[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

deepmd/dpmodel/output_def.py

@@ -4,8 +4,8 @@
     IntEnum,
 )
 from typing import (
-    Union,
     Optional,
+    Union,
 )
 
 

deepmd/pt/loss/property.py

@@ -57,7 +57,9 @@ def __init__(
             property_dim = [property_dim]
         self.property_name = property_name
         assert self.task_dim == sum(property_dim)
-        assert len(property_name) == len(property_dim), f"The shape of the `property_name` you provide must be consistent with the `property_dim`, but your `property_name` is {property_name} and your `property_dim` is {property_dim}!"
+        assert (
+            len(property_name) == len(property_dim)
+        ), f"The shape of the `property_name` you provide must be consistent with the `property_dim`, but your `property_name` is {property_name} and your `property_dim` is {property_dim}!"
         self.property_name_dim_mapping = dict(zip(property_name, property_dim))
         self.out_bias = out_bias
         self.out_std = out_std

deepmd/pt/model/model/__init__.py

@@ -100,7 +100,7 @@ def _get_standard_model_components(model_params, ntypes):
             fitting_net["return_energy"] = True
     if "property" in fitting_net["type"]:
         if isinstance(fitting_net["property_dim"], list):
-            fitting_net["task_dim"]  = sum(fitting_net["property_dim"])
+            fitting_net["task_dim"] = sum(fitting_net["property_dim"])
         else:
             fitting_net["task_dim"] = fitting_net["property_dim"]
     fitting = BaseFitting(**fitting_net)

deepmd/pt/utils/stat.py

@@ -519,10 +519,12 @@ def compute_output_stats_global(
             concat_bias.append(bias_atom_e[ii])
             concat_std.append(std_atom_e[ii])
         bias_atom_e = {"property": np.concatenate(concat_bias, axis=-1)}
-        std_atom_e = {"property": np.tile(
-             np.concatenate(concat_std, axis=-1),
-             (bias_atom_e["property"].shape[0], 1)
-        )}
+        std_atom_e = {
+            "property": np.tile(
+                np.concatenate(concat_std, axis=-1),
+                (bias_atom_e["property"].shape[0], 1),
+            )
+        }
 
         return bias_atom_e, std_atom_e
 

deepmd/utils/argcheck.py

@@ -2512,7 +2512,7 @@ def loss_property():
             optional=True,
             default=1.00,
             doc=doc_beta,
-        )
+        ),
     ]