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

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

deepmd/entrypoints/test.py

@@ -784,7 +784,9 @@ def test_property(
     assert isinstance(property_name, list)
     assert isinstance(property_dim, list)
     assert sum(property_dim) == dp.task_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}!"
     for name, dim in zip(property_name, property_dim):
         data.add(name, dim, atomic=False, must=True, high_prec=True)
         if has_atom_property:

deepmd/utils/out_stat.py

@@ -129,6 +129,7 @@ def compute_stats_from_atomic(
         )
     return output_bias, output_std
 
+
 def compute_stats_property(
     output_redu: np.ndarray,
     natoms: np.ndarray,

source/tests/common/dpmodel/test_output_def.py

@@ -94,12 +94,20 @@ def test_model_output_def(self) -> None:
                 c_differentiable=False,
                 atomic=True,
                 intensive=True,
-                sub_var_name=["foo","bar"],
+                sub_var_name=["foo", "bar"],
             ),
         ]
         # fitting definition
         fd = FittingOutputDef(defs)
-        expected_keys = ["energy", "energy2", "energy3", "dos", "foo", "gap", "property"]
+        expected_keys = [
+            "energy",
+            "energy2",
+            "energy3",
+            "dos",
+            "foo",
+            "gap",
+            "property",
+        ]
         self.assertEqual(
             set(expected_keys),
             set(fd.keys()),

source/tests/common/test_out_stat.py

@@ -93,8 +93,10 @@ def test_compute_stats_from_redu_with_assigned_bias(self) -> None:
     def test_compute_stats_property(self) -> None:
         bias, std = compute_stats_property(self.output_redu, self.natoms)
         for fake_atom_bias in bias:
-            np.testing.assert_allclose(fake_atom_bias, np.mean(self.output_redu,axis=0), rtol=1e-7)
-        np.testing.assert_allclose(std, np.std(self.output_redu,axis=0), rtol=1e-7)
+            np.testing.assert_allclose(
+                fake_atom_bias, np.mean(self.output_redu, axis=0), rtol=1e-7
+            )
+        np.testing.assert_allclose(std, np.std(self.output_redu, axis=0), rtol=1e-7)
 
     def test_compute_stats_from_atomic(self) -> None:
         bias, std = compute_stats_from_atomic(self.output, self.atype)