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

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

Author: pre-commit-ci[bot]

deepmd/pt/infer/deep_eval.py

@@ -543,24 +543,33 @@ def _eval_model(
                 atomic_weight = np.tile(atomic_weight, (nframes, 1))
             elif atomic_weight.ndim == 2:
                 # (nframes, natoms) or (natoms, k)
-                if atomic_weight.shape[0] == natoms and atomic_weight.shape[1] != nframes:
+                if (
+                    atomic_weight.shape[0] == natoms
+                    and atomic_weight.shape[1] != nframes
+                ):
                     # (natoms, k) - broadcast across frames
                     atomic_weight = np.tile(atomic_weight, (nframes, 1, 1))
-                elif atomic_weight.shape[0] != nframes or atomic_weight.shape[1] != natoms:
+                elif (
+                    atomic_weight.shape[0] != nframes
+                    or atomic_weight.shape[1] != natoms
+                ):
                     raise ValueError(
                         f"atomic_weight shape {atomic_weight.shape} incompatible with nframes={nframes} and natoms={natoms}"
                     )
             elif atomic_weight.ndim == 3:
                 # (nframes, natoms, k)
-                if atomic_weight.shape[0] != nframes or atomic_weight.shape[1] != natoms:
+                if (
+                    atomic_weight.shape[0] != nframes
+                    or atomic_weight.shape[1] != natoms
+                ):
                     raise ValueError(
                         f"atomic_weight shape {atomic_weight.shape} incompatible with nframes={nframes} and natoms={natoms}"
                     )
             else:
                 raise ValueError(
                     f"atomic_weight must have 1, 2, or 3 dimensions, got {atomic_weight.ndim}"
                 )
-            
+
             atomic_weight_input = to_torch_tensor(
                 atomic_weight.reshape(nframes, natoms, -1)
             )
@@ -657,24 +666,33 @@ def _eval_model_spin(
                 atomic_weight = np.tile(atomic_weight, (nframes, 1))
             elif atomic_weight.ndim == 2:
                 # (nframes, natoms) or (natoms, k)
-                if atomic_weight.shape[0] == natoms and atomic_weight.shape[1] != nframes:
+                if (
+                    atomic_weight.shape[0] == natoms
+                    and atomic_weight.shape[1] != nframes
+                ):
                     # (natoms, k) - broadcast across frames
                     atomic_weight = np.tile(atomic_weight, (nframes, 1, 1))
-                elif atomic_weight.shape[0] != nframes or atomic_weight.shape[1] != natoms:
+                elif (
+                    atomic_weight.shape[0] != nframes
+                    or atomic_weight.shape[1] != natoms
+                ):
                     raise ValueError(
                         f"atomic_weight shape {atomic_weight.shape} incompatible with nframes={nframes} and natoms={natoms}"
                     )
             elif atomic_weight.ndim == 3:
                 # (nframes, natoms, k)
-                if atomic_weight.shape[0] != nframes or atomic_weight.shape[1] != natoms:
+                if (
+                    atomic_weight.shape[0] != nframes
+                    or atomic_weight.shape[1] != natoms
+                ):
                     raise ValueError(
                         f"atomic_weight shape {atomic_weight.shape} incompatible with nframes={nframes} and natoms={natoms}"
                     )
             else:
                 raise ValueError(
                     f"atomic_weight must have 1, 2, or 3 dimensions, got {atomic_weight.ndim}"
                 )
-            
+
             atomic_weight_input = to_torch_tensor(
                 atomic_weight.reshape(nframes, natoms, -1)
             )