remove old code cuz merge

deepmodeling · Nov 28, 2023 · 0439995 · 0439995
1 parent 9fc9a67
commit 0439995
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Showing 5 changed files with 3 additions and 78 deletions.
diff --git a/deepmd/descriptor/se_a.py b/deepmd/descriptor/se_a.py
@@ -444,9 +444,6 @@ def merge_input_stats(self, stat_dict):
             self.davg = np.array(all_davg)
         self.dstd = np.array(all_dstd)
 
-        self.t_avg = paddle.to_tensor(self.davg, dtype=GLOBAL_NP_FLOAT_PRECISION)
-        self.t_std = paddle.to_tensor(self.dstd, dtype=GLOBAL_NP_FLOAT_PRECISION)
-
     def enable_compression(
         self,
         min_nbor_dist: float,

diff --git a/deepmd/fit/ener.py b/deepmd/fit/ener.py
@@ -191,71 +191,6 @@ def __init__(
             self.aparam_std = None
             self.aparam_inv_std = None
 
-        emenets = []
-        for type_i in range(self.ntypes):
-            layers = []
-            for ii in range(0, len(self.n_neuron)):
-                if ii >= 1 and self.n_neuron[ii] == self.n_neuron[ii - 1]:
-                    layers.append(
-                        OneLayer(
-                            self.n_neuron[ii - 1],
-                            self.n_neuron[ii],
-                            name="layer_" + str(ii) + "_type_" + str(type_i),
-                            seed=self.seed,
-                            use_timestep=self.resnet_dt,
-                            activation_fn=self.fitting_activation_fn,
-                            precision=self.fitting_precision,
-                            trainable=self.trainable[ii],
-                        )
-                    )
-                else:
-                    layers.append(
-                        OneLayer(
-                            self.dim_descrpt + self.numb_fparam + self.numb_aparam,
-                            self.n_neuron[ii],
-                            name="layer_" + str(ii) + "_type_" + str(type_i),
-                            seed=self.seed,
-                            activation_fn=self.fitting_activation_fn,
-                            precision=self.fitting_precision,
-                            trainable=self.trainable[ii],
-                        )
-                    )
-            layers.append(
-                OneLayer(
-                    self.n_neuron[-1],
-                    1,
-                    name="final_layer_type_" + str(type_i),
-                    seed=self.seed,
-                    activation_fn=None,
-                    precision=self.fitting_precision,
-                    trainable=self.trainable[ii],
-                )
-            )
-
-            emenets.append(paddle.nn.LayerList(layers))
-        self.ElementNets = paddle.nn.LayerList(emenets)
-
-        self.t_dfparam = paddle.to_tensor(self.numb_fparam, dtype="int32")
-        self.t_daparam = paddle.to_tensor(self.numb_aparam, dtype="int32")
-
-        # stat fparam
-        if self.numb_fparam > 0:
-            self.t_fparam_avg = paddle.to_tensor(
-                np.zeros([1, self.numb_fparam]), dtype=GLOBAL_PD_FLOAT_PRECISION
-            )
-            self.t_fparam_istd = paddle.to_tensor(
-                np.ones([1, self.numb_fparam]), dtype=GLOBAL_PD_FLOAT_PRECISION
-            )
-
-        # stat aparam
-        if self.numb_aparam > 0:
-            self.t_aparam_avg = paddle.to_tensor(
-                np.zeros([1, self.numb_aparam]), dtype=GLOBAL_PD_FLOAT_PRECISION
-            )
-            self.t_aparam_istd = paddle.to_tensor(
-                np.ones([1, self.numb_aparam]), dtype=GLOBAL_PD_FLOAT_PRECISION
-            )
-
         self.fitting_net_variables = None
         self.mixed_prec = None
         self.layer_name = layer_name

diff --git a/deepmd/infer/deep_eval.py b/deepmd/infer/deep_eval.py
@@ -220,10 +220,10 @@ def _get_value(self, tensor_name: str, attr_name: Optional[str] = None):
             if tensor_name in name:
                 value = tensor.numpy()[0] if tensor.shape == [1] else tensor.numpy()
         if attr_name:
-            setattr(self, attr_name, value)
-            return value
+            setattr(self, attr_name, tensor)
+            return tensor
         else:
-            return value
+            return tensor
 
     @staticmethod
     def _load_graph(

diff --git a/deepmd/model/ener.py b/deepmd/model/ener.py
@@ -66,7 +66,6 @@ def __init__(
         # super(EnerModel, self).__init__(name_scope="EnerModel")
         """Constructor."""
         # descriptor
-        super(EnerModel, self).__init__(name_scope="EnerModel")
         self.descrpt = descrpt
         self.rcut = self.descrpt.get_rcut()
         self.ntypes = self.descrpt.get_ntypes()
@@ -93,10 +92,6 @@ def __init__(
         else:
             self.srtab = None
 
-        self.t_tmap = " ".join(self.type_map)
-        self.t_mt = self.model_type
-        self.t_ver = MODEL_VERSION
-
         # self.type_map = " ".join(self.type_map)
         self.t_tmap = " ".join(self.type_map)
         self.t_mt = self.model_type

diff --git a/deepmd/train/trainer.py b/deepmd/train/trainer.py
@@ -4,9 +4,7 @@
 import os
 import platform
 import shutil
-import sys
 import time
-from collections import defaultdict
 from typing import Dict
 from typing import List