diff --git a/deepmd/entrypoints/test.py b/deepmd/entrypoints/test.py
index 5f0225c0cd..5f4e758f0b 100644
--- a/deepmd/entrypoints/test.py
+++ b/deepmd/entrypoints/test.py
@@ -67,7 +67,6 @@ def test(
     model: str,
     system: str,
     datafile: str,
-    set_prefix: str,
     numb_test: int,
     rand_seed: Optional[int],
     shuffle_test: bool,
@@ -86,8 +85,6 @@ def test(
         system directory
     datafile : str
         the path to the list of systems to test
-    set_prefix : str
-        string prefix of set
     numb_test : int
         munber of tests to do. 0 means all data.
     rand_seed : Optional[int]
@@ -137,7 +134,7 @@ def test(
         tmap = dp.get_type_map() if isinstance(dp, DeepPot) else None
         data = DeepmdData(
             system,
-            set_prefix,
+            set_prefix="set",
             shuffle_test=shuffle_test,
             type_map=tmap,
             sort_atoms=False,
diff --git a/deepmd/infer/model_devi.py b/deepmd/infer/model_devi.py
index a37dfd34c5..477acf0282 100644
--- a/deepmd/infer/model_devi.py
+++ b/deepmd/infer/model_devi.py
@@ -350,7 +350,6 @@ def make_model_devi(
     *,
     models: list,
     system: str,
-    set_prefix: str,
     output: str,
     frequency: int,
     real_error: bool = False,
@@ -367,8 +366,6 @@ def make_model_devi(
         A list of paths of models to use for making model deviation
     system : str
         The path of system to make model deviation calculation
-    set_prefix : str
-        The set prefix of the system
     output : str
         The output file for model deviation results
     frequency : int
@@ -410,7 +407,7 @@ def make_model_devi(
     for system in all_sys:
         # create data-system
         dp_data = DeepmdData(
-            system, set_prefix, shuffle_test=False, type_map=tmap, sort_atoms=False
+            system, "set", shuffle_test=False, type_map=tmap, sort_atoms=False
         )
         if first_dp.get_dim_fparam() > 0:
             dp_data.add(
diff --git a/deepmd/main.py b/deepmd/main.py
index 9d023221a6..e9e7b0fcad 100644
--- a/deepmd/main.py
+++ b/deepmd/main.py
@@ -9,6 +9,7 @@
 import logging
 import os
 import textwrap
+import warnings
 from collections import (
     defaultdict,
 )
@@ -69,6 +70,24 @@ def __call__(self, parser, namespace, values, option_string=None):
         setattr(namespace, self.dest, BACKEND_TABLE[values])
 
 
+class DeprecateAction(argparse.Action):
+    # See https://stackoverflow.com/a/69052677/9567349 by Ibolit under CC BY-SA 4.0
+    def __init__(self, *args, **kwargs):
+        self.call_count = 0
+        if "help" in kwargs:
+            kwargs["help"] = f'[DEPRECATED] {kwargs["help"]}'
+        super().__init__(*args, **kwargs)
+
+    def __call__(self, parser, namespace, values, option_string=None):
+        if self.call_count == 0:
+            warnings.warn(
+                f"The option `{option_string}` is deprecated. It will be ignored.",
+                FutureWarning,
+            )
+            delattr(namespace, self.dest)
+        self.call_count += 1
+
+
 def main_parser() -> argparse.ArgumentParser:
     """DeePMD-Kit commandline options argument parser.
 
@@ -355,9 +374,8 @@ def main_parser() -> argparse.ArgumentParser:
     parser_tst.add_argument(
         "-S",
         "--set-prefix",
-        default="set",
-        type=str,
-        help="(Supported backend: TensorFlow) The set prefix",
+        action=DeprecateAction,
+        help="Deprecated argument.",
     )
     parser_tst.add_argument(
         "-n",
@@ -528,7 +546,7 @@ def main_parser() -> argparse.ArgumentParser:
         help="The system directory. Recursively detect systems in this directory.",
     )
     parser_model_devi.add_argument(
-        "-S", "--set-prefix", default="set", type=str, help="The set prefix"
+        "-S", "--set-prefix", action=DeprecateAction, help="Deprecated argument."
     )
     parser_model_devi.add_argument(
         "-o",
diff --git a/deepmd/tf/nvnmd/data/data.py b/deepmd/tf/nvnmd/data/data.py
index 7f2c9ef5e9..55e7c51bc7 100644
--- a/deepmd/tf/nvnmd/data/data.py
+++ b/deepmd/tf/nvnmd/data/data.py
@@ -319,7 +319,7 @@
         "disp_training": True,
         "time_training": True,
         "profiling": False,
-        "training_data": {"systems": "dataset", "set_prefix": "set", "batch_size": 1},
+        "training_data": {"systems": "dataset", "batch_size": 1},
     },
 }
 
@@ -385,7 +385,7 @@
         "disp_training": True,
         "time_training": True,
         "profiling": False,
-        "training_data": {"systems": "dataset", "set_prefix": "set", "batch_size": 1},
+        "training_data": {"systems": "dataset", "batch_size": 1},
     },
 }
 
diff --git a/deepmd/utils/argcheck.py b/deepmd/utils/argcheck.py
index c817536b92..f6dbada56c 100644
--- a/deepmd/utils/argcheck.py
+++ b/deepmd/utils/argcheck.py
@@ -1,6 +1,7 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import json
 import logging
+import warnings
 from typing import (
     Callable,
     List,
@@ -54,6 +55,24 @@ def make_link(content, ref_key):
     )
 
 
+def deprecate_argument_extra_check(key: str) -> Callable[[dict], bool]:
+    """Generate an extra check to deprecate an argument in sub fields.
+
+    Parameters
+    ----------
+    key : str
+        The name of the deprecated argument.
+    """
+
+    def deprecate_something(data: Optional[dict]):
+        if data is not None and key in data:
+            warnings.warn(f"{key} has been removed and takes no effect.", FutureWarning)
+            data.pop(key)
+        return True
+
+    return deprecate_something
+
+
 def type_embedding_args():
     doc_neuron = "Number of neurons in each hidden layers of the embedding net. When two layers are of the same size or one layer is twice as large as the previous layer, a skip connection is built."
     doc_resnet_dt = 'Whether to use a "Timestep" in the skip connection'
@@ -1951,7 +1970,6 @@ def training_data_args():  # ! added by Ziyao: new specification style for data
         "This key can be provided with a list that specifies the systems, or be provided with a string "
         "by which the prefix of all systems are given and the list of the systems is automatically generated."
     )
-    doc_set_prefix = f"The prefix of the sets in the {link_sys}."
     doc_batch_size = f'This key can be \n\n\
 - list: the length of which is the same as the {link_sys}. The batch size of each system is given by the elements of the list.\n\n\
 - int: all {link_sys} use the same batch size.\n\n\
@@ -1973,7 +1991,6 @@ def training_data_args():  # ! added by Ziyao: new specification style for data
         Argument(
             "systems", [List[str], str], optional=False, default=".", doc=doc_systems
         ),
-        Argument("set_prefix", str, optional=True, default="set", doc=doc_set_prefix),
         Argument(
             "batch_size",
             [List[int], int, str],
@@ -2009,6 +2026,7 @@ def training_data_args():  # ! added by Ziyao: new specification style for data
         sub_fields=args,
         sub_variants=[],
         doc=doc_training_data,
+        extra_check=deprecate_argument_extra_check("set_prefix"),
     )
 
 
@@ -2019,7 +2037,6 @@ def validation_data_args():  # ! added by Ziyao: new specification style for dat
         "This key can be provided with a list that specifies the systems, or be provided with a string "
         "by which the prefix of all systems are given and the list of the systems is automatically generated."
     )
-    doc_set_prefix = f"The prefix of the sets in the {link_sys}."
     doc_batch_size = f'This key can be \n\n\
 - list: the length of which is the same as the {link_sys}. The batch size of each system is given by the elements of the list.\n\n\
 - int: all {link_sys} use the same batch size.\n\n\
@@ -2040,7 +2057,6 @@ def validation_data_args():  # ! added by Ziyao: new specification style for dat
         Argument(
             "systems", [List[str], str], optional=False, default=".", doc=doc_systems
         ),
-        Argument("set_prefix", str, optional=True, default="set", doc=doc_set_prefix),
         Argument(
             "batch_size",
             [List[int], int, str],
@@ -2090,6 +2106,7 @@ def validation_data_args():  # ! added by Ziyao: new specification style for dat
         sub_fields=args,
         sub_variants=[],
         doc=doc_validation_data,
+        extra_check=deprecate_argument_extra_check("set_prefix"),
     )
 
 
diff --git a/deepmd/utils/compat.py b/deepmd/utils/compat.py
index 5f9c14e6d8..11f5e639dc 100644
--- a/deepmd/utils/compat.py
+++ b/deepmd/utils/compat.py
@@ -263,7 +263,8 @@ def _jcopy(src: Dict[str, Any], dst: Dict[str, Any], keys: Sequence[str]):
         list of keys to copy
     """
     for k in keys:
-        dst[k] = src[k]
+        if k in src:
+            dst[k] = src[k]
 
 
 def remove_decay_rate(jdata: Dict[str, Any]):
diff --git a/doc/nvnmd/nvnmd.md b/doc/nvnmd/nvnmd.md
index 67cfb5e22d..c415b275ec 100644
--- a/doc/nvnmd/nvnmd.md
+++ b/doc/nvnmd/nvnmd.md
@@ -153,7 +153,6 @@ The "training" section is defined as
   "save_freq": 10000,
   "training_data": {
     "systems": ["system1_path", "system2_path", "..."],
-    "set_prefix": "set",
     "batch_size": ["batch_size_of_system1", "batch_size_of_system2", "..."]
   }
 }
@@ -171,7 +170,6 @@ where items are defined as:
 | save_ckpt  | path prefix of check point files                    | a string           |
 | save_freq  | save frequency                                      | a positive integer |
 | systems    | a list of data directory which contains the dataset | string list        |
-| set_prefix | the prefix of dataset                               | a string           |
 | batch_size | a list of batch size of corresponding dataset       | a integer list     |
 
 ## Training
diff --git a/doc/train/tensorboard.md b/doc/train/tensorboard.md
index 7b41c004ce..32ecdd0ab2 100644
--- a/doc/train/tensorboard.md
+++ b/doc/train/tensorboard.md
@@ -28,7 +28,6 @@ directory by modifying the input script, setting {ref}`tensorboard <training/ten
 ```json
     "training" : {
 	"systems":	["../data/"],
-	"set_prefix":	"set",
 	"stop_batch":	1000000,
 	"batch_size":	1,
 
diff --git a/examples/dos/train/input.json b/examples/dos/train/input.json
index 327a9c3aff..56466fcb60 100644
--- a/examples/dos/train/input.json
+++ b/examples/dos/train/input.json
@@ -66,7 +66,6 @@
       "systems": [
         "../data/heat-221/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     }
   },
diff --git a/examples/dos/train/input_torch.json b/examples/dos/train/input_torch.json
index 99bc106e7d..239e31cc1e 100644
--- a/examples/dos/train/input_torch.json
+++ b/examples/dos/train/input_torch.json
@@ -67,7 +67,6 @@
         "../data/heat-221-reformat/atomic_system/",
         "../data/heat-221-reformat/global_system/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     }
   },
diff --git a/examples/fparam/train/input.json b/examples/fparam/train/input.json
index 1bb9b55f95..42ecba948f 100644
--- a/examples/fparam/train/input.json
+++ b/examples/fparam/train/input.json
@@ -58,7 +58,6 @@
         "../data/e3000_i2000/",
         "../data/e8000_i2000/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     },
     "stop_batch": 1000000,
diff --git a/examples/fparam/train/input_aparam.json b/examples/fparam/train/input_aparam.json
index 93a34f7305..32420068e6 100644
--- a/examples/fparam/train/input_aparam.json
+++ b/examples/fparam/train/input_aparam.json
@@ -55,7 +55,6 @@
         "../data/e3000_i2000/",
         "../data/e8000_i2000/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     },
     "stop_batch": 1000000,
diff --git a/examples/nvnmd/train/train_cnn.json b/examples/nvnmd/train/train_cnn.json
index 1865106909..52bfd47dfd 100644
--- a/examples/nvnmd/train/train_cnn.json
+++ b/examples/nvnmd/train/train_cnn.json
@@ -40,7 +40,6 @@
       "systems": [
         "../data"
       ],
-      "set_prefix": "set",
       "batch_size": [
         1
       ]
diff --git a/examples/nvnmd/train/train_qnn.json b/examples/nvnmd/train/train_qnn.json
index 72b299f70d..8445c4d07a 100644
--- a/examples/nvnmd/train/train_qnn.json
+++ b/examples/nvnmd/train/train_qnn.json
@@ -40,7 +40,6 @@
       "systems": [
         "../data"
       ],
-      "set_prefix": "set",
       "batch_size": [
         1
       ]
diff --git a/examples/water/dplr/train/dw.json b/examples/water/dplr/train/dw.json
index 038e07abef..169cc43b07 100644
--- a/examples/water/dplr/train/dw.json
+++ b/examples/water/dplr/train/dw.json
@@ -65,7 +65,6 @@
         "data"
       ],
       "batch_size": "auto",
-      "set_prefix": "set",
       "_comment8": "that's all"
     },
 
diff --git a/source/lmp/tests/lrmodel.pbtxt b/source/lmp/tests/lrmodel.pbtxt
index 6cdf1f9d79..026b30da33 100644
--- a/source/lmp/tests/lrmodel.pbtxt
+++ b/source/lmp/tests/lrmodel.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"hybrid\",\"list\":[{\"type\":\"se_e2_a\",\"sel\":[20,40],\"rcut_smth\":0.5,\"rcut\":4.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":8,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false}]},\"fitting_net\":{\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"modifier\":{\"type\":\"dipole_charge\",\"model_name\":\"lrdipole.pb\",\"model_charge_map\":[-8],\"sys_charge_map\":[6,1],\"ewald_h\":1.0,\"ewald_beta\":0.4},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.012\",\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.016\",\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.020\",\"../../4-deep-wannier/data/dpgen.merged/init/00.liq/state.0300.1.00e00.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/00.liq/state.0400.1.00e04.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/01.liq/state.0300.1.00e00.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/01.liq/state.0400.1.00e04.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/iter.000000/02.fp/data.000\",\"../../4-deep-wannier/data/dpgen.merged/iter.000001/02.fp/data.001\",\"../../4-deep-wannier/data/dpgen.merged/iter.000002/02.fp/data.002\",\"../../4-deep-wannier/data/dpgen.merged/iter.000005/02.fp/data.001\",\"../../4-deep-wannier/data/dpgen.merged/iter.000008/02.fp/data.004\",\"../../4-deep-wannier/data/dpgen.merged/iter.000009/02.fp/data.005\",\"../../4-deep-wannier/data/dpgen.merged/iter.000010/02.fp/data.006\"],\"set_prefix\":\"set\",\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":1,\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":1,\"save_freq\":1,\"validation_data\":null,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"hybrid\",\"list\":[{\"type\":\"se_e2_a\",\"sel\":[20,40],\"rcut_smth\":0.5,\"rcut\":4.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":8,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false}]},\"fitting_net\":{\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"modifier\":{\"type\":\"dipole_charge\",\"model_name\":\"lrdipole.pb\",\"model_charge_map\":[-8],\"sys_charge_map\":[6,1],\"ewald_h\":1.0,\"ewald_beta\":0.4},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.012\",\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.016\",\"../../4-deep-wannier/data/dpgen.lowd.merged/iter.000016/02.fp/data.020\",\"../../4-deep-wannier/data/dpgen.merged/init/00.liq/state.0300.1.00e00.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/00.liq/state.0400.1.00e04.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/01.liq/state.0300.1.00e00.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/init/01.liq/state.0400.1.00e04.00/vasp/data\",\"../../4-deep-wannier/data/dpgen.merged/iter.000000/02.fp/data.000\",\"../../4-deep-wannier/data/dpgen.merged/iter.000001/02.fp/data.001\",\"../../4-deep-wannier/data/dpgen.merged/iter.000002/02.fp/data.002\",\"../../4-deep-wannier/data/dpgen.merged/iter.000005/02.fp/data.001\",\"../../4-deep-wannier/data/dpgen.merged/iter.000008/02.fp/data.004\",\"../../4-deep-wannier/data/dpgen.merged/iter.000009/02.fp/data.005\",\"../../4-deep-wannier/data/dpgen.merged/iter.000010/02.fp/data.006\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":1,\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":1,\"save_freq\":1,\"validation_data\":null,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/common/test_argument_parser.py b/source/tests/common/test_argument_parser.py
index 0b4f053aed..f63dc11a57 100644
--- a/source/tests/common/test_argument_parser.py
+++ b/source/tests/common/test_argument_parser.py
@@ -317,7 +317,6 @@ def test_parser_test(self):
         ARGS = {
             "--model": {"type": str, "value": "MODEL.PB"},
             "--system": {"type": str, "value": "SYSTEM_DIR"},
-            "--set-prefix": {"type": str, "value": "SET_PREFIX"},
             "--numb-test": {"type": int, "value": 1},
             "--rand-seed": {"type": (int, type(None)), "value": 12321},
             "--detail-file": {"type": (str, type(None)), "value": "TARGET.FILE"},
@@ -355,7 +354,6 @@ def test_parser_model_devi(self):
                 "expected": ["GRAPH.000.pb", "GRAPH.001.pb"],
             },
             "--system": {"type": str, "value": "SYSTEM_DIR"},
-            "--set-prefix": {"type": str, "value": "SET_PREFIX"},
             "--output": {"type": str, "value": "OUTFILE"},
             "--frequency": {"type": int, "value": 1},
         }
diff --git a/source/tests/infer/deepdos.pbtxt b/source/tests/infer/deepdos.pbtxt
index d923e1f8c4..79cb2474bc 100644
--- a/source/tests/infer/deepdos.pbtxt
+++ b/source/tests/infer/deepdos.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"Si\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[90],\"rcut_smth\":4.8,\"rcut\":5.0,\"neuron\":[5,10,20],\"resnet_dt\":false,\"axis_neuron\":2,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"type\":\"dos\",\"numb_dos\":250,\"ener_min\":-15.0,\"ener_max\":10.0,\"neuron\":[40,40,40],\"resnet_dt\":true,\"numb_fparam\":0,\"seed\":1,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"float64\",\"trainable\":true,\"rcond\":0.001},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"loss\":{\"type\":\"dos\",\"start_pref_dos\":0.0,\"limit_pref_dos\":0.0,\"start_pref_cdf\":0.0,\"limit_pref_cdf\":0.0,\"start_pref_ados\":1.0,\"limit_pref_ados\":1.0,\"start_pref_acdf\":0.0,\"limit_pref_acdf\":0.0},\"learning_rate\":{\"type\":\"exp\",\"start_lr\":0.001,\"stop_lr\":1e-08,\"scale_by_worker\":\"linear\",\"decay_steps\":5000},\"training\":{\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"training_data\":{\"systems\":[\"/data/home/djy4/work/dp-dos/set-train/111/size-80\",\"/data/home/djy4/work/dp-dos/set-train/111/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/211/cd-2000-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/211/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/221/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/222/heat-5-fermi\"],\"set_prefix\":\"set\",\"batch_size\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":50000,\"validation_data\":null,\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"Si\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[90],\"rcut_smth\":4.8,\"rcut\":5.0,\"neuron\":[5,10,20],\"resnet_dt\":false,\"axis_neuron\":2,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"type\":\"dos\",\"numb_dos\":250,\"ener_min\":-15.0,\"ener_max\":10.0,\"neuron\":[40,40,40],\"resnet_dt\":true,\"numb_fparam\":0,\"seed\":1,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"float64\",\"trainable\":true,\"rcond\":0.001},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"loss\":{\"type\":\"dos\",\"start_pref_dos\":0.0,\"limit_pref_dos\":0.0,\"start_pref_cdf\":0.0,\"limit_pref_cdf\":0.0,\"start_pref_ados\":1.0,\"limit_pref_ados\":1.0,\"start_pref_acdf\":0.0,\"limit_pref_acdf\":0.0},\"learning_rate\":{\"type\":\"exp\",\"start_lr\":0.001,\"stop_lr\":1e-08,\"scale_by_worker\":\"linear\",\"decay_steps\":5000},\"training\":{\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"training_data\":{\"systems\":[\"/data/home/djy4/work/dp-dos/set-train/111/size-80\",\"/data/home/djy4/work/dp-dos/set-train/111/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/211/cd-2000-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/211/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/221/heat-5-fermi\",\"/data/home/djy4/work/dp-dos/set-train/222/heat-5-fermi\"],\"batch_size\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":50000,\"validation_data\":null,\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/deepspin.pbtxt b/source/tests/infer/deepspin.pbtxt
index f7de29c435..8aedd4680e 100644
--- a/source/tests/infer/deepspin.pbtxt
+++ b/source/tests/infer/deepspin.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"Ni\",\"O\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[60,60],\"rcut_smth\":5.4,\"rcut\":5.6,\"neuron\":[1],\"resnet_dt\":false,\"axis_neuron\":1,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[1],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"spin\":{\"use_spin\":[true,false],\"virtual_len\":[0.4],\"spin_norm\":[1.2737]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":10000,\"start_lr\":0.001,\"stop_lr\":5.92e-06,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener_spin\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_fr\":1000,\"limit_pref_fr\":1.0,\"start_pref_fm\":10000,\"limit_pref_fm\":10.0,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../../data/data_train/\"],\"batch_size\":1,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../../data/data_valid/\"],\"batch_size\":1,\"numb_btch\":10,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":1,\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":1,\"save_freq\":1,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"Ni\",\"O\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[60,60],\"rcut_smth\":5.4,\"rcut\":5.6,\"neuron\":[1],\"resnet_dt\":false,\"axis_neuron\":1,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[1],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"spin\":{\"use_spin\":[true,false],\"virtual_len\":[0.4],\"spin_norm\":[1.2737]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":10000,\"start_lr\":0.001,\"stop_lr\":5.92e-06,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener_spin\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_fr\":1000,\"limit_pref_fr\":1.0,\"start_pref_fm\":10000,\"limit_pref_fm\":10.0,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../../data/data_train/\"],\"batch_size\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../../data/data_valid/\"],\"batch_size\":1,\"numb_btch\":10,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":1,\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":1,\"save_freq\":1,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/dp4mask.pbtxt b/source/tests/infer/dp4mask.pbtxt
index ea014d3c3f..8356f00aa3 100644
--- a/source/tests/infer/dp4mask.pbtxt
+++ b/source/tests/infer/dp4mask.pbtxt
@@ -14,7 +14,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"C\",\"ZN\"],\"descriptor\":{\"type\":\"se_a_mask\",\"sel\":[20,1],\"neuron\":[2,2,2,2],\"resnet_dt\":true,\"axis_neuron\":2,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"exclude_types\":[],\"precision\":\"default\",\"trainable\":true,\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"numb_aparam\":1,\"use_aparam_as_mask\":true,\"type\":\"ener\",\"numb_fparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":20000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.0,\"limit_pref_e\":0.0,\"start_pref_f\":0.0,\"limit_pref_f\":0.0,\"start_pref_pf\":1.0,\"limit_pref_pf\":1.0,\"start_pref_v\":0.0,\"limit_pref_v\":0.0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":\"../data4train_sample/\",\"batch_size\":4,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":\"../data4test_sample/\",\"batch_size\":4,\"numb_btch\":1,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10,\"disp_file\":\"loss.sample.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"./ckpt.dp4mask_sample/model.ckpt\",\"tensorboard\":true,\"tensorboard_log_dir\":\"log4tensorboard\",\"tensorboard_freq\":100,\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false}}"
+        string_val: "{\"model\":{\"type_map\":[\"C\",\"ZN\"],\"descriptor\":{\"type\":\"se_a_mask\",\"sel\":[20,1],\"neuron\":[2,2,2,2],\"resnet_dt\":true,\"axis_neuron\":2,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"exclude_types\":[],\"precision\":\"default\",\"trainable\":true,\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"numb_aparam\":1,\"use_aparam_as_mask\":true,\"type\":\"ener\",\"numb_fparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":20000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.0,\"limit_pref_e\":0.0,\"start_pref_f\":0.0,\"limit_pref_f\":0.0,\"start_pref_pf\":1.0,\"limit_pref_pf\":1.0,\"start_pref_v\":0.0,\"limit_pref_v\":0.0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":\"../data4train_sample/\",\"batch_size\":4,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":\"../data4test_sample/\",\"batch_size\":4,\"numb_btch\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10,\"disp_file\":\"loss.sample.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"./ckpt.dp4mask_sample/model.ckpt\",\"tensorboard\":true,\"tensorboard_log_dir\":\"log4tensorboard\",\"tensorboard_freq\":100,\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false}}"
       }
     }
   }
diff --git a/source/tests/infer/fparam_aparam.pbtxt b/source/tests/infer/fparam_aparam.pbtxt
index 8c2e884090..ab9cd71ffa 100644
--- a/source/tests/infer/fparam_aparam.pbtxt
+++ b/source/tests/infer/fparam_aparam.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"data_stat_nbatch\":1,\"type_map\":[\"O\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[60],\"rcut_smth\":1.8,\"rcut\":6.0,\"neuron\":[5,10,20],\"resnet_dt\":false,\"axis_neuron\":8,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[5,5,5],\"resnet_dt\":true,\"numb_fparam\":1,\"numb_aparam\":1,\"seed\":1,\"type\":\"ener\",\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"loss\":{\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"type\":\"ener\",\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"learning_rate\":{\"start_lr\":0.001,\"stop_lr\":3e-08,\"decay_steps\":5000,\"scale_by_worker\":\"linear\",\"type\":\"exp\"},\"training\":{\"training_data\":{\"systems\":[\"../data/e3000_i2000/\",\"../data/e8000_i2000/\"],\"set_prefix\":\"set\",\"batch_size\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"numb_steps\":1000,\"validation_data\":null,\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"data_stat_nbatch\":1,\"type_map\":[\"O\"],\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[60],\"rcut_smth\":1.8,\"rcut\":6.0,\"neuron\":[5,10,20],\"resnet_dt\":false,\"axis_neuron\":8,\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[5,5,5],\"resnet_dt\":true,\"numb_fparam\":1,\"numb_aparam\":1,\"seed\":1,\"type\":\"ener\",\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"loss\":{\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"type\":\"ener\",\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"learning_rate\":{\"start_lr\":0.001,\"stop_lr\":3e-08,\"decay_steps\":5000,\"scale_by_worker\":\"linear\",\"type\":\"exp\"},\"training\":{\"training_data\":{\"systems\":[\"../data/e3000_i2000/\",\"../data/e8000_i2000/\"],\"batch_size\":1,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"seed\":1,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"numb_steps\":1000,\"validation_data\":null,\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/pairwise_dprc.pbtxt b/source/tests/infer/pairwise_dprc.pbtxt
index 1469bda72f..4eb61c58ce 100644
--- a/source/tests/infer/pairwise_dprc.pbtxt
+++ b/source/tests/infer/pairwise_dprc.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type\":\"pairwise_dprc\",\"type_map\":[\"C\",\"P\",\"O\",\"H\",\"OW\",\"HW\"],\"type_embedding\":{\"neuron\":[8],\"precision\":\"float32\",\"activation_function\":\"tanh\",\"resnet_dt\":false,\"trainable\":true,\"seed\":null},\"qm_model\":{\"descriptor\":{\"type\":\"se_atten_v2\",\"sel\":24,\"rcut_smth\":0.5,\"rcut\":9.0,\"attn_layer\":0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"precision\":\"float32\",\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"trainable\":true,\"exclude_types\":[],\"attn\":128,\"attn_dotr\":true,\"attn_mask\":false,\"set_davg_zero\":false},\"fitting_net\":{\"type\":\"ener\",\"neuron\":[2,4,8],\"resnet_dt\":true,\"precision\":\"float32\",\"atom_ener\":[null,null,null,null,0.0,0.0],\"seed\":1,\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"trainable\":true,\"rcond\":null,\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true,\"type\":\"standard\"},\"qmmm_model\":{\"descriptor\":{\"type\":\"se_atten_v2\",\"sel\":27,\"rcut_smth\":0.5,\"rcut\":6.0,\"attn_layer\":0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"set_davg_zero\":true,\"exclude_types\":[[0,0],[0,1],[0,2],[0,3],[1,1],[1,2],[1,3],[2,2],[2,3],[3,3],[4,4],[4,5],[5,5]],\"precision\":\"float32\",\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"trainable\":true,\"attn\":128,\"attn_dotr\":true,\"attn_mask\":false},\"fitting_net\":{\"type\":\"ener\",\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"precision\":\"float32\",\"atom_ener\":[0.0,0.0,0.0,0.0,0.0,0.0],\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"trainable\":true,\"rcond\":null,\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true,\"type\":\"standard\"},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false,\"start_pref_gf\":0.0,\"limit_pref_gf\":0.0,\"numb_generalized_coord\":0},\"training\":{\"training_data\":{\"systems\":[\"../data\"],\"batch_size\":\"auto\",\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"validation_data\":null,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type\":\"pairwise_dprc\",\"type_map\":[\"C\",\"P\",\"O\",\"H\",\"OW\",\"HW\"],\"type_embedding\":{\"neuron\":[8],\"precision\":\"float32\",\"activation_function\":\"tanh\",\"resnet_dt\":false,\"trainable\":true,\"seed\":null},\"qm_model\":{\"descriptor\":{\"type\":\"se_atten_v2\",\"sel\":24,\"rcut_smth\":0.5,\"rcut\":9.0,\"attn_layer\":0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"precision\":\"float32\",\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"trainable\":true,\"exclude_types\":[],\"attn\":128,\"attn_dotr\":true,\"attn_mask\":false,\"set_davg_zero\":false},\"fitting_net\":{\"type\":\"ener\",\"neuron\":[2,4,8],\"resnet_dt\":true,\"precision\":\"float32\",\"atom_ener\":[null,null,null,null,0.0,0.0],\"seed\":1,\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"trainable\":true,\"rcond\":null,\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true,\"type\":\"standard\"},\"qmmm_model\":{\"descriptor\":{\"type\":\"se_atten_v2\",\"sel\":27,\"rcut_smth\":0.5,\"rcut\":6.0,\"attn_layer\":0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"set_davg_zero\":true,\"exclude_types\":[[0,0],[0,1],[0,2],[0,3],[1,1],[1,2],[1,3],[2,2],[2,3],[3,3],[4,4],[4,5],[5,5]],\"precision\":\"float32\",\"seed\":1,\"activation_function\":\"tanh\",\"type_one_side\":false,\"trainable\":true,\"attn\":128,\"attn_dotr\":true,\"attn_mask\":false},\"fitting_net\":{\"type\":\"ener\",\"neuron\":[2,2,2],\"resnet_dt\":true,\"seed\":1,\"precision\":\"float32\",\"atom_ener\":[0.0,0.0,0.0,0.0,0.0,0.0],\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"trainable\":true,\"rcond\":null,\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true,\"type\":\"standard\"},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10,\"srtab_add_bias\":true},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false,\"start_pref_gf\":0.0,\"limit_pref_gf\":0.0,\"numb_generalized_coord\":0},\"training\":{\"training_data\":{\"systems\":[\"../data\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"validation_data\":null,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/se_atten_no_atten_1.pbtxt b/source/tests/infer/se_atten_no_atten_1.pbtxt
index 3f1d6feb92..37c913fe50 100644
--- a/source/tests/infer/se_atten_no_atten_1.pbtxt
+++ b/source/tests/infer/se_atten_no_atten_1.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":10,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"seed\":1,\"attn\":128,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":true},\"fitting_net\":{\"neuron\":[10,10,10],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":100,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":10,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"seed\":1,\"attn\":128,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":true},\"fitting_net\":{\"neuron\":[10,10,10],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":100,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/se_atten_no_atten_2.pbtxt b/source/tests/infer/se_atten_no_atten_2.pbtxt
index 9e4f6c13cb..1dbb51a895 100644
--- a/source/tests/infer/se_atten_no_atten_2.pbtxt
+++ b/source/tests/infer/se_atten_no_atten_2.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":10,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"seed\":1000,\"attn\":128,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":true},\"fitting_net\":{\"neuron\":[10,10,10],\"resnet_dt\":true,\"seed\":10000,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10000,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":100,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":10,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[2,4,8],\"resnet_dt\":false,\"axis_neuron\":4,\"seed\":1000,\"attn\":128,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":true},\"fitting_net\":{\"neuron\":[10,10,10],\"resnet_dt\":true,\"seed\":10000,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":100,\"seed\":10000,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":100,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/se_e2_a_tebd.pbtxt b/source/tests/infer/se_e2_a_tebd.pbtxt
index 9fab995694..3b7a19495f 100644
--- a/source/tests/infer/se_e2_a_tebd.pbtxt
+++ b/source/tests/infer/se_e2_a_tebd.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"type_embedding\":{\"neuron\":[8],\"resnet_dt\":false,\"seed\":1,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true},\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[2,2],\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[8],\"resnet_dt\":false,\"axis_neuron\":4,\"type_one_side\":true,\"seed\":1,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"type_embedding\":{\"neuron\":[8],\"resnet_dt\":false,\"seed\":1,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true},\"descriptor\":{\"type\":\"se_e2_a\",\"sel\":[2,2],\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[8],\"resnet_dt\":false,\"axis_neuron\":4,\"type_one_side\":true,\"seed\":1,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[]},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/infer/virtual_type.pbtxt b/source/tests/infer/virtual_type.pbtxt
index f216e28a20..eff9625c57 100644
--- a/source/tests/infer/virtual_type.pbtxt
+++ b/source/tests/infer/virtual_type.pbtxt
@@ -35,7 +35,7 @@ node {
         dtype: DT_STRING
         tensor_shape {
         }
-        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":5,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[4],\"resnet_dt\":false,\"axis_neuron\":2,\"seed\":1,\"attn\":1,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[1],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"set_prefix\":\"set\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
+        string_val: "{\"model\":{\"type_map\":[\"O\",\"H\"],\"descriptor\":{\"type\":\"se_atten\",\"sel\":5,\"rcut_smth\":0.5,\"rcut\":6.0,\"neuron\":[4],\"resnet_dt\":false,\"axis_neuron\":2,\"seed\":1,\"attn\":1,\"attn_layer\":0,\"attn_dotr\":true,\"attn_mask\":false,\"activation_function\":\"tanh\",\"type_one_side\":false,\"precision\":\"default\",\"trainable\":true,\"exclude_types\":[],\"set_davg_zero\":false},\"fitting_net\":{\"neuron\":[1],\"resnet_dt\":true,\"seed\":1,\"type\":\"ener\",\"numb_fparam\":0,\"numb_aparam\":0,\"activation_function\":\"tanh\",\"precision\":\"default\",\"trainable\":true,\"rcond\":0.001,\"atom_ener\":[],\"use_aparam_as_mask\":false},\"data_stat_nbatch\":10,\"data_stat_protect\":0.01,\"data_bias_nsample\":10},\"learning_rate\":{\"type\":\"exp\",\"decay_steps\":5000,\"start_lr\":0.001,\"stop_lr\":3.51e-08,\"scale_by_worker\":\"linear\"},\"loss\":{\"type\":\"ener\",\"start_pref_e\":0.02,\"limit_pref_e\":1,\"start_pref_f\":1000,\"limit_pref_f\":1,\"start_pref_v\":0,\"limit_pref_v\":0,\"start_pref_ae\":0.0,\"limit_pref_ae\":0.0,\"start_pref_pf\":0.0,\"limit_pref_pf\":0.0,\"enable_atom_ener_coeff\":false},\"training\":{\"training_data\":{\"systems\":[\"../data/data_0/\",\"../data/data_1/\",\"../data/data_2/\"],\"batch_size\":\"auto\",\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"validation_data\":{\"systems\":[\"../data/data_3\"],\"batch_size\":1,\"numb_btch\":3,\"auto_prob\":\"prob_sys_size\",\"sys_probs\":null},\"numb_steps\":0,\"seed\":10,\"disp_file\":\"lcurve.out\",\"disp_freq\":100,\"save_freq\":1000,\"save_ckpt\":\"model.ckpt\",\"disp_training\":true,\"time_training\":true,\"profiling\":false,\"profiling_file\":\"timeline.json\",\"enable_profiler\":false,\"tensorboard\":false,\"tensorboard_log_dir\":\"log\",\"tensorboard_freq\":1}}"
       }
     }
   }
diff --git a/source/tests/pt/dos/input.json b/source/tests/pt/dos/input.json
index 991f5acf70..a76afe368a 100644
--- a/source/tests/pt/dos/input.json
+++ b/source/tests/pt/dos/input.json
@@ -67,7 +67,6 @@
         "pt/dos/data/atomic_system/",
         "pt/dos/data/global_system/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     },
     "validation_data": {
@@ -75,7 +74,6 @@
         "pt/dos/data/atomic_system/",
         "pt/dos/data/global_system/"
       ],
-      "set_prefix": "set",
       "batch_size": 1
     }
   },
diff --git a/source/tests/tf/compat_inputs/water_se_a_v0.json b/source/tests/tf/compat_inputs/water_se_a_v0.json
index be313266e2..65849a9b1b 100644
--- a/source/tests/tf/compat_inputs/water_se_a_v0.json
+++ b/source/tests/tf/compat_inputs/water_se_a_v0.json
@@ -27,7 +27,6 @@
   "systems": [
     "../data/"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": [
     1
diff --git a/source/tests/tf/compat_inputs/water_se_a_v1.json b/source/tests/tf/compat_inputs/water_se_a_v1.json
index 7ebec4d5a3..b893765340 100644
--- a/source/tests/tf/compat_inputs/water_se_a_v1.json
+++ b/source/tests/tf/compat_inputs/water_se_a_v1.json
@@ -48,7 +48,6 @@
     "systems": [
       "../data/"
     ],
-    "set_prefix": "set",
     "stop_batch": 1000000,
     "batch_size": [
       1
diff --git a/source/tests/tf/compat_inputs/water_v0.json b/source/tests/tf/compat_inputs/water_v0.json
index 385363ce80..4d0e7662cf 100644
--- a/source/tests/tf/compat_inputs/water_v0.json
+++ b/source/tests/tf/compat_inputs/water_v0.json
@@ -42,7 +42,6 @@
   "systems": [
     "../data/"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": [
     4
diff --git a/source/tests/tf/compat_inputs/water_v1.json b/source/tests/tf/compat_inputs/water_v1.json
index 076a576d7b..39de1e8fa4 100644
--- a/source/tests/tf/compat_inputs/water_v1.json
+++ b/source/tests/tf/compat_inputs/water_v1.json
@@ -59,7 +59,6 @@
     "systems": [
       "../data/"
     ],
-    "set_prefix": "set",
     "stop_batch": 1000000,
     "batch_size": [
       4
diff --git a/source/tests/tf/compat_inputs/water_v2.json b/source/tests/tf/compat_inputs/water_v2.json
index af8eca7db1..dbc241450a 100644
--- a/source/tests/tf/compat_inputs/water_v2.json
+++ b/source/tests/tf/compat_inputs/water_v2.json
@@ -60,7 +60,6 @@
       "systems": [
         "../data/"
       ],
-      "set_prefix": "set",
       "batch_size": [
         4
       ]
diff --git a/source/tests/tf/data_modifier/dipole.json b/source/tests/tf/data_modifier/dipole.json
index ac9cec0570..f4880b12c3 100644
--- a/source/tests/tf/data_modifier/dipole.json
+++ b/source/tests/tf/data_modifier/dipole.json
@@ -58,7 +58,6 @@
     "systems": [
       "data_modifier/sys_10"
     ],
-    "set_prefix": "set",
     "stop_batch": 1000000,
     "batch_size": 4,
 
diff --git a/source/tests/tf/polar_se_a.json b/source/tests/tf/polar_se_a.json
index 624113c340..eed6b58b94 100644
--- a/source/tests/tf/polar_se_a.json
+++ b/source/tests/tf/polar_se_a.json
@@ -59,7 +59,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": [
     1
diff --git a/source/tests/tf/polar_se_a_tebd.json b/source/tests/tf/polar_se_a_tebd.json
index 6bb548a590..50d1cb0841 100644
--- a/source/tests/tf/polar_se_a_tebd.json
+++ b/source/tests/tf/polar_se_a_tebd.json
@@ -68,7 +68,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": [
     1
diff --git a/source/tests/tf/test_data_modifier.py b/source/tests/tf/test_data_modifier.py
index cf2c50b761..eae3155cb8 100644
--- a/source/tests/tf/test_data_modifier.py
+++ b/source/tests/tf/test_data_modifier.py
@@ -65,7 +65,7 @@ def _setUp(self):
         systems = j_must_have(jdata["training"], "systems")
         # systems[0] = tests_path / systems[0]
         systems = [tests_path / ii for ii in systems]
-        set_pfx = j_must_have(jdata["training"], "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata["training"], "batch_size")
         test_size = j_must_have(jdata["training"], "numb_test")
         data = DeepmdDataSystem(
diff --git a/source/tests/tf/test_data_modifier_shuffle.py b/source/tests/tf/test_data_modifier_shuffle.py
index 41086cc775..1fdd8b4967 100644
--- a/source/tests/tf/test_data_modifier_shuffle.py
+++ b/source/tests/tf/test_data_modifier_shuffle.py
@@ -66,7 +66,7 @@ def _setUp(self):
 
         # init data system
         systems = j_must_have(jdata["training"], "systems")
-        set_pfx = j_must_have(jdata["training"], "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata["training"], "batch_size")
         test_size = j_must_have(jdata["training"], "numb_test")
         data = DeepmdDataSystem(
@@ -176,7 +176,6 @@ def _setUp_jdata(self):
             },
             "training": {
                 "systems": ["data_modifier/sys_test_0"],
-                "set_prefix": "set",
                 "stop_batch": 1000000,
                 "batch_size": 1,
                 "numb_test": 2,
diff --git a/source/tests/tf/test_descrpt_hybrid.py b/source/tests/tf/test_descrpt_hybrid.py
index 6aa04118da..4023521fca 100644
--- a/source/tests/tf/test_descrpt_hybrid.py
+++ b/source/tests/tf/test_descrpt_hybrid.py
@@ -41,7 +41,7 @@ def test_descriptor_hybrid(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 2
diff --git a/source/tests/tf/test_descrpt_se_a_mask.py b/source/tests/tf/test_descrpt_se_a_mask.py
index b6488d88c6..7f2461a6f4 100644
--- a/source/tests/tf/test_descrpt_se_a_mask.py
+++ b/source/tests/tf/test_descrpt_se_a_mask.py
@@ -232,7 +232,6 @@ def test_descriptor_se_a_mask(self):
             str(tests_path / "data_dp_mask")
         ]
         systems = j_must_have(jdata["training"]["validation_data"], "systems")
-        # set_pfx = j_must_have(jdata['validation_data'], "set_prefix")
         set_pfx = "set"
         batch_size = 2
         test_size = 1
diff --git a/source/tests/tf/test_descrpt_se_a_type.py b/source/tests/tf/test_descrpt_se_a_type.py
index 87c2adcca7..d321183c54 100644
--- a/source/tests/tf/test_descrpt_se_a_type.py
+++ b/source/tests/tf/test_descrpt_se_a_type.py
@@ -34,7 +34,7 @@ def test_descriptor_two_sides(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 2
@@ -198,7 +198,7 @@ def test_descriptor_one_side(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_descrpt_se_atten.py b/source/tests/tf/test_descrpt_se_atten.py
index da5eb05650..610788d32e 100644
--- a/source/tests/tf/test_descrpt_se_atten.py
+++ b/source/tests/tf/test_descrpt_se_atten.py
@@ -43,7 +43,7 @@ def test_descriptor_two_sides(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 2
@@ -220,7 +220,7 @@ def test_descriptor_one_side(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -398,7 +398,7 @@ def test_stripped_type_embedding_descriptor_two_sides(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 2
@@ -569,7 +569,7 @@ def test_compressible_descriptor_two_sides(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 2
diff --git a/source/tests/tf/test_dipole_se_a.py b/source/tests/tf/test_dipole_se_a.py
index 6905d94371..5764861ca3 100644
--- a/source/tests/tf/test_dipole_se_a.py
+++ b/source/tests/tf/test_dipole_se_a.py
@@ -39,7 +39,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_dipole_se_a_tebd.py b/source/tests/tf/test_dipole_se_a_tebd.py
index 3db90bc3f8..769a715346 100644
--- a/source/tests/tf/test_dipole_se_a_tebd.py
+++ b/source/tests/tf/test_dipole_se_a_tebd.py
@@ -49,7 +49,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_fitting_dos.py b/source/tests/tf/test_fitting_dos.py
index f9df5fc126..c414c543fe 100644
--- a/source/tests/tf/test_fitting_dos.py
+++ b/source/tests/tf/test_fitting_dos.py
@@ -34,7 +34,7 @@ def test_fitting(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata["training"], "systems")
-        set_pfx = j_must_have(jdata["training"], "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata["training"], "batch_size")
         test_size = j_must_have(jdata["training"], "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_fitting_ener_type.py b/source/tests/tf/test_fitting_ener_type.py
index c1c1698d4f..5c3027924b 100644
--- a/source/tests/tf/test_fitting_ener_type.py
+++ b/source/tests/tf/test_fitting_ener_type.py
@@ -34,7 +34,7 @@ def test_fitting(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_init_frz_model_spin.py b/source/tests/tf/test_init_frz_model_spin.py
index c2c433cde0..a99a052391 100644
--- a/source/tests/tf/test_init_frz_model_spin.py
+++ b/source/tests/tf/test_init_frz_model_spin.py
@@ -57,7 +57,6 @@ def _init_models():
     jdata["training"]["training_data"]["systems"] = [str(tests_path / "model_spin/")]
     jdata["training"]["validation_data"]["systems"] = [str(tests_path / "model_spin/")]
 
-    del jdata["training"]["set_prefix"]
     with open(INPUT, "w") as fp:
         json.dump(jdata, fp, indent=4)
     ret = run_dp("dp train " + INPUT)
@@ -72,7 +71,6 @@ def _init_models():
     jdata["training"]["save_ckpt"] = ckpt
     jdata["training"]["training_data"]["systems"] = [str(tests_path / "model_spin/")]
     jdata["training"]["validation_data"]["systems"] = [str(tests_path / "model_spin/")]
-    del jdata["training"]["set_prefix"]
     jdata["loss"]["type"] = "ener_spin"
     jdata = update_deepmd_input(jdata, warning=True, dump="input_v2_compat.json")
     jdata = normalize(jdata)
diff --git a/source/tests/tf/test_layer_name.py b/source/tests/tf/test_layer_name.py
index 089bd19dd1..c61c5eafe2 100644
--- a/source/tests/tf/test_layer_name.py
+++ b/source/tests/tf/test_layer_name.py
@@ -43,7 +43,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_dos.py b/source/tests/tf/test_model_dos.py
index 9c01b14e32..6ba1d73a0c 100644
--- a/source/tests/tf/test_model_dos.py
+++ b/source/tests/tf/test_model_dos.py
@@ -41,7 +41,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata["training"], "systems")
-        set_pfx = j_must_have(jdata["training"], "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata["training"], "batch_size")
         test_size = j_must_have(jdata["training"], "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_loc_frame.py b/source/tests/tf/test_model_loc_frame.py
index 84467b436a..91d38bab52 100644
--- a/source/tests/tf/test_model_loc_frame.py
+++ b/source/tests/tf/test_model_loc_frame.py
@@ -36,7 +36,7 @@ def test_model(self):
         jfile = "water.json"
         jdata = j_loader(jfile)
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_multi.py b/source/tests/tf/test_model_multi.py
index 66b0cce000..4b0605b8a7 100644
--- a/source/tests/tf/test_model_multi.py
+++ b/source/tests/tf/test_model_multi.py
@@ -44,7 +44,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_pairtab.py b/source/tests/tf/test_model_pairtab.py
index e2c45ee50c..5835d67343 100644
--- a/source/tests/tf/test_model_pairtab.py
+++ b/source/tests/tf/test_model_pairtab.py
@@ -31,7 +31,7 @@ def test_model(self):
         jfile = "water.json"
         jdata = j_loader(jfile)
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = 1
         test_size = 1
 
diff --git a/source/tests/tf/test_model_se_a.py b/source/tests/tf/test_model_se_a.py
index 0b2f17e99c..ad2c1b7ced 100644
--- a/source/tests/tf/test_model_se_a.py
+++ b/source/tests/tf/test_model_se_a.py
@@ -60,7 +60,7 @@ def test_model_atom_ener(self):
         sys.to_deepmd_npy("system", prec=np.float64)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -141,7 +141,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -287,7 +287,7 @@ def test_model_atom_ener_type_embedding(self):
         sys.to_deepmd_npy("system", prec=np.float64)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_aparam.py b/source/tests/tf/test_model_se_a_aparam.py
index 00a71f9136..e44e1c8c9f 100644
--- a/source/tests/tf/test_model_se_a_aparam.py
+++ b/source/tests/tf/test_model_se_a_aparam.py
@@ -36,7 +36,7 @@ def test_model(self):
         jfile = "water_se_a_aparam.json"
         jdata = j_loader(jfile)
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_ebd.py b/source/tests/tf/test_model_se_a_ebd.py
index e4a6d78d65..8f91295f26 100644
--- a/source/tests/tf/test_model_se_a_ebd.py
+++ b/source/tests/tf/test_model_se_a_ebd.py
@@ -37,7 +37,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_ebd_v2.py b/source/tests/tf/test_model_se_a_ebd_v2.py
index 86aead5eef..6156455402 100644
--- a/source/tests/tf/test_model_se_a_ebd_v2.py
+++ b/source/tests/tf/test_model_se_a_ebd_v2.py
@@ -40,7 +40,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_fparam.py b/source/tests/tf/test_model_se_a_fparam.py
index 3045948480..ce31f94488 100644
--- a/source/tests/tf/test_model_se_a_fparam.py
+++ b/source/tests/tf/test_model_se_a_fparam.py
@@ -37,7 +37,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_srtab.py b/source/tests/tf/test_model_se_a_srtab.py
index 2c4d5d70f9..ae192b09ec 100644
--- a/source/tests/tf/test_model_se_a_srtab.py
+++ b/source/tests/tf/test_model_se_a_srtab.py
@@ -54,7 +54,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_a_type.py b/source/tests/tf/test_model_se_a_type.py
index 9a42466766..f92fdaa2a7 100644
--- a/source/tests/tf/test_model_se_a_type.py
+++ b/source/tests/tf/test_model_se_a_type.py
@@ -40,7 +40,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_atten.py b/source/tests/tf/test_model_se_atten.py
index a4b6575ecb..e1143d8c2e 100644
--- a/source/tests/tf/test_model_se_atten.py
+++ b/source/tests/tf/test_model_se_atten.py
@@ -51,7 +51,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -205,7 +205,7 @@ def test_exclude_types(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -278,7 +278,7 @@ def test_compressible_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -434,7 +434,7 @@ def test_compressible_exclude_types(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -509,7 +509,7 @@ def test_stripped_type_embedding_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -668,7 +668,7 @@ def test_stripped_type_embedding_exclude_types(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -748,7 +748,7 @@ def test_smoothness_of_stripped_type_embedding_smooth_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -897,7 +897,7 @@ def test_smoothness_of_stripped_type_embedding_smooth_model_excluded_types(self)
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = 1
         test_size = 1
         rcut = j_must_have(jdata["model"]["descriptor"], "rcut")
diff --git a/source/tests/tf/test_model_se_r.py b/source/tests/tf/test_model_se_r.py
index 1e63922e19..90976b9d47 100644
--- a/source/tests/tf/test_model_se_r.py
+++ b/source/tests/tf/test_model_se_r.py
@@ -37,7 +37,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_se_t.py b/source/tests/tf/test_model_se_t.py
index d75fac2f07..1948c8b54b 100644
--- a/source/tests/tf/test_model_se_t.py
+++ b/source/tests/tf/test_model_se_t.py
@@ -37,7 +37,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_model_spin.json b/source/tests/tf/test_model_spin.json
index 295cf608c4..8b7a91fbfd 100644
--- a/source/tests/tf/test_model_spin.json
+++ b/source/tests/tf/test_model_spin.json
@@ -77,7 +77,6 @@
       "batch_size": 1,
       "numb_btch": 1
     },
-    "set_prefix": "set",
     "numb_steps": 1,
     "seed": 1,
     "disp_file": "lcurve.out",
diff --git a/source/tests/tf/test_model_spin.py b/source/tests/tf/test_model_spin.py
index 5d20c76c35..65a866b021 100644
--- a/source/tests/tf/test_model_spin.py
+++ b/source/tests/tf/test_model_spin.py
@@ -47,7 +47,7 @@ def test_model_spin(self):
         jdata = j_loader(jfile)
 
         # set system information
-        set_pfx = j_must_have(jdata["training"], "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata["training"]["training_data"], "batch_size")
         batch_size = 2
         test_size = j_must_have(jdata["training"]["validation_data"], "numb_btch")
diff --git a/source/tests/tf/test_polar_se_a.py b/source/tests/tf/test_polar_se_a.py
index 8ef967de55..63f4bfa589 100644
--- a/source/tests/tf/test_polar_se_a.py
+++ b/source/tests/tf/test_polar_se_a.py
@@ -46,7 +46,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_polar_se_a_tebd.py b/source/tests/tf/test_polar_se_a_tebd.py
index 5a3c001004..f9f4954d74 100644
--- a/source/tests/tf/test_polar_se_a_tebd.py
+++ b/source/tests/tf/test_polar_se_a_tebd.py
@@ -49,7 +49,7 @@ def test_model(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/test_type_one_side.py b/source/tests/tf/test_type_one_side.py
index 5c71a41739..e2f992f212 100644
--- a/source/tests/tf/test_type_one_side.py
+++ b/source/tests/tf/test_type_one_side.py
@@ -42,7 +42,7 @@ def test_descriptor_one_side_exclude_types(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
@@ -149,7 +149,7 @@ def test_se_r_one_side_exclude_types(self):
         jdata = j_loader(jfile)
 
         systems = j_must_have(jdata, "systems")
-        set_pfx = j_must_have(jdata, "set_prefix")
+        set_pfx = "set"
         batch_size = j_must_have(jdata, "batch_size")
         test_size = j_must_have(jdata, "numb_test")
         batch_size = 1
diff --git a/source/tests/tf/train_dos.json b/source/tests/tf/train_dos.json
index d08fbd90e1..95bd219592 100644
--- a/source/tests/tf/train_dos.json
+++ b/source/tests/tf/train_dos.json
@@ -53,7 +53,6 @@
     "systems": [
       "system/"
     ],
-    "set_prefix": "set",
     "stop_batch": 100000,
     "batch_size": 1,
     "seed": 1,
diff --git a/source/tests/tf/water.json b/source/tests/tf/water.json
index 6b61ce98ae..cf9f1ae61d 100644
--- a/source/tests/tf/water.json
+++ b/source/tests/tf/water.json
@@ -49,7 +49,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 4,
   "start_lr": 0.001,
diff --git a/source/tests/tf/water_hybrid.json b/source/tests/tf/water_hybrid.json
index 4e813beec1..5ca70efdaf 100644
--- a/source/tests/tf/water_hybrid.json
+++ b/source/tests/tf/water_hybrid.json
@@ -70,7 +70,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_layer_name.json b/source/tests/tf/water_layer_name.json
index caa953c903..06b9b981ec 100644
--- a/source/tests/tf/water_layer_name.json
+++ b/source/tests/tf/water_layer_name.json
@@ -86,7 +86,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "seed": 1,
diff --git a/source/tests/tf/water_multi.json b/source/tests/tf/water_multi.json
index 2ccbaa9384..44522ed362 100644
--- a/source/tests/tf/water_multi.json
+++ b/source/tests/tf/water_multi.json
@@ -84,7 +84,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "seed": 1,
diff --git a/source/tests/tf/water_se_a.json b/source/tests/tf/water_se_a.json
index e864d85f6b..e5256060a7 100644
--- a/source/tests/tf/water_se_a.json
+++ b/source/tests/tf/water_se_a.json
@@ -33,7 +33,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_afparam.json b/source/tests/tf/water_se_a_afparam.json
index 6504643b0c..6519ee2272 100644
--- a/source/tests/tf/water_se_a_afparam.json
+++ b/source/tests/tf/water_se_a_afparam.json
@@ -35,7 +35,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_aparam.json b/source/tests/tf/water_se_a_aparam.json
index 4a0c478de5..916cfa331d 100644
--- a/source/tests/tf/water_se_a_aparam.json
+++ b/source/tests/tf/water_se_a_aparam.json
@@ -34,7 +34,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_ebd.json b/source/tests/tf/water_se_a_ebd.json
index 3ce0653d28..037294ed0f 100644
--- a/source/tests/tf/water_se_a_ebd.json
+++ b/source/tests/tf/water_se_a_ebd.json
@@ -32,7 +32,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 100000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_fparam.json b/source/tests/tf/water_se_a_fparam.json
index fff46098b8..623dc926b9 100644
--- a/source/tests/tf/water_se_a_fparam.json
+++ b/source/tests/tf/water_se_a_fparam.json
@@ -34,7 +34,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_srtab.json b/source/tests/tf/water_se_a_srtab.json
index dda7f52dbf..12dd148131 100644
--- a/source/tests/tf/water_se_a_srtab.json
+++ b/source/tests/tf/water_se_a_srtab.json
@@ -37,7 +37,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_a_type.json b/source/tests/tf/water_se_a_type.json
index 9f5e4e7a51..17da987cd6 100644
--- a/source/tests/tf/water_se_a_type.json
+++ b/source/tests/tf/water_se_a_type.json
@@ -43,7 +43,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_atten.json b/source/tests/tf/water_se_atten.json
index c8799bf254..f8911d0f21 100644
--- a/source/tests/tf/water_se_atten.json
+++ b/source/tests/tf/water_se_atten.json
@@ -46,7 +46,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_atten_compressible_mixed_type.json b/source/tests/tf/water_se_atten_compressible_mixed_type.json
index fbf723d10a..5ecb24faf0 100644
--- a/source/tests/tf/water_se_atten_compressible_mixed_type.json
+++ b/source/tests/tf/water_se_atten_compressible_mixed_type.json
@@ -47,7 +47,6 @@
   "systems": [
     "system_mixed_type"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_atten_mixed_type.json b/source/tests/tf/water_se_atten_mixed_type.json
index 8edabb394a..05dfad48b6 100644
--- a/source/tests/tf/water_se_atten_mixed_type.json
+++ b/source/tests/tf/water_se_atten_mixed_type.json
@@ -46,7 +46,6 @@
   "systems": [
     "system_mixed_type"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_r.json b/source/tests/tf/water_se_r.json
index eb12f359cc..e9be3b8a68 100644
--- a/source/tests/tf/water_se_r.json
+++ b/source/tests/tf/water_se_r.json
@@ -32,7 +32,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/water_se_t.json b/source/tests/tf/water_se_t.json
index 7ce666e4aa..c05b5f3b7a 100644
--- a/source/tests/tf/water_se_t.json
+++ b/source/tests/tf/water_se_t.json
@@ -32,7 +32,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": 1,
   "start_lr": 0.005,
diff --git a/source/tests/tf/wfc.json b/source/tests/tf/wfc.json
index b2c98ab136..9772bdba5c 100644
--- a/source/tests/tf/wfc.json
+++ b/source/tests/tf/wfc.json
@@ -69,7 +69,6 @@
   "systems": [
     "system"
   ],
-  "set_prefix": "set",
   "stop_batch": 1000000,
   "batch_size": [
     1
diff --git a/source/tests/tf/yaml_inputs/water_se_a_v1.json b/source/tests/tf/yaml_inputs/water_se_a_v1.json
index 7ebec4d5a3..b893765340 100644
--- a/source/tests/tf/yaml_inputs/water_se_a_v1.json
+++ b/source/tests/tf/yaml_inputs/water_se_a_v1.json
@@ -48,7 +48,6 @@
     "systems": [
       "../data/"
     ],
-    "set_prefix": "set",
     "stop_batch": 1000000,
     "batch_size": [
       1
diff --git a/source/tests/tf/yaml_inputs/water_se_a_v1.yaml b/source/tests/tf/yaml_inputs/water_se_a_v1.yaml
index f0a1e32766..909741a079 100644
--- a/source/tests/tf/yaml_inputs/water_se_a_v1.yaml
+++ b/source/tests/tf/yaml_inputs/water_se_a_v1.yaml
@@ -34,7 +34,6 @@ loss:
   limit_pref_v: 0
 training:
   systems: ["../data/"]
-  set_prefix: set
   stop_batch: 1000000
   batch_size:
     - 1
diff --git a/source/tests/tf/yaml_inputs/water_v1.json b/source/tests/tf/yaml_inputs/water_v1.json
index 076a576d7b..39de1e8fa4 100644
--- a/source/tests/tf/yaml_inputs/water_v1.json
+++ b/source/tests/tf/yaml_inputs/water_v1.json
@@ -59,7 +59,6 @@
     "systems": [
       "../data/"
     ],
-    "set_prefix": "set",
     "stop_batch": 1000000,
     "batch_size": [
       4
diff --git a/source/tests/tf/yaml_inputs/water_v1.yaml b/source/tests/tf/yaml_inputs/water_v1.yaml
index 95000631f6..d1a360c4b2 100644
--- a/source/tests/tf/yaml_inputs/water_v1.yaml
+++ b/source/tests/tf/yaml_inputs/water_v1.yaml
@@ -33,7 +33,6 @@ loss:
 training:
   systems:
     - ../data/
-  set_prefix: set
   stop_batch: 1000000
   batch_size:
     - 4