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

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deepmd/pt/infer/deep_eval.py

@@ -12,8 +12,8 @@
 
 import numpy as np
 import torch
-from deepmd.infer.deep_pot import DeepPot as DeepPotBase
 
+from deepmd.infer.deep_pot import DeepPot as DeepPotBase
 from deepmd.pt.model.model import (
     get_model,
 )

deepmd/pt/infer/inference.py

@@ -11,14 +11,14 @@
 
 import numpy as np
 import torch
-from deepmd.common import (
-    expand_sys_str,
-)
 from torch.utils.data import (
     DataLoader,
     RandomSampler,
 )
 
+from deepmd.common import (
+    expand_sys_str,
+)
 from deepmd.pt.loss import (
     DenoiseLoss,
     EnergyStdLoss,

deepmd/pt/model/descriptor/se_a.py

@@ -29,7 +29,6 @@
     from torch.jit import Final
 
 from deepmd.model_format import EnvMat as DPEnvMat
-
 from deepmd.pt.model.network.mlp import (
     EmbeddingNet,
     NetworkCollection,

deepmd/pt/model/model/atomic_model.py

@@ -10,10 +10,10 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
 )
-
 from deepmd.pt.model.task import (
     Fitting,
 )

deepmd/pt/model/model/dp_atomic_model.py

@@ -6,10 +6,10 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
 )
-
 from deepmd.pt.model.descriptor.descriptor import (
     Descriptor,
 )

deepmd/pt/model/model/make_model.py

@@ -5,10 +5,10 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     ModelOutputDef,
 )
-
 from deepmd.pt.model.model.transform_output import (
     communicate_extended_output,
     fit_output_to_model_output,

deepmd/pt/model/model/transform_output.py

@@ -6,6 +6,7 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
     ModelOutputDef,

deepmd/pt/model/network/mlp.py

@@ -24,7 +24,6 @@
     make_fitting_network,
     make_multilayer_network,
 )
-
 from deepmd.pt.utils.env import (
     DEFAULT_PRECISION,
     PRECISION_DICT,

deepmd/pt/model/task/denoise.py

@@ -4,12 +4,12 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
     OutputVariableDef,
     fitting_check_output,
 )
-
 from deepmd.pt.model.network.network import (
     MaskLMHead,
     NonLinearHead,

deepmd/pt/model/task/ener.py

@@ -6,12 +6,12 @@
 )
 
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
     OutputVariableDef,
     fitting_check_output,
 )
-
 from deepmd.pt.model.network.network import (
     ResidualDeep,
 )

deepmd/pt/model/task/fitting.py

@@ -6,10 +6,10 @@
 
 import numpy as np
 import torch
+
 from deepmd.model_format import (
     FittingOutputDef,
 )
-
 from deepmd.pt.model.task.task import (
     TaskBaseMethod,
 )

deepmd/pt/utils/auto_batch_size.py

@@ -1,5 +1,6 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import torch
+
 from deepmd.utils.batch_size import AutoBatchSize as AutoBatchSizeBase
 
 

deepmd/pt/utils/dataloader.py

@@ -17,10 +17,6 @@
 import torch
 import torch.distributed as dist
 import torch.multiprocessing
-from deepmd.utils.data_system import (
-    prob_sys_size_ext,
-    process_sys_probs,
-)
 from torch.utils.data import (
     DataLoader,
     Dataset,
@@ -39,6 +35,10 @@
 from deepmd.pt.utils.dataset import (
     DeepmdDataSetForLoader,
 )
+from deepmd.utils.data_system import (
+    prob_sys_size_ext,
+    process_sys_probs,
+)
 
 torch.multiprocessing.set_sharing_strategy("file_system")
 

source/pt/lmp/pair_deepmd.cpp

@@ -44,18 +44,24 @@ static bool is_key(const string &input) {
   return false;
 }
 
