[pre-commit.ci] pre-commit autoupdate (#5178)

<!--pre-commit.ci start-->
updates:
- [github.com/astral-sh/ruff-pre-commit: v0.14.13 →
v0.14.14](astral-sh/ruff-pre-commit@v0.14.13...v0.14.14)
<!--pre-commit.ci end-->

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Jinzhe Zeng <jinzhe.zeng@ustc.edu.cn>

Author: pre-commit-ci[bot]

.pre-commit-config.yaml

@@ -29,7 +29,7 @@ repos:
         exclude: ^source/3rdparty
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.14.13
+    rev: v0.14.14
     hooks:
       - id: ruff
         args: ["--fix"]

deepmd/dpmodel/modifier/base_modifier.py

@@ -8,6 +8,10 @@
     Any,
 )
 
+from typing_extensions import (
+    Self,
+)
+
 from deepmd.utils.plugin import (
     PluginVariant,
     make_plugin_registry,
@@ -18,7 +22,7 @@ def make_base_modifier() -> type[object]:
     class BaseModifier(ABC, PluginVariant, make_plugin_registry("modifier")):
         """Base class for data modifier."""
 
-        def __new__(cls, *args: Any, **kwargs: Any) -> "BaseModifier":
+        def __new__(cls, *args: Any, **kwargs: Any) -> Self:
             if cls is BaseModifier:
                 cls = cls.get_class_by_type(kwargs["type"])
             return super().__new__(cls)

deepmd/infer/deep_eval.py

@@ -11,6 +11,9 @@
 )
 
 import numpy as np
+from typing_extensions import (
+    Self,
+)
 
 from deepmd.backend.backend import (
     Backend,
@@ -89,9 +92,7 @@ def __init__(
     ) -> None:
         pass
 
-    def __new__(
-        cls, model_file: str, *args: object, **kwargs: object
-    ) -> "DeepEvalBackend":
+    def __new__(cls, model_file: str, *args: object, **kwargs: object) -> Self:
         if cls is DeepEvalBackend:
             backend = Backend.detect_backend_by_model(model_file)
             return super().__new__(backend().deep_eval)
@@ -384,7 +385,7 @@ class DeepEval(ABC):
         Keyword arguments.
     """
 
-    def __new__(cls, model_file: str, *args: object, **kwargs: object) -> "DeepEval":
+    def __new__(cls, model_file: str, *args: object, **kwargs: object) -> Self:
         if cls is DeepEval:
             deep_eval = DeepEvalBackend(
                 model_file,

deepmd/pd/model/descriptor/descriptor.py

@@ -13,6 +13,9 @@
 )
 
 import paddle
+from typing_extensions import (
+    Self,
+)
 
 from deepmd.pd.model.network.network import (
     TypeEmbedNet,
@@ -44,7 +47,7 @@ class DescriptorBlock(paddle.nn.Layer, ABC, make_plugin_registry("DescriptorBloc
 
     local_cluster = False
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> "DescriptorBlock":
+    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
         if cls is DescriptorBlock:
             try:
                 descrpt_type = kwargs["type"]

deepmd/pd/model/task/fitting.py

@@ -12,6 +12,9 @@
 
 import numpy as np
 import paddle
+from typing_extensions import (
+    Self,
+)
 
 from deepmd.dpmodel.utils.seed import (
     child_seed,
@@ -54,7 +57,7 @@
 class Fitting(paddle.nn.Layer, BaseFitting):
     # plugin moved to BaseFitting
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> "Fitting":
+    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
         if cls is Fitting:
             return BaseFitting.__new__(BaseFitting, *args, **kwargs)
         return super().__new__(cls)

deepmd/pt/model/descriptor/descriptor.py

@@ -13,6 +13,9 @@
 )
 
 import torch
+from typing_extensions import (
+    Self,
+)
 
 from deepmd.pt.model.network.network import (
     TypeEmbedNet,
@@ -44,7 +47,7 @@ class DescriptorBlock(torch.nn.Module, ABC, make_plugin_registry("DescriptorBloc
 
     local_cluster = False
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> "DescriptorBlock":
+    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
         if cls is DescriptorBlock:
             try:
                 descrpt_type = kwargs["type"]

deepmd/pt/model/task/fitting.py

@@ -13,6 +13,9 @@
 
 import numpy as np
 import torch
+from typing_extensions import (
+    Self,
+)
 
 from deepmd.dpmodel.utils.seed import (
     child_seed,
@@ -58,7 +61,7 @@
 class Fitting(torch.nn.Module, BaseFitting):
     # plugin moved to BaseFitting
 
-    def __new__(cls, *args: Any, **kwargs: Any) -> "Fitting":
+    def __new__(cls, *args: Any, **kwargs: Any) -> Self:
         if cls is Fitting:
             return BaseFitting.__new__(BaseFitting, *args, **kwargs)
         return super().__new__(cls)

deepmd/utils/path.py

@@ -18,6 +18,9 @@
 
 import h5py
 import numpy as np
+from typing_extensions import (
+    Self,
+)
 from wcmatch.glob import (
     globfilter,
 )
@@ -34,7 +37,7 @@ class DPPath(ABC):
         mode, by default "r"
     """
 
-    def __new__(cls, path: str, mode: str = "r") -> "DPPath":
+    def __new__(cls, path: str, mode: str = "r") -> Self:
         if cls is DPPath:
             if os.path.isdir(path):
                 return super().__new__(DPOSPath)

pyproject.toml

@@ -45,7 +45,7 @@ dependencies = [
     'scipy',
     'pyyaml',
     'dargs >= 0.4.7',
-    'typing_extensions; python_version < "3.8"',
+    'typing_extensions>=4.0.0',
     'importlib_metadata>=1.4; python_version < "3.8"',
     'h5py',
     "h5py>=3.6.0,!=3.11.0; platform_system=='Linux' and platform_machine=='aarch64'",