fix: eliminate all ANN401 errors by replacing Any with more specific types

deepmd/__init__.py

@@ -10,7 +10,6 @@
 
 from typing import (
     TYPE_CHECKING,
-    Any,
 )
 
 if TYPE_CHECKING:
@@ -24,7 +23,7 @@
     )
 
 
-def DeepPotential(*args: Any, **kwargs: Any) -> "DeepPotentialType":
+def DeepPotential(*args: object, **kwargs: object) -> "DeepPotentialType":
     """Factory function that forwards to DeepEval (for compatibility
     and performance).
 

deepmd/calculator.py

@@ -6,7 +6,6 @@
 )
 from typing import (
     TYPE_CHECKING,
-    Any,
     ClassVar,
     Optional,
     Union,
@@ -91,7 +90,7 @@ def __init__(
         type_dict: Optional[dict[str, int]] = None,
         neighbor_list: Optional["NeighborList"] = None,
         head: Optional[str] = None,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> None:
         Calculator.__init__(self, label=label, **kwargs)
         self.dp = DeepPot(

deepmd/common.py

@@ -284,7 +284,7 @@ def symlink_prefix_files(old_prefix: str, new_prefix: str) -> None:
             shutil.copyfile(ori_ff, new_ff)
 
 
-def get_hash(obj: Any) -> str:
+def get_hash(obj: object) -> str:
     """Get hash of object.
 
     Parameters

deepmd/entrypoints/convert_backend.py

@@ -1,7 +1,4 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
-from typing import (
-    Any,
-)
 
 from deepmd.backend.backend import (
     Backend,
@@ -12,7 +9,7 @@ def convert_backend(
     *,  # Enforce keyword-only arguments
     INPUT: str,
     OUTPUT: str,
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     """Convert a model file from one backend to another.
 

deepmd/entrypoints/doc.py

@@ -1,10 +1,6 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 """Module that prints train input arguments docstrings."""
 
-from typing import (
-    Any,
-)
-
 from deepmd.utils.argcheck import (
     gen_doc,
     gen_json,
@@ -15,7 +11,7 @@
 
 
 def doc_train_input(
-    *, out_type: str = "rst", multi_task: bool = False, **kwargs: Any
+    *, out_type: str = "rst", multi_task: bool = False, **kwargs: object
 ) -> None:
     """Print out trining input arguments to console."""
     if out_type == "rst":

deepmd/entrypoints/eval_desc.py

@@ -7,7 +7,6 @@
     Path,
 )
 from typing import (
-    Any,
     Optional,
 )
 
@@ -35,7 +34,7 @@ def eval_desc(
     datafile: str,
     output: str = "desc",
     head: Optional[str] = None,
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     """Evaluate descriptors for given systems.
 

deepmd/entrypoints/gui.py

@@ -1,12 +1,8 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 """DP-GUI entrypoint."""
 
-from typing import (
-    Any,
-)
 
-
-def start_dpgui(*, port: int, bind_all: bool, **kwargs: Any) -> None:
+def start_dpgui(*, port: int, bind_all: bool, **kwargs: object) -> None:
     """Host DP-GUI server.
 
     Parameters

deepmd/entrypoints/neighbor_stat.py

@@ -1,7 +1,6 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import logging
 from typing import (
-    Any,
     Optional,
 )
 
@@ -25,7 +24,7 @@ def neighbor_stat(
     type_map: Optional[list[str]],
     mixed_type: bool = False,
     backend: str = "tensorflow",
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     """Calculate neighbor statistics.
 

deepmd/entrypoints/show.py

@@ -1,8 +1,5 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import logging
-from typing import (
-    Any,
-)
 
 from deepmd.infer.deep_eval import (
     DeepEval,
@@ -22,7 +19,7 @@ def show(
     *,
     INPUT: str,
     ATTRIBUTES: list[str],
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     model = DeepEval(INPUT, head=0)
     model_params = model.get_model_def_script()

deepmd/entrypoints/test.py

@@ -7,7 +7,6 @@
 )
 from typing import (
     TYPE_CHECKING,
-    Any,
     Optional,
 )
 
@@ -67,7 +66,7 @@ def test(
     detail_file: str,
     atomic: bool,
     head: Optional[str] = None,
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     """Test model predictions.
 

deepmd/infer/deep_dos.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 from typing import (
-    Any,
     Optional,
     Union,
 )
@@ -67,7 +66,7 @@ def eval(
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
         mixed_type: bool = False,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> tuple[np.ndarray, ...]:
         """Evaluate energy, force, and virial. If atomic is True,
         also return atomic energy and atomic virial.

deepmd/infer/deep_eval.py

@@ -5,7 +5,6 @@
 )
 from typing import (
     TYPE_CHECKING,
-    Any,
     ClassVar,
     Optional,
     Union,
@@ -83,10 +82,10 @@ def __init__(
         self,
         model_file: str,
         output_def: ModelOutputDef,
-        *args: Any,
+        *args: object,
         auto_batch_size: Union[bool, int, AutoBatchSize] = True,
         neighbor_list: Optional["ase.neighborlist.NewPrimitiveNeighborList"] = None,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> None:
         pass
 
@@ -107,7 +106,7 @@ def eval(
         atomic: bool = False,
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> dict[str, np.ndarray]:
         """Evaluate the energy, force and virial by using this DP.
 