-static void ana_st(double &max, double &min, double &sum,
-                   const vector<double> &vec, const int &nloc) {
-  if (nloc == 0)
+static void ana_st(double &max,
+                   double &min,
+                   double &sum,
+                   const vector<double> &vec,
+                   const int &nloc) {
+  if (nloc == 0) {
     return;
+  }
   max = vec[0];
   min = vec[0];
   sum = vec[0];
   for (unsigned ii = 1; ii < nloc; ++ii) {
-    if (vec[ii] > max)
+    if (vec[ii] > max) {
       max = vec[ii];
-    if (vec[ii] < min)
+    }
+    if (vec[ii] < min) {
       min = vec[ii];
+    }
     sum += vec[ii];
   }
 }
@@ -129,13 +135,15 @@ void PairDeepMD::settings(int narg, char **arg) {
                  "Illegal pair_style command\nwrong number of parameters\n");
     }
     if (string(arg[iarg]) == string("out_freq")) {
-      if (iarg + 1 >= narg)
+      if (iarg + 1 >= narg) {
         error->all(FLERR, "Illegal out_freq, not provided");
+      }
       out_freq = atoi(arg[iarg + 1]);
       iarg += 2;
     } else if (string(arg[iarg]) == string("out_file")) {
-      if (iarg + 1 >= narg)
+      if (iarg + 1 >= narg) {
         error->all(FLERR, "Illegal out_file, not provided");
+      }
       out_file = string(arg[iarg + 1]);
       iarg += 2;
     } else if (string(arg[iarg]) == string("fparam")) {
@@ -184,8 +192,9 @@ void PairDeepMD::settings(int narg, char **arg) {
     else if (string(arg[iarg]) == string("fparam_from_compute")) {
       for (int ii = 0; ii < 1; ++ii) {
         if (iarg + 1 + ii >= narg || is_key(arg[iarg + 1 + ii])) {
-          error->all(FLERR, "invalid fparam_from_compute key: should be "
-                            "fparam_from_compute compute_id(str)");
+          error->all(FLERR,
+                     "invalid fparam_from_compute key: should be "
+                     "fparam_from_compute compute_id(str)");
         }
       }
       do_compute = true;
@@ -219,8 +228,9 @@ void PairDeepMD::settings(int narg, char **arg) {
     }
   }
 
-  if (out_freq < 0)
+  if (out_freq < 0) {
     error->all(FLERR, "Illegal out_freq, should be >= 0");
+  }
   if (do_ttm && aparam.size() > 0) {
     error->all(FLERR, "aparam and ttm should NOT be set simultaneously");
   }
@@ -282,12 +292,12 @@ void PairDeepMD::compute(int eflag, int vflag) {
   }
 
   // get box
-  dbox[0] = domain->h[0]; // xx
-  dbox[4] = domain->h[1]; // yy
-  dbox[8] = domain->h[2]; // zz
-  dbox[7] = domain->h[3]; // zy
-  dbox[6] = domain->h[4]; // zx
-  dbox[3] = domain->h[5]; // yx
+  dbox[0] = domain->h[0];  // xx
+  dbox[4] = domain->h[1];  // yy
+  dbox[8] = domain->h[2];  // zz
+  dbox[7] = domain->h[3];  // zy
+  dbox[6] = domain->h[4];  // zx
+  dbox[3] = domain->h[5];  // yx
 
   // int ago = numb_models > 1 ? 0 : neighbor->ago;
   int ago = neighbor->ago;
@@ -392,8 +402,9 @@ void PairDeepMD::compute(int eflag, int vflag) {
         }
         MPI_Gather(&nlocal, 1, MPI_INT, counts, 1, MPI_INT, 0, world);
         displacements[0] = 0;
-        for (int ii = 0; ii < nprocs - 1; ii++)
+        for (int ii = 0; ii < nprocs - 1; ii++) {
           displacements[ii + 1] = displacements[ii] + counts[ii];
+        }
         MPI_Gatherv(tagsend, nlocal, MPI_LMP_TAGINT, tagrecv, counts,
                     displacements, MPI_LMP_TAGINT, 0, world);
         MPI_Gatherv(stdfsend, nlocal, MPI_DOUBLE, stdfrecv, counts,
@@ -440,8 +451,9 @@ void PairDeepMD::compute(int eflag, int vflag) {
 void PairDeepMD::coeff(int narg, char **arg) {
   // if (narg < 4 || narg > 5) error->all(FLERR, "Incorrect args for pair
   // coefficients");
-  if (!allocated)
+  if (!allocated) {
     allocate();
+  }
 
   int ilo, ihi, jlo, jhi;
   utils::bounds(FLERR, arg[0], 1, atom->ntypes, ilo, ihi, error);
@@ -458,8 +470,9 @@ void PairDeepMD::coeff(int narg, char **arg) {
     }
   }
 
-  if (count == 0)
+  if (count == 0) {
     error->all(FLERR, "Incorrect args for pair coefficients");
+  }
 }
 
 /* ---------------------------------------------------------------------- */

source/pt/lmp/pair_deepmd.h

@@ -16,7 +16,7 @@ namespace deepmd_compat = deepmd;
 namespace LAMMPS_NS {
 
 class PairDeepMD : public Pair {
-public:
+ public:
   PairDeepMD(class LAMMPS *);
   ~PairDeepMD() override;
   void compute(int, int) override;
@@ -55,18 +55,18 @@ class PairDeepMD : public Pair {
   // std::vector<std::string> get_file_content(
   //     const std::vector<std::string> &models);
 
-protected:
+ protected:
   virtual void allocate();
   double **scale;
 
-private:
+ private:
   deepmd_compat::DeepPot deep_pot;
   deepmd_compat::DeepPotModelDevi deep_pot_model_devi;
   unsigned numb_models;
   double cutoff;
   int numb_types;
   int numb_types_spin;
-  std::vector<std::vector<double>> all_force;
+  std::vector<std::vector<double> > all_force;
   std::ofstream fp;
   int out_freq;
   std::string out_file;
@@ -84,7 +84,7 @@ class PairDeepMD : public Pair {
   int extend_inum;
   std::vector<int> extend_ilist;
   std::vector<int> extend_numneigh;
-  std::vector<std::vector<int>> extend_neigh;
+  std::vector<std::vector<int> > extend_neigh;
   std::vector<int *> extend_firstneigh;
   std::vector<double> extend_dcoord;
   std::vector<int> extend_dtype;
@@ -112,7 +112,7 @@ class PairDeepMD : public Pair {
   std::vector<int> type_idx_map;
 };
 
-} // namespace LAMMPS_NS
+}  // namespace LAMMPS_NS
 
 #endif
 #endif

source/tests/pt/test_descriptor.py

@@ -10,13 +10,6 @@
 
 import json
 
-from deepmd.tf.common import (
-    expand_sys_str,
-)
-from deepmd.tf.env import (
-    op_module,
-)
-
 from deepmd.pt.model.descriptor import (
     prod_env_mat_se_a,
 )
@@ -32,6 +25,12 @@
     GLOBAL_PT_FLOAT_PRECISION,
     TEST_CONFIG,
 )
+from deepmd.tf.common import (
+    expand_sys_str,
+)
+from deepmd.tf.env import (
+    op_module,
+)
 
 CUR_DIR = os.path.dirname(__file__)
 

source/tests/pt/test_embedding_net.py

@@ -10,11 +10,6 @@
 
 tf.disable_eager_execution()
 
-from deepmd.tf.common import (
-    expand_sys_str,
-)
-from deepmd.tf.descriptor import DescrptSeA as DescrptSeA_tf
-
 from deepmd.pt.model.descriptor import (
     DescrptSeA,
 )
@@ -29,6 +24,10 @@
     GLOBAL_NP_FLOAT_PRECISION,
     TEST_CONFIG,
 )
+from deepmd.tf.common import (
+    expand_sys_str,
+)
+from deepmd.tf.descriptor import DescrptSeA as DescrptSeA_tf
 
 CUR_DIR = os.path.dirname(__file__)
 

source/tests/pt/test_fitting_net.py

@@ -8,16 +8,15 @@
 
 tf.disable_eager_execution()
 
-from deepmd.tf.fit.ener import (
-    EnerFitting,
-)
-
 from deepmd.pt.model.task import (
     EnergyFittingNet,
 )
 from deepmd.pt.utils.env import (
     GLOBAL_NP_FLOAT_PRECISION,
 )
+from deepmd.tf.fit.ener import (
+    EnerFitting,
+)
 
 
 class FakeDescriptor: