From 50cdfe002034025a260344b2c3e7cc1fdf3c03db Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 26 Feb 2024 06:53:37 +0000
Subject: [PATCH] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 deepmd/pt/model/descriptor/__init__.py |  1 -
 deepmd/pt/model/descriptor/env_mat.py  | 15 ++++++++++++---
 deepmd/pt/model/descriptor/se_r.py     |  4 ----
 deepmd/pt/utils/env_mat_stat.py        | 12 ++++++++----
 4 files changed, 20 insertions(+), 12 deletions(-)

diff --git a/deepmd/pt/model/descriptor/__init__.py b/deepmd/pt/model/descriptor/__init__.py
index 2c55346f94..784db59be0 100644
--- a/deepmd/pt/model/descriptor/__init__.py
+++ b/deepmd/pt/model/descriptor/__init__.py
@@ -13,7 +13,6 @@
 )
 from .env_mat import (
     prod_env_mat,
-
 )
 from .gaussian_lcc import (
     DescrptGaussianLcc,
diff --git a/deepmd/pt/model/descriptor/env_mat.py b/deepmd/pt/model/descriptor/env_mat.py
index c3a1d38726..4e6ffb7785 100644
--- a/deepmd/pt/model/descriptor/env_mat.py
+++ b/deepmd/pt/model/descriptor/env_mat.py
@@ -1,5 +1,5 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
-from typing import Optional
+
 import torch
 
 from deepmd.pt.utils.preprocess import (
@@ -7,7 +7,9 @@
 )
 
 
-def _make_env_mat(nlist, coord, rcut: float, ruct_smth: float, radial_only: bool=False):
+def _make_env_mat(
+    nlist, coord, rcut: float, ruct_smth: float, radial_only: bool = False
+):
     """Make smooth environment matrix."""
     bsz, natoms, nnei = nlist.shape
     coord = coord.view(bsz, -1, 3)
@@ -35,7 +37,14 @@ def _make_env_mat(nlist, coord, rcut: float, ruct_smth: float, radial_only: bool
 
 
 def prod_env_mat(
-    extended_coord, nlist, atype, mean, stddev, rcut: float, rcut_smth: float, radial_only: bool=False
+    extended_coord,
+    nlist,
+    atype,
+    mean,
+    stddev,
+    rcut: float,
+    rcut_smth: float,
+    radial_only: bool = False,
 ):
     """Generate smooth environment matrix from atom coordinates and other context.
 
diff --git a/deepmd/pt/model/descriptor/se_r.py b/deepmd/pt/model/descriptor/se_r.py
index 0ddbfd5c63..4ccb6f8842 100644
--- a/deepmd/pt/model/descriptor/se_r.py
+++ b/deepmd/pt/model/descriptor/se_r.py
@@ -18,9 +18,6 @@
     EmbeddingNet,
     NetworkCollection,
 )
-from deepmd.pt.model.network.network import (
-    TypeFilter,
-)
 from deepmd.pt.utils import (
     env,
 )
@@ -89,7 +86,6 @@ def __init__(
         self.filter_layers_old = None
         self.filter_layers = None
 
-        
         filter_layers = NetworkCollection(
             ndim=1, ntypes=len(sel), network_type="embedding_network"
         )
diff --git a/deepmd/pt/utils/env_mat_stat.py b/deepmd/pt/utils/env_mat_stat.py
index 7f63f0a99e..3af03bda97 100644
--- a/deepmd/pt/utils/env_mat_stat.py
+++ b/deepmd/pt/utils/env_mat_stat.py
@@ -68,7 +68,9 @@ class EnvMatStatSe(EnvMatStat):
     def __init__(self, descriptor: "DescriptorBlock"):
         super().__init__()
         self.descriptor = descriptor
-        self.last_dim = self.descriptor.ndescrpt// self.descriptor.nnei # se_r=1, se_a=4
+        self.last_dim = (
+            self.descriptor.ndescrpt // self.descriptor.nnei
+        )  # se_r=1, se_a=4
 
     def iter(
         self, data: List[Dict[str, torch.Tensor]]
@@ -132,7 +134,9 @@ def iter(
             # reshape to nframes * nloc at the atom level,
             # so nframes/mixed_type do not matter
             env_mat = env_mat.view(
-                coord.shape[0] * coord.shape[1], self.descriptor.get_nsel(), self.last_dim
+                coord.shape[0] * coord.shape[1],
+                self.descriptor.get_nsel(),
+                self.last_dim,
             )
             atype = atype.view(coord.shape[0] * coord.shape[1])
             # (1, nloc) eq (ntypes, 1), so broadcast is possible
@@ -179,7 +183,7 @@ def __call__(self):
 
         all_davg = []
         all_dstd = []
-        
+
         for type_i in range(self.descriptor.get_ntypes()):
             if self.last_dim == 4:
                 davgunit = [[avgs[f"r_{type_i}"], 0, 0, 0]]
@@ -205,4 +209,4 @@ def __call__(self):
 
         mean = np.stack(all_davg)
         stddev = np.stack(all_dstd)
-        return mean, stddev
\ No newline at end of file
+        return mean, stddev