@@ -175,7 +174,7 @@ def eval_descriptor(
         aparam: Optional[np.ndarray] = None,
         efield: Optional[np.ndarray] = None,
         mixed_type: bool = False,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> np.ndarray:
         """Evaluate descriptors by using this DP.
 
@@ -224,7 +223,7 @@ def eval_fitting_last_layer(
         atom_types: np.ndarray,
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> np.ndarray:
         """Evaluate fitting before last layer by using this DP.
 
@@ -381,10 +380,10 @@ def __new__(cls, model_file: str, *args: object, **kwargs: object) -> "DeepEval"
     def __init__(
         self,
         model_file: str,
-        *args: Any,
+        *args: object,
         auto_batch_size: Union[bool, int, AutoBatchSize] = True,
         neighbor_list: Optional["ase.neighborlist.NewPrimitiveNeighborList"] = None,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> None:
         self.deep_eval = DeepEvalBackend(
             model_file,
@@ -454,7 +453,7 @@ def eval_descriptor(
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
         mixed_type: bool = False,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> np.ndarray:
         """Evaluate descriptors by using this DP.
 
@@ -521,7 +520,7 @@ def eval_fitting_last_layer(
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
         mixed_type: bool = False,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> np.ndarray:
         """Evaluate fitting before last layer by using this DP.
 

deepmd/infer/deep_polar.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 from typing import (
-    Any,
     Optional,
     Union,
 )
@@ -56,7 +55,7 @@ def eval(
         fparam: Optional[np.ndarray] = None,
         aparam: Optional[np.ndarray] = None,
         mixed_type: bool = False,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> np.ndarray:
         """Evaluate the model.
 

deepmd/infer/deep_pot.py

@@ -99,7 +99,7 @@ def eval(
         fparam: Optional[np.ndarray],
         aparam: Optional[np.ndarray],
         mixed_type: bool,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> Union[
         tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray],
         tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray, np.ndarray],
@@ -116,7 +116,7 @@ def eval(
         fparam: Optional[np.ndarray],
         aparam: Optional[np.ndarray],
         mixed_type: bool,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> Union[
         tuple[np.ndarray, np.ndarray, np.ndarray],
         tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray],
@@ -133,7 +133,7 @@ def eval(
         fparam: Optional[np.ndarray],
         aparam: Optional[np.ndarray],
         mixed_type: bool,
-        **kwargs: Any,
+        **kwargs: object,
     ) -> tuple[np.ndarray, ...]:
         pass
 

deepmd/infer/model_devi.py

@@ -1,6 +1,5 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 from typing import (
-    Any,
     Optional,
     overload,
 )
@@ -364,7 +363,7 @@ def make_model_devi(
     atomic: bool = False,
     relative: Optional[float] = None,
     relative_v: Optional[float] = None,
-    **kwargs: Any,
+    **kwargs: object,
 ) -> None:
     """Make model deviation calculation.
 

deepmd/main.py

@@ -14,7 +14,6 @@
     defaultdict,
 )
 from typing import (
-    Any,
     Optional,
 )
 
@@ -68,15 +67,15 @@ def __call__(
         self,
         parser: argparse.ArgumentParser,
         namespace: argparse.Namespace,
-        values: Any,
+        values: object,
         option_string: Optional[str] = None,
     ) -> None:
         setattr(namespace, self.dest, BACKEND_TABLE[values])
 
 
 class DeprecateAction(argparse.Action):
     # See https://stackoverflow.com/a/69052677/9567349 by Ibolit under CC BY-SA 4.0
-    def __init__(self, *args: Any, **kwargs: Any) -> None:
+    def __init__(self, *args: object, **kwargs: object) -> None:
         self.call_count = 0
         if "help" in kwargs:
             kwargs["help"] = f"[DEPRECATED] {kwargs['help']}"
@@ -86,7 +85,7 @@ def __call__(
         self,
         parser: argparse.ArgumentParser,
         namespace: argparse.Namespace,
-        values: Any,
+        values: object,
         option_string: Optional[str] = None,
     ) -> None:
         if self.call_count == 0: