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source/tests/consistent/model/test_dos.py

@@ -6,18 +6,8 @@
 
 import numpy as np
 
-from deepmd.dpmodel.common import (
-    to_numpy_array,
-)
 from deepmd.dpmodel.model.dos_model import DOSModel as DOSModelDP
 from deepmd.dpmodel.model.model import get_model as get_model_dp
-from deepmd.dpmodel.utils.nlist import (
-    build_neighbor_list,
-    extend_coord_with_ghosts,
-)
-from deepmd.dpmodel.utils.region import (
-    normalize_coord,
-)
 from deepmd.env import (
     GLOBAL_NP_FLOAT_PRECISION,
 )
@@ -36,8 +26,6 @@
 if INSTALLED_PT:
     from deepmd.pt.model.model import get_model as get_model_pt
     from deepmd.pt.model.model.dos_model import DOSModel as DOSModelPT
-    from deepmd.pt.utils.utils import to_numpy_array as torch_to_numpy
-    from deepmd.pt.utils.utils import to_torch_tensor as numpy_to_torch
 else:
     DOSModelPT = None
 if INSTALLED_TF:
@@ -64,39 +52,27 @@ class TestDOS(CommonTest, ModelTest, unittest.TestCase):
     def data(self) -> dict:
         pair_exclude_types, atom_exclude_types = self.param
         return {
-            "type_map": [
-            "H"
-            ],
+            "type_map": ["H"],
             "descriptor": {
-            "type": "se_e2_a",
-            "sel": [
-                90
-            ],
-            "rcut_smth": 1.8,
-            "rcut": 6.0,
-            "neuron": [
-                25,
-                50,
-                100
-            ],
-            "resnet_dt": False,
-            "axis_neuron": 8,
-            "precision": "float64",
-            "seed": 1
+                "type": "se_e2_a",
+                "sel": [90],
+                "rcut_smth": 1.8,
+                "rcut": 6.0,
+                "neuron": [25, 50, 100],
+                "resnet_dt": False,
+                "axis_neuron": 8,
+                "precision": "float64",
+                "seed": 1,
             },
             "fitting_net": {
-            "type": "dos",
-            "numb_dos": 250,
-            "neuron": [
-                120,
-                120,
-                120
-            ],
-            "resnet_dt": True,
-            "numb_fparam": 0,
-            "precision": "float64",
-            "seed": 1
-            }
+                "type": "dos",
+                "numb_dos": 250,
+                "neuron": [120, 120, 120],
+                "resnet_dt": True,
+                "numb_fparam": 0,
+                "precision": "float64",
+                "seed": 1,
+            },
         }
 
     tf_class = DOSModelTF
@@ -242,4 +218,3 @@ def extract_ret(self, ret: Any, backend) -> tuple[np.ndarray, ...]:
                 ret[4].ravel(),
             )
         raise ValueError(f"Unknown backend: {backend}")
-