From 6e3554bac76f96852361bc1226dd89f8ac5f1562 Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 12:14:58 +0800
Subject: [PATCH 1/9] fix(model): fit residual bias changes for preset outputs

---
 .../dpmodel/atomic_model/base_atomic_model.py | 12 +++++----
 .../model/atomic_model/base_atomic_model.py   | 12 +++++----
 .../model/atomic_model/base_atomic_model.py   | 12 +++++----
 .../dpmodel/test_atomic_model_global_stat.py  | 23 +++++++++++-----
 .../pd/model/test_atomic_model_global_stat.py | 26 ++++++++++++++-----
 .../pt/model/test_atomic_model_global_stat.py | 26 ++++++++++++++-----
 6 files changed, 78 insertions(+), 33 deletions(-)

diff --git a/deepmd/dpmodel/atomic_model/base_atomic_model.py b/deepmd/dpmodel/atomic_model/base_atomic_model.py
index 3a7922e8bd..a665be29ae 100644
--- a/deepmd/dpmodel/atomic_model/base_atomic_model.py
+++ b/deepmd/dpmodel/atomic_model/base_atomic_model.py
@@ -817,12 +817,14 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
+            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
+            is fixed by the preset:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero
-            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
+            preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
+            In 'change-by-statistic' mode, presets are treated as part of the
+            current stored bias and the residual statistics are fitted normally.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -842,7 +844,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias:
+        if self.preset_out_bias and not change:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -853,7 +855,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=change,
+                keep_unassigned=False,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat(rows)
diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py
index 8a8aaefd48..5ce71605b8 100644
--- a/deepmd/pd/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pd/model/atomic_model/base_atomic_model.py
@@ -518,12 +518,14 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
+            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
+            is fixed by the preset:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero
-            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
+            preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
+            In 'change-by-statistic' mode, presets are treated as part of the
+            current stored bias and the residual statistics are fitted normally.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -538,7 +540,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias:
+        if self.preset_out_bias and not change:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -549,7 +551,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=change,
+                keep_unassigned=False,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat({kk: to_paddle_tensor(vv) for kk, vv in rows.items()})
diff --git a/deepmd/pt/model/atomic_model/base_atomic_model.py b/deepmd/pt/model/atomic_model/base_atomic_model.py
index d18e780cd3..91c251098f 100644
--- a/deepmd/pt/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pt/model/atomic_model/base_atomic_model.py
@@ -648,12 +648,14 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
+            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
+            is fixed by the preset:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero
-            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
+            preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
+            In 'change-by-statistic' mode, presets are treated as part of the
+            current stored bias and the residual statistics are fitted normally.
         model_forward : Callable[..., dict[str, torch.Tensor]], optional
             Predictor of the complete atomic outputs used by 'change-by-statistic'.
             Defaults to the forward of this atomic model; a model that adds
@@ -670,7 +672,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias:
+        if self.preset_out_bias and not change:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -681,7 +683,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=change,
+                keep_unassigned=False,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat({kk: to_torch_tensor(vv) for kk, vv in rows.items()})
diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 0059374e0a..54a3fa792f 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -319,16 +319,27 @@ def test_preset_bias(self) -> None:
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
 
-        # 3. change-by-statistic keeps every assigned type at its preset
+        # 3. change-by-statistic treats the preset as the stored starting bias
+        # and fits a downstream residual shift.
         md0.change_out_bias(
             self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        ret3 = md0.forward_common_atomic(*args)
-        for kk in ["foo", "pix", "bar"]:
-            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
+        args_stat = [
+            self.coord_ext,
+            np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
+            self.nlist,
+        ]
+        ret3 = md0.forward_common_atomic(*args_stat)
+        expected_ret3 = {}
+        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
+        expected_ret3["pix"] = ret0["pix"]
+        for kk in ["foo", "pix"]:
+            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(out_bias["foo"], foo_bias)
-        np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
+        np.testing.assert_almost_equal(
+            out_bias["foo"], np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(out_bias["bar"], bar_bias)
 
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPDPAtomicModel(
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index bacec7e682..c8ba1e176f 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -349,17 +349,31 @@ def cvt_ret(x):
         expected_ret1["bar"] = ret0["bar"] + bar_bias[at]
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
-        # 3. change-by-statistic keeps every assigned type at its preset
+        # 3. change-by-statistic treats the preset as the stored starting bias
+        # and fits a downstream residual shift.
         BaseAtomicModel.change_out_bias(
             md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        ret3 = md0.forward_common_atomic(*args)
+        args_stat = [
+            to_paddle_tensor(ii)
+            for ii in [
+                self.coord_ext,
+                np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
+                self.nlist,
+            ]
+        ]
+        ret3 = md0.forward_common_atomic(*args_stat)
         ret3 = cvt_ret(ret3)
-        for kk in ["foo", "pix", "bar"]:
-            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
+        expected_ret3 = {}
+        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
+        expected_ret3["pix"] = ret0["pix"]
+        for kk in ["foo", "pix"]:
+            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+        np.testing.assert_almost_equal(
+            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index a4bca815b9..1388d3f16b 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -375,17 +375,31 @@ def cvt_ret(x):
         expected_ret1["bar"] = ret0["bar"] + bar_bias[at]
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
-        # 3. change-by-statistic keeps every assigned type at its preset
+        # 3. change-by-statistic treats the preset as the stored starting bias
+        # and fits a downstream residual shift.
         BaseAtomicModel.change_out_bias(
             md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        ret3 = md0.forward_common_atomic(*args, fparam=self.fparam)
+        args_stat = [
+            to_torch_tensor(ii)
+            for ii in [
+                self.coord_ext,
+                np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
+                self.nlist,
+            ]
+        ]
+        ret3 = md0.forward_common_atomic(*args_stat, fparam=self.fparam)
         ret3 = cvt_ret(ret3)
-        for kk in ["foo", "pix", "bar"]:
-            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
+        expected_ret3 = {}
+        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
+        expected_ret3["pix"] = ret0["pix"]
+        for kk in ["foo", "pix"]:
+            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+        np.testing.assert_almost_equal(
+            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,

From d085730967d38e2658bc7cd5399c57fcd196c21f Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 12:34:42 +0800
Subject: [PATCH 2/9] fix(finetune): honor explicit downstream output bias
 presets

---
 deepmd/dpmodel/atomic_model/base_atomic_model.py   | 12 ++++++++----
 deepmd/dpmodel/model/make_model.py                 |  5 ++++-
 deepmd/dpmodel/model/spin_model.py                 |  2 ++
 deepmd/dpmodel/train/trainer.py                    |  2 ++
 deepmd/jax/train/trainer.py                        |  1 +
 deepmd/pd/model/atomic_model/base_atomic_model.py  | 12 ++++++++----
 deepmd/pd/model/model/make_model.py                |  2 ++
 deepmd/pd/train/training.py                        |  3 +++
 deepmd/pt/model/atomic_model/base_atomic_model.py  | 12 ++++++++----
 deepmd/pt/model/model/make_model.py                |  2 ++
 deepmd/pt/model/model/sezm_spin_model.py           |  2 ++
 deepmd/pt/model/model/spin_model.py                |  2 ++
 deepmd/pt/train/training.py                        |  3 +++
 deepmd/utils/argcheck.py                           |  7 +++++--
 .../dpmodel/test_atomic_model_global_stat.py       | 12 ++++++++++++
 source/tests/common/test_dpmodel_train.py          | 14 +++++++++++++-
 .../pd/model/test_atomic_model_global_stat.py      | 13 +++++++++++++
 .../pt/model/test_atomic_model_global_stat.py      | 13 +++++++++++++
 18 files changed, 103 insertions(+), 16 deletions(-)

diff --git a/deepmd/dpmodel/atomic_model/base_atomic_model.py b/deepmd/dpmodel/atomic_model/base_atomic_model.py
index a665be29ae..ecad9d08b7 100644
--- a/deepmd/dpmodel/atomic_model/base_atomic_model.py
+++ b/deepmd/dpmodel/atomic_model/base_atomic_model.py
@@ -800,6 +800,7 @@ def change_out_bias(
         stat_file_path: DPPath | None = None,
         bias_adjust_mode: str = "change-by-statistic",
         observed_type: list[str] | None = None,
+        apply_preset: bool = False,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -823,8 +824,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, presets are treated as part of the
-            current stored bias and the residual statistics are fitted normally.
+            In 'change-by-statistic' mode, stored presets are ignored unless
+            apply_preset is True for an explicitly provided downstream preset.
+        apply_preset : bool
+            Apply the current configuration's preset during residual fitting.
+            Enable only when the downstream operation explicitly supplies it.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -844,7 +848,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and not change:
+        if self.preset_out_bias and (not change or apply_preset):
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -855,7 +859,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=False,
+                keep_unassigned=change,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat(rows)
diff --git a/deepmd/dpmodel/model/make_model.py b/deepmd/dpmodel/model/make_model.py
index b74fb6b697..3cf8430470 100644
--- a/deepmd/dpmodel/model/make_model.py
+++ b/deepmd/dpmodel/model/make_model.py
@@ -926,6 +926,7 @@ def change_out_bias(
             self,
             merged: Any,
             bias_adjust_mode: str = "change-by-statistic",
+            apply_preset: bool = False,
         ) -> None:
             """Change the output bias according to the input data and the pretrained model.
 
@@ -937,7 +938,9 @@ def change_out_bias(
                 The mode for changing output bias:
                 'change-by-statistic' or 'set-by-statistic'.
             """
-            self.atomic_model.change_out_bias(merged, bias_adjust_mode=bias_adjust_mode)
+            self.atomic_model.change_out_bias(
+                merged, bias_adjust_mode=bias_adjust_mode, apply_preset=apply_preset
+            )
 
         def _input_type_cast(
             self,
diff --git a/deepmd/dpmodel/model/spin_model.py b/deepmd/dpmodel/model/spin_model.py
index 8678e51398..21c83de014 100644
--- a/deepmd/dpmodel/model/spin_model.py
+++ b/deepmd/dpmodel/model/spin_model.py
@@ -603,6 +603,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict]] | list[dict],
         bias_adjust_mode: str = "change-by-statistic",
+        apply_preset: bool = False,
     ) -> None:
         """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -627,6 +628,7 @@ def change_out_bias(
         self.backbone_model.change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
+            apply_preset=apply_preset,
         )
 
     def change_type_map(
diff --git a/deepmd/dpmodel/train/trainer.py b/deepmd/dpmodel/train/trainer.py
index 531bc7d07c..5c6544518b 100644
--- a/deepmd/dpmodel/train/trainer.py
+++ b/deepmd/dpmodel/train/trainer.py
@@ -74,12 +74,14 @@ def change_model_out_bias(
     *,
     bias_adjust_mode: str = "change-by-statistic",
     recompute_input_stats: bool = False,
+    apply_preset: bool = False,
 ) -> Any:
     """Change one model's output bias and log the before/after values."""
     old_bias = deepcopy(model.get_out_bias())
     model.change_out_bias(
         sample_func,
         bias_adjust_mode=bias_adjust_mode,
+        apply_preset=apply_preset,
     )
     new_bias = deepcopy(model.get_out_bias())
 
diff --git a/deepmd/jax/train/trainer.py b/deepmd/jax/train/trainer.py
index a35de2a49b..3194398ded 100644
--- a/deepmd/jax/train/trainer.py
+++ b/deepmd/jax/train/trainer.py
@@ -616,6 +616,7 @@ def _apply_finetune(self) -> None:
             self.models[model_key].change_out_bias(
                 self._sample_funcs[model_key],
                 bias_adjust_mode=bias_mode,
+                apply_preset=True,
             )
 
     def _initialize_stat(self, model_key: str) -> None:
diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py
index 5ce71605b8..88ff961fbb 100644
--- a/deepmd/pd/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pd/model/atomic_model/base_atomic_model.py
@@ -501,6 +501,7 @@ def change_out_bias(
         stat_file_path: DPPath | None = None,
         bias_adjust_mode: str = "change-by-statistic",
         observed_type: list[str] | None = None,
+        apply_preset: bool = False,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -524,8 +525,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, presets are treated as part of the
-            current stored bias and the residual statistics are fitted normally.
+            In 'change-by-statistic' mode, stored presets are ignored unless
+            apply_preset is True for an explicitly provided downstream preset.
+        apply_preset : bool
+            Apply the current configuration's preset during residual fitting.
+            Enable only when the downstream operation explicitly supplies it.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -540,7 +544,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and not change:
+        if self.preset_out_bias and (not change or apply_preset):
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -551,7 +555,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=False,
+                keep_unassigned=change,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat({kk: to_paddle_tensor(vv) for kk, vv in rows.items()})
diff --git a/deepmd/pd/model/model/make_model.py b/deepmd/pd/model/model/make_model.py
index f5beb501fc..294d395e51 100644
--- a/deepmd/pd/model/model/make_model.py
+++ b/deepmd/pd/model/model/make_model.py
@@ -231,6 +231,7 @@ def change_out_bias(
             self,
             merged: list[dict] | Callable[[], list[dict]],
             bias_adjust_mode: str = "change-by-statistic",
+            apply_preset: bool = False,
         ) -> None:
             """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -252,6 +253,7 @@ def change_out_bias(
             self.atomic_model.change_out_bias(
                 merged,
                 bias_adjust_mode=bias_adjust_mode,
+                apply_preset=apply_preset,
             )
 
         def forward_common_lower(
diff --git a/deepmd/pd/train/training.py b/deepmd/pd/train/training.py
index a33908c632..906225235b 100644
--- a/deepmd/pd/train/training.py
+++ b/deepmd/pd/train/training.py
@@ -647,6 +647,7 @@ def single_model_finetune(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule_single.get_random_fitting()
                             else "set-by-statistic",
+                            apply_preset=True,
                         )
                         return _model
 
@@ -1455,11 +1456,13 @@ def model_change_out_bias(
     _model: Any,
     _sample_func: Any,
     _bias_adjust_mode: str = "change-by-statistic",
+    apply_preset: bool = False,
 ) -> None:
     old_bias = deepcopy(_model.get_out_bias())
     _model.change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
+        apply_preset=apply_preset,
     )
     new_bias = deepcopy(_model.get_out_bias())
 
diff --git a/deepmd/pt/model/atomic_model/base_atomic_model.py b/deepmd/pt/model/atomic_model/base_atomic_model.py
index 91c251098f..01a95dad85 100644
--- a/deepmd/pt/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pt/model/atomic_model/base_atomic_model.py
@@ -629,6 +629,7 @@ def change_out_bias(
         bias_adjust_mode: str = "change-by-statistic",
         model_forward: Callable[..., dict[str, torch.Tensor]] | None = None,
         observed_type: list[str] | None = None,
+        apply_preset: bool = False,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -654,8 +655,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, presets are treated as part of the
-            current stored bias and the residual statistics are fitted normally.
+            In 'change-by-statistic' mode, stored presets are ignored unless
+            apply_preset is True for an explicitly provided downstream preset.
+        apply_preset : bool
+            Apply the current configuration's preset during residual fitting.
+            Enable only when the downstream operation explicitly supplies it.
         model_forward : Callable[..., dict[str, torch.Tensor]], optional
             Predictor of the complete atomic outputs used by 'change-by-statistic'.
             Defaults to the forward of this atomic model; a model that adds
@@ -672,7 +676,7 @@ def change_out_bias(
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and not change:
+        if self.preset_out_bias and (not change or apply_preset):
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
@@ -683,7 +687,7 @@ def change_out_bias(
                 to_numpy_array(self.out_bias),
                 self.bias_keys,
                 [self.atomic_output_def()[kk].size for kk in self.bias_keys],
-                keep_unassigned=False,
+                keep_unassigned=change,
                 excluded_types=self.atom_exclude_types,
             )
             self._store_out_stat({kk: to_torch_tensor(vv) for kk, vv in rows.items()})
diff --git a/deepmd/pt/model/model/make_model.py b/deepmd/pt/model/model/make_model.py
index 185122349d..523f93b3cf 100644
--- a/deepmd/pt/model/model/make_model.py
+++ b/deepmd/pt/model/model/make_model.py
@@ -335,6 +335,7 @@ def change_out_bias(
             self,
             merged: Any,
             bias_adjust_mode: str = "change-by-statistic",
+            apply_preset: bool = False,
         ) -> None:
             """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -359,6 +360,7 @@ def change_out_bias(
             self.atomic_model.change_out_bias(
                 merged,
                 bias_adjust_mode=bias_adjust_mode,
+                apply_preset=apply_preset,
                 model_forward=self.predict_atomic_outputs_for_stat,
             )
 
diff --git a/deepmd/pt/model/model/sezm_spin_model.py b/deepmd/pt/model/model/sezm_spin_model.py
index ace082b02b..7cbe965302 100644
--- a/deepmd/pt/model/model/sezm_spin_model.py
+++ b/deepmd/pt/model/model/sezm_spin_model.py
@@ -432,6 +432,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict[str, Any]]] | list[dict[str, Any]],
         bias_adjust_mode: str = "change-by-statistic",
+        apply_preset: bool = False,
     ) -> None:
         """Change output bias using spin-expanded sampled data."""
         spin_sampled_func = self._get_spin_sampled_func(
@@ -440,6 +441,7 @@ def change_out_bias(
         super().change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
+            apply_preset=apply_preset,
         )
 
     def change_type_map(
diff --git a/deepmd/pt/model/model/spin_model.py b/deepmd/pt/model/model/spin_model.py
index 550de0bfa4..cb8c303ce0 100644
--- a/deepmd/pt/model/model/spin_model.py
+++ b/deepmd/pt/model/model/spin_model.py
@@ -518,6 +518,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict]] | list[dict],
         bias_adjust_mode: str = "change-by-statistic",
+        apply_preset: bool = False,
     ) -> None:
         """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -542,6 +543,7 @@ def change_out_bias(
         self.backbone_model.change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
+            apply_preset=apply_preset,
         )
 
     def change_type_map(
diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py
index 7a7210962e..2681344fd6 100644
--- a/deepmd/pt/train/training.py
+++ b/deepmd/pt/train/training.py
@@ -975,6 +975,7 @@ def update_finetune_bias(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule.get_random_fitting()
                             else "set-by-statistic",
+                            apply_preset=True,
                         )
                         if self.multi_task:
                             self.model[_model_key] = model
@@ -2600,6 +2601,7 @@ def model_change_out_bias(
     _model: Any,
     _sample_func: Callable[[], Any],
     _bias_adjust_mode: str = "change-by-statistic",
+    apply_preset: bool = False,
 ) -> Any:
     from deepmd.pt.model.model.dp_model import (
         DPModelCommon,
@@ -2610,4 +2612,5 @@ def model_change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
         recompute_input_stats=isinstance(_model, DPModelCommon),
+        apply_preset=apply_preset,
     )
diff --git a/deepmd/utils/argcheck.py b/deepmd/utils/argcheck.py
index 982c5d2a26..1457bb4ca4 100644
--- a/deepmd/utils/argcheck.py
+++ b/deepmd/utils/argcheck.py
@@ -3646,8 +3646,11 @@ def model_args(
         "for tensor outputs, e.g. `{'dipole': [null, [0., 1., 2.]]}`. "
         "Elements outside the `type_map` are ignored and every element that occurs in the data must be assigned. "
         "A table is resolved once when the input is processed and its values are stored in the model. An assigned "
-        "output is taken from the preset without statistics, both when a model is initialized and when its bias is "
-        "changed by fine-tuning or `dp change-bias`. Dipole models apply no output bias and take no preset."
+        "output is taken from the preset without statistics when a model is initialized. During fine-tuning, "
+        "a preset explicitly provided in the downstream input overrides the loaded bias and skips fitting for "
+        "that output; without a downstream preset, the loaded bias is adjusted by fitting residuals. "
+        "`dp change-bias` in change mode fits residuals without reapplying the model's stored preset. "
+        "Dipole models apply no output bias and take no preset."
     )
     doc_finetune_head = (
         "The chosen fitting net to fine-tune on, when doing multi-task fine-tuning. "
diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 54a3fa792f..5313e9f57d 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -341,6 +341,18 @@ def test_preset_bias(self) -> None:
         )
         assert not np.allclose(out_bias["bar"], bar_bias)
 
+        # An explicit downstream preset overrides the fitted bias.
+        new_foo_bias = foo_bias + 7.0
+        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
+        md0.change_out_bias(
+            self.merged_output_stat,
+            bias_adjust_mode="change-by-statistic",
+            apply_preset=True,
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(out_bias["foo"], new_foo_bias)
+        np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
+
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPDPAtomicModel(
             ds,
diff --git a/source/tests/common/test_dpmodel_train.py b/source/tests/common/test_dpmodel_train.py
index 22149f8e99..884346d710 100644
--- a/source/tests/common/test_dpmodel_train.py
+++ b/source/tests/common/test_dpmodel_train.py
@@ -26,7 +26,8 @@ def __init__(self, bias: float = 0.0) -> None:
     def get_out_bias(self):
         return self.out_bias
 
-    def change_out_bias(self, sample_func, bias_adjust_mode):
+    def change_out_bias(self, sample_func, bias_adjust_mode, apply_preset=False):
+        self.apply_preset = apply_preset
         self.change_calls.append((sample_func, bias_adjust_mode))
         self.out_bias = self.out_bias + 1.0
 
@@ -38,6 +39,17 @@ def get_fitting_net(self):
 
 
 class TestChangeModelOutBias(unittest.TestCase):
+    def test_change_model_out_bias_explicit_preset(self):
+        model = FakeModel()
+
+        def sample_func():
+            return []
+
+        change_model_out_bias(model, sample_func)
+        self.assertFalse(model.apply_preset)
+        change_model_out_bias(model, sample_func, apply_preset=True)
+        self.assertTrue(model.apply_preset)
+
     def test_change_model_out_bias_recomputes_input_stats_when_requested(self):
         model = FakeModel()
 
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index c8ba1e176f..93c3096f27 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -374,6 +374,19 @@ def cvt_ret(x):
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
         )
         assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
+
+        # An explicit downstream preset overrides the fitted bias.
+        new_foo_bias = foo_bias + 7.0
+        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
+        BaseAtomicModel.change_out_bias(
+            md0,
+            self.merged_output_stat,
+            bias_adjust_mode="change-by-statistic",
+            apply_preset=True,
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index 1388d3f16b..81ceec0577 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -400,6 +400,19 @@ def cvt_ret(x):
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
         )
         assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
+
+        # An explicit downstream preset overrides the fitted bias.
+        new_foo_bias = foo_bias + 7.0
+        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
+        BaseAtomicModel.change_out_bias(
+            md0,
+            self.merged_output_stat,
+            bias_adjust_mode="change-by-statistic",
+            apply_preset=True,
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,

From 8cffa358336cdbfdf3b2afff8e4f182038a8b84e Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 12:40:18 +0800
Subject: [PATCH 3/9] fix(model): unify downstream preset bias updates

---
 .../dpmodel/atomic_model/base_atomic_model.py | 23 +++++++++++--------
 deepmd/dpmodel/model/make_model.py            |  6 +++--
 deepmd/dpmodel/model/spin_model.py            |  4 ++--
 deepmd/dpmodel/train/trainer.py               | 10 ++++++--
 deepmd/jax/train/trainer.py                   |  8 ++++++-
 .../model/atomic_model/base_atomic_model.py   | 23 +++++++++++--------
 deepmd/pd/model/model/make_model.py           |  4 ++--
 deepmd/pd/train/training.py                   | 17 ++++++++++----
 .../model/atomic_model/base_atomic_model.py   | 23 +++++++++++--------
 deepmd/pt/model/model/make_model.py           |  4 ++--
 deepmd/pt/model/model/sezm_spin_model.py      |  4 ++--
 deepmd/pt/model/model/spin_model.py           |  4 ++--
 deepmd/pt/train/training.py                   | 14 ++++++++---
 deepmd/utils/argcheck.py                      |  1 +
 .../dpmodel/test_atomic_model_global_stat.py  | 17 ++++++++++++--
 source/tests/common/test_dpmodel_train.py     | 14 +++++++----
 source/tests/jax/test_training.py             |  6 +++++
 .../pd/model/test_atomic_model_global_stat.py | 18 +++++++++++++--
 .../pt/model/test_atomic_model_global_stat.py | 18 +++++++++++++--
 source/tests/pt/test_training.py              |  4 +++-
 20 files changed, 161 insertions(+), 61 deletions(-)

diff --git a/deepmd/dpmodel/atomic_model/base_atomic_model.py b/deepmd/dpmodel/atomic_model/base_atomic_model.py
index ecad9d08b7..871cf15efb 100644
--- a/deepmd/dpmodel/atomic_model/base_atomic_model.py
+++ b/deepmd/dpmodel/atomic_model/base_atomic_model.py
@@ -800,7 +800,7 @@ def change_out_bias(
         stat_file_path: DPPath | None = None,
         bias_adjust_mode: str = "change-by-statistic",
         observed_type: list[str] | None = None,
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -824,11 +824,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored unless
-            apply_preset is True for an explicitly provided downstream preset.
-        apply_preset : bool
-            Apply the current configuration's preset during residual fitting.
-            Enable only when the downstream operation explicitly supplies it.
+            In 'change-by-statistic' mode, stored presets are ignored.
+        preset_out_bias : dict, optional
+            An explicit downstream preset. Assigned outputs use this bias and
+            skip fitting; other outputs fit residuals against the stored bias.
+            In 'set-by-statistic' mode, the model preset is used when omitted.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -843,17 +843,22 @@ def change_out_bias(
         if bias_adjust_mode not in ("change-by-statistic", "set-by-statistic"):
             raise RuntimeError("Unknown bias_adjust_mode mode: " + bias_adjust_mode)
         change = bias_adjust_mode == "change-by-statistic"
+        preset = (
+            normalize_preset_out_bias(preset_out_bias, self.type_map)
+            if preset_out_bias is not None
+            else (None if change else self.preset_out_bias)
+        )
         distinguish_types = self.get_compute_stats_distinguish_types()
-        check_preset_out_bias(self.preset_out_bias, self.bias_keys, distinguish_types)
+        check_preset_out_bias(preset, self.bias_keys, distinguish_types)
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and (not change or apply_preset):
+        if preset:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
             rows = preset_out_bias_rows(
-                self.preset_out_bias,
+                preset,
                 self.type_map,
                 observed_type,
                 to_numpy_array(self.out_bias),
diff --git a/deepmd/dpmodel/model/make_model.py b/deepmd/dpmodel/model/make_model.py
index 3cf8430470..a7cbd0d357 100644
--- a/deepmd/dpmodel/model/make_model.py
+++ b/deepmd/dpmodel/model/make_model.py
@@ -926,7 +926,7 @@ def change_out_bias(
             self,
             merged: Any,
             bias_adjust_mode: str = "change-by-statistic",
-            apply_preset: bool = False,
+            preset_out_bias: dict | None = None,
         ) -> None:
             """Change the output bias according to the input data and the pretrained model.
 
@@ -939,7 +939,9 @@ def change_out_bias(
                 'change-by-statistic' or 'set-by-statistic'.
             """
             self.atomic_model.change_out_bias(
-                merged, bias_adjust_mode=bias_adjust_mode, apply_preset=apply_preset
+                merged,
+                bias_adjust_mode=bias_adjust_mode,
+                preset_out_bias=preset_out_bias,
             )
 
         def _input_type_cast(
diff --git a/deepmd/dpmodel/model/spin_model.py b/deepmd/dpmodel/model/spin_model.py
index 21c83de014..8930e84e35 100644
--- a/deepmd/dpmodel/model/spin_model.py
+++ b/deepmd/dpmodel/model/spin_model.py
@@ -603,7 +603,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict]] | list[dict],
         bias_adjust_mode: str = "change-by-statistic",
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -628,7 +628,7 @@ def change_out_bias(
         self.backbone_model.change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
-            apply_preset=apply_preset,
+            preset_out_bias=preset_out_bias,
         )
 
     def change_type_map(
diff --git a/deepmd/dpmodel/train/trainer.py b/deepmd/dpmodel/train/trainer.py
index 5c6544518b..89c0203571 100644
--- a/deepmd/dpmodel/train/trainer.py
+++ b/deepmd/dpmodel/train/trainer.py
@@ -74,14 +74,14 @@ def change_model_out_bias(
     *,
     bias_adjust_mode: str = "change-by-statistic",
     recompute_input_stats: bool = False,
-    apply_preset: bool = False,
+    preset_out_bias: dict | None = None,
 ) -> Any:
     """Change one model's output bias and log the before/after values."""
     old_bias = deepcopy(model.get_out_bias())
     model.change_out_bias(
         sample_func,
         bias_adjust_mode=bias_adjust_mode,
-        apply_preset=apply_preset,
+        preset_out_bias=preset_out_bias,
     )
     new_bias = deepcopy(model.get_out_bias())
 
@@ -104,6 +104,7 @@ def change_model_out_bias_by_task(
     *,
     bias_adjust_mode: str = "change-by-statistic",
     recompute_input_stats: bool = False,
+    preset_out_bias_by_task: Mapping[str, dict | None] | None = None,
 ) -> MutableMapping[str, Any]:
     """Change output bias for all requested training-task models."""
     log.info("Changing output bias after training.")
@@ -113,6 +114,11 @@ def change_model_out_bias_by_task(
             sample_funcs[model_key],
             bias_adjust_mode=bias_adjust_mode,
             recompute_input_stats=recompute_input_stats,
+            preset_out_bias=(
+                preset_out_bias_by_task.get(model_key)
+                if preset_out_bias_by_task is not None
+                else None
+            ),
         )
     return models
 
diff --git a/deepmd/jax/train/trainer.py b/deepmd/jax/train/trainer.py
index 3194398ded..f906d82eb3 100644
--- a/deepmd/jax/train/trainer.py
+++ b/deepmd/jax/train/trainer.py
@@ -616,7 +616,9 @@ def _apply_finetune(self) -> None:
             self.models[model_key].change_out_bias(
                 self._sample_funcs[model_key],
                 bias_adjust_mode=bias_mode,
-                apply_preset=True,
+                preset_out_bias=self.model_params_by_task[model_key].get(
+                    "preset_out_bias"
+                ),
             )
 
     def _initialize_stat(self, model_key: str) -> None:
@@ -929,6 +931,10 @@ def _change_bias_after_training(self) -> None:
                 self._sample_funcs,
                 self.model_keys,
                 bias_adjust_mode="change-by-statistic",
+                preset_out_bias_by_task={
+                    key: self.model_params_by_task[key].get("preset_out_bias")
+                    for key in self.model_keys
+                },
             )
         self._broadcast_model_states()
 
diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py
index 88ff961fbb..5ae71b42c7 100644
--- a/deepmd/pd/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pd/model/atomic_model/base_atomic_model.py
@@ -501,7 +501,7 @@ def change_out_bias(
         stat_file_path: DPPath | None = None,
         bias_adjust_mode: str = "change-by-statistic",
         observed_type: list[str] | None = None,
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -525,11 +525,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored unless
-            apply_preset is True for an explicitly provided downstream preset.
-        apply_preset : bool
-            Apply the current configuration's preset during residual fitting.
-            Enable only when the downstream operation explicitly supplies it.
+            In 'change-by-statistic' mode, stored presets are ignored.
+        preset_out_bias : dict, optional
+            An explicit downstream preset. Assigned outputs use this bias and
+            skip fitting; other outputs fit residuals against the stored bias.
+            In 'set-by-statistic' mode, the model preset is used when omitted.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -539,17 +539,22 @@ def change_out_bias(
         if bias_adjust_mode not in ("change-by-statistic", "set-by-statistic"):
             raise RuntimeError("Unknown bias_adjust_mode mode: " + bias_adjust_mode)
         change = bias_adjust_mode == "change-by-statistic"
+        preset = (
+            normalize_preset_out_bias(preset_out_bias, self.type_map)
+            if preset_out_bias is not None
+            else (None if change else self.preset_out_bias)
+        )
         distinguish_types = self.get_compute_stats_distinguish_types()
-        check_preset_out_bias(self.preset_out_bias, self.bias_keys, distinguish_types)
+        check_preset_out_bias(preset, self.bias_keys, distinguish_types)
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and (not change or apply_preset):
+        if preset:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
             rows = preset_out_bias_rows(
-                self.preset_out_bias,
+                preset,
                 self.type_map,
                 observed_type,
                 to_numpy_array(self.out_bias),
diff --git a/deepmd/pd/model/model/make_model.py b/deepmd/pd/model/model/make_model.py
index 294d395e51..2d0a288754 100644
--- a/deepmd/pd/model/model/make_model.py
+++ b/deepmd/pd/model/model/make_model.py
@@ -231,7 +231,7 @@ def change_out_bias(
             self,
             merged: list[dict] | Callable[[], list[dict]],
             bias_adjust_mode: str = "change-by-statistic",
-            apply_preset: bool = False,
+            preset_out_bias: dict | None = None,
         ) -> None:
             """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -253,7 +253,7 @@ def change_out_bias(
             self.atomic_model.change_out_bias(
                 merged,
                 bias_adjust_mode=bias_adjust_mode,
-                apply_preset=apply_preset,
+                preset_out_bias=preset_out_bias,
             )
 
         def forward_common_lower(
diff --git a/deepmd/pd/train/training.py b/deepmd/pd/train/training.py
index 906225235b..ccce989229 100644
--- a/deepmd/pd/train/training.py
+++ b/deepmd/pd/train/training.py
@@ -640,6 +640,7 @@ def single_model_finetune(
                         _model: Any,
                         _finetune_rule_single: Any,
                         _sample_func: Any,
+                        _model_params: dict,
                     ) -> Any:
                         _model = model_change_out_bias(
                             _model,
@@ -647,14 +648,17 @@ def single_model_finetune(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule_single.get_random_fitting()
                             else "set-by-statistic",
-                            apply_preset=True,
+                            preset_out_bias=_model_params.get("preset_out_bias"),
                         )
                         return _model
 
                     if not self.multi_task:
                         finetune_rule_single = self