+                table_stride_2,
+                check_frequency,
+            )
+
     def forward_atomic(
         self,
         extended_coord,

deepmd/dpmodel/atomic_model/make_base_atomic_model.py

@@ -148,6 +148,31 @@ def change_type_map(
         ) -> None:
             pass
 
+        def enable_compression(
+            self,
+            min_nbor_dist: float,
+            table_extrapolate: float = 5,
+            table_stride_1: float = 0.01,
+            table_stride_2: float = 0.1,
+            check_frequency: int = -1,
+        ) -> None:
+            """Call descriptor enable_compression().
+
+            Parameters
+            ----------
+            min_nbor_dist
+                The nearest distance between atoms
+            table_extrapolate
+                The scale of model extrapolation
+            table_stride_1
+                The uniform stride of the first table
+            table_stride_2
+                The uniform stride of the second table
+            check_frequency
+                The overflow check frequency
+            """
+            raise NotImplementedError("This atomi model doesn't support compression!")
+
         def make_atom_mask(
             self,
             atype: t_tensor,

deepmd/dpmodel/model/base_model.py

@@ -191,6 +191,28 @@ def update_sel(
             cls = cls.get_class_by_type(model_type)
             return cls.update_sel(train_data, type_map, local_jdata)
 
+        def enable_compression(
+            self,
+            table_extrapolate: float = 5,
+            table_stride_1: float = 0.01,
+            table_stride_2: float = 0.1,
+            check_frequency: int = -1,
+        ) -> None:
+            """Enable model compression by tabulation.
+
+            Parameters
+            ----------
+            table_extrapolate
+                The scale of model extrapolation
+            table_stride_1
+                The uniform stride of the first table
+            table_stride_2
+                The uniform stride of the second table
+            check_frequency
+                The overflow check frequency
+            """
+            raise NotImplementedError("This atomic model doesn't support compression!")
+
         @classmethod
         def get_model(cls, model_params: dict) -> "BaseBaseModel":
             """Get the model by the parameters.

deepmd/dpmodel/model/make_model.py

@@ -186,6 +186,34 @@ def model_output_type(self) -> list[str]:
             ]
             return vars
 
+        def enable_compression(
+            self,
+            table_extrapolate: float = 5,
+            table_stride_1: float = 0.01,
+            table_stride_2: float = 0.1,
+            check_frequency: int = -1,
+        ) -> None:
+            """Call atomic_model enable_compression().
+
+            Parameters
+            ----------
+            table_extrapolate
+                The scale of model extrapolation
+            table_stride_1
+                The uniform stride of the first table
+            table_stride_2
+                The uniform stride of the second table
+            check_frequency
+                The overflow check frequency
+            """
+            self.atomic_model.enable_compression(
+                self.get_min_nbor_dist(),
+                table_extrapolate,
+                table_stride_1,
+                table_stride_2,
+                check_frequency,
+            )
+
         def call(
             self,
             coord,

deepmd/pt/model/atomic_model/dp_atomic_model.py

@@ -160,6 +160,37 @@ def deserialize(cls, data) -> "DPAtomicModel":
         obj = super().deserialize(data)
         return obj
 
+    def enable_compression(
+        self,
+        min_nbor_dist: float,
+        table_extrapolate: float = 5,
+        table_stride_1: float = 0.01,
+        table_stride_2: float = 0.1,
+        check_frequency: int = -1,
+    ) -> None:
+        """Call descriptor enable_compression().
+
+        Parameters
+        ----------
+        min_nbor_dist
+            The nearest distance between atoms
+        table_extrapolate
+            The scale of model extrapolation
+        table_stride_1
+            The uniform stride of the first table
+        table_stride_2
+            The uniform stride of the second table
+        check_frequency
+            The overflow check frequency
+        """
+        self.descriptor.enable_compression(
+            min_nbor_dist,
+            table_extrapolate,
+            table_stride_1,
+            table_stride_2,
+            check_frequency,
+        )
+
     def forward_atomic(
         self,
         extended_coord,

deepmd/pt/model/atomic_model/linear_atomic_model.py

@@ -184,6 +184,38 @@ def _sort_rcuts_sels(self) -> tuple[list[float], list[int]]:
         sorted_sels: list[int] = outer_sorted[:, 1].to(torch.int64).tolist()
         return sorted_rcuts, sorted_sels
 
+    def enable_compression(
+        self,
+        min_nbor_dist: float,
+        table_extrapolate: float = 5,
+        table_stride_1: float = 0.01,
+        table_stride_2: float = 0.1,
+        check_frequency: int = -1,
+    ) -> None:
+        """Compress model.
+
+        Parameters
+        ----------
+        min_nbor_dist
+            The nearest distance between atoms
+        table_extrapolate
+            The scale of model extrapolation
+        table_stride_1
+            The uniform stride of the first table
+        table_stride_2
+            The uniform stride of the second table
+        check_frequency
+            The overflow check frequency
+        """
+        for model in self.models:
+            model.enable_compression(
+                min_nbor_dist,
+                table_extrapolate,
+                table_stride_1,
+                table_stride_2,
+                check_frequency,
+            )
+
     def forward_atomic(
         self,
         extended_coord: torch.Tensor,

deepmd/pt/model/model/make_model.py

@@ -98,6 +98,34 @@ def model_output_type(self) -> list[str]:
                     vars.append(kk)
             return vars
 
+        def enable_compression(
+            self,
+            table_extrapolate: float = 5,
+            table_stride_1: float = 0.01,
+            table_stride_2: float = 0.1,
+            check_frequency: int = -1,
+        ) -> None:
+            """Call atomic_model enable_compression().
+
+            Parameters
+            ----------
+            table_extrapolate
+                The scale of model extrapolation
+            table_stride_1
+                The uniform stride of the first table
+            table_stride_2
+                The uniform stride of the second table
+            check_frequency
+                The overflow check frequency
+            """
+            self.atomic_model.enable_compression(
+                self.get_min_nbor_dist(),
+                table_extrapolate,
+                table_stride_1,
+                table_stride_2,
+                check_frequency,
+            )
+
         # cannot use the name forward. torch script does not work
         def forward_common(
             self,