[pre-commit.ci] pre-commit autoupdate

.pre-commit-config.yaml

@@ -23,14 +23,14 @@ repos:
       - id: check-toml
   # Python
   - repo: https://github.com/PyCQA/isort
-    rev: 9.0.0b1
+    rev: 10.0.0b1
     hooks:
       - id: isort
         files: \.py$
         exclude: ^source/3rdparty
   - repo: https://github.com/astral-sh/ruff-pre-commit
     # Ruff version.
-    rev: v0.16.0
+    rev: v0.17.2
     hooks:
       - id: ruff
         args: ["--fix"]
@@ -62,7 +62,7 @@ repos:
           - mdformat-gfm-alerts==2.0.0
   # C++
   - repo: https://github.com/pre-commit/mirrors-clang-format
-    rev: v22.1.8
+    rev: v23.1.3
     hooks:
       - id: clang-format
         exclude: ^(source/3rdparty|source/lib/src/gpu/cudart/.+\.inc|.+\.ipynb$|source/tests/infer/.+\.json$)
@@ -76,7 +76,7 @@ repos:
         exclude: ^(source/3rdparty|\.clang-format)
   # Shell
   - repo: https://github.com/scop/pre-commit-shfmt
-    rev: v3.13.1-1
+    rev: v3.14.1-1
     hooks:
       - id: shfmt
   # CMake
@@ -156,7 +156,7 @@ repos:
         exclude: .pre-commit-config.yaml|source/lmp
   # customized pylint rules
   - repo: https://github.com/pylint-dev/pylint/
-    rev: v4.0.6
+    rev: v4.1.3
     hooks:
       - id: pylint
         entry: env PYTHONPATH=source/checker pylint

deepmd/_vendors/ndtensorflow/linalg.py

@@ -24,12 +24,10 @@
     finfo,
     matmul,
     matrix_transpose,
-)
-from ._namespace import sum as xp_sum
-from ._namespace import (
     tensordot,
     vecdot,
 )
+from ._namespace import sum as xp_sum
 
 EighResult = namedtuple("EighResult", ["eigenvalues", "eigenvectors"])
 EigResult = namedtuple("EigResult", ["eigenvalues", "eigenvectors"])

deepmd/pd/model/network/mlp.py

@@ -20,13 +20,11 @@
 
 from deepmd.dpmodel.utils import (
     NativeLayer,
-)
-from deepmd.dpmodel.utils import NetworkCollection as DPNetworkCollection
-from deepmd.dpmodel.utils import (
     make_embedding_network,
     make_fitting_network,
     make_multilayer_network,
 )
+from deepmd.dpmodel.utils import NetworkCollection as DPNetworkCollection
 from deepmd.pd.model.network.init import (
     PaddleGenerator,
     kaiming_normal_,

deepmd/pd/utils/finetune.py

@@ -9,11 +9,9 @@
 
 from deepmd.utils.finetune import (
     FinetuneRuleItem,
-)
-from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
-from deepmd.utils.finetune import (
     get_finetune_rules_from_model_params,
 )
+from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
 
 __all__ = ["get_finetune_rule_single", "get_finetune_rules"]
 

deepmd/pt/model/network/mlp.py

@@ -17,13 +17,11 @@
 
 from deepmd.dpmodel.utils import (
     NativeLayer,
-)
-from deepmd.dpmodel.utils import NetworkCollection as DPNetworkCollection
-from deepmd.dpmodel.utils import (
     make_embedding_network,
     make_fitting_network,
     make_multilayer_network,
 )
+from deepmd.dpmodel.utils import NetworkCollection as DPNetworkCollection
 from deepmd.pt.model.network.init import (
     kaiming_normal_,
     normal_,

deepmd/pt/utils/finetune.py

@@ -12,11 +12,9 @@
 )
 from deepmd.utils.finetune import (
     FinetuneRuleItem,
-)
-from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
-from deepmd.utils.finetune import (
     get_finetune_rules_from_model_params,
 )
+from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
 
 __all__ = ["get_finetune_rule_single", "get_finetune_rules"]
 

deepmd/pt_expt/common.py

@@ -628,7 +628,9 @@ def _ensure_registrations() -> None:
     converters are registered before any descriptors/fittings try to use them.
     """
     # Import triggers registration of NetworkCollection, ExcludeMask, EnvMat
-    from deepmd.pt_expt import utils  # noqa: F401
+    from deepmd.pt_expt import (  # noqa: F401
+        utils,
+    )
 
 
 _ensure_registrations()

deepmd/pt_expt/kernels/dpa4c/canonical.py

@@ -459,13 +459,11 @@ def dpa4c_canonical_compress_energy_force(
     from deepmd.pt_expt.kernels.edge_force_virial import (
         canonical_edge_force_virial,
         canonical_op_available,
+        frame_scalar_sum,
     )
     from deepmd.pt_expt.kernels.edge_force_virial import (
         ensure_registered as ensure_force_registered,
     )
-    from deepmd.pt_expt.kernels.edge_force_virial import (
-        frame_scalar_sum,
-    )
     from deepmd.pt_expt.kernels.graph_fitting import (
         ensure_registered as ensure_fitting_registered,
     )

deepmd/pt_expt/kernels/dpa4c/graph_compress.py

@@ -2233,13 +2233,11 @@ def dpa4c_graph_compress_energy_force(
     """
     from deepmd.pt_expt.kernels.edge_force_virial import (
         edge_force_virial,
+        frame_scalar_sum,
     )
     from deepmd.pt_expt.kernels.edge_force_virial import (
         ensure_registered as ensure_force_registered,
     )
-    from deepmd.pt_expt.kernels.edge_force_virial import (
-        frame_scalar_sum,
-    )
     from deepmd.pt_expt.kernels.graph_fitting import (
         ensure_registered as ensure_fitting_registered,
     )

deepmd/pt_expt/train/training.py

@@ -100,12 +100,10 @@
     apply_global_compile_patches,
     build_inductor_compile_options,
     check_compile_torch_version,
+    relax_views_to_reshapes,
 )
 from deepmd.pt.utils.compile_compat import next_safe_prime as _next_safe_prime
 from deepmd.pt.utils.compile_compat import rebuild_graph_module as _rebuild_graph_module
-from deepmd.pt.utils.compile_compat import (
-    relax_views_to_reshapes,
-)
 from deepmd.pt.utils.compile_compat import (
     strip_saved_tensor_detach as _strip_saved_tensor_detach,
 )

deepmd/pt_expt/utils/finetune.py

@@ -15,11 +15,9 @@
 )
 from deepmd.utils.finetune import (
     FinetuneRuleItem,
-)
-from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
-from deepmd.utils.finetune import (
     get_finetune_rules_from_model_params,
 )
+from deepmd.utils.finetune import get_finetune_rule_single as get_finetune_rule_single
 
 __all__ = ["get_finetune_rule_single", "get_finetune_rules"]
 

deepmd/pt_expt/utils/type_embed.py

@@ -12,7 +12,9 @@
 )
 
 # Import network to ensure EmbeddingNet is registered before TypeEmbedNet is used
-from deepmd.pt_expt.utils import network  # noqa: F401
+from deepmd.pt_expt.utils import (  # noqa: F401
+    network,
+)
 
 
 class TypeEmbedNet(TypeEmbedNetDP, torch.nn.Module):

deepmd/tf/env.py

@@ -27,15 +27,11 @@
     GLOBAL_NP_FLOAT_PRECISION,
     SHARED_LIB_DIR,
     SHARED_LIB_MODULE,
-)
-from deepmd.env import get_default_nthreads as get_tf_default_nthreads
-from deepmd.env import (
     global_float_prec,
-)
-from deepmd.env import set_default_nthreads as set_tf_default_nthreads
-from deepmd.env import (
     set_env_if_empty,
 )
+from deepmd.env import get_default_nthreads as get_tf_default_nthreads
+from deepmd.env import set_default_nthreads as set_tf_default_nthreads
 
 if TYPE_CHECKING:
     from types import (

deepmd/tf/model/model_stat.py

@@ -3,11 +3,9 @@
 
 from deepmd.utils.model_stat import (
     _make_all_stat_ref,
-)
-from deepmd.utils.model_stat import collect_batches as make_stat_input
-from deepmd.utils.model_stat import (
     merge_sys_stat,
 )
+from deepmd.utils.model_stat import collect_batches as make_stat_input
 
 __all__ = [
     "_make_all_stat_ref",  # used by tests

deepmd/utils/data_system.py

@@ -40,13 +40,11 @@
 from deepmd.utils.data_path import process_systems as process_systems
 from deepmd.utils.data_sampling import (
     data_child_seeds,
-)
-from deepmd.utils.data_sampling import prob_sys_size_ext as prob_sys_size_ext
-from deepmd.utils.data_sampling import process_sys_probs as process_sys_probs
-from deepmd.utils.data_sampling import (
     system_probabilities,
     uniform_sampling_weights,
 )
+from deepmd.utils.data_sampling import prob_sys_size_ext as prob_sys_size_ext
+from deepmd.utils.data_sampling import process_sys_probs as process_sys_probs
 from deepmd.utils.out_stat import (
     compute_stats_from_redu,
 )

source/tests/pt_expt/model/test_unimol.py

@@ -17,11 +17,9 @@
 
 from deepmd.dpmodel.descriptor.unimol import (
     UNIMOL_ELEMENTS,
-)
-from deepmd.dpmodel.descriptor.unimol import DescrptUniMol as DescrptUniMolDP
-from deepmd.dpmodel.descriptor.unimol import (
     unimol_vocabulary,
 )
+from deepmd.dpmodel.descriptor.unimol import DescrptUniMol as DescrptUniMolDP
 from deepmd.dpmodel.fitting.unimol_pretrain import (
     UniMolPretrainFitting as UniMolPretrainFittingDP,
 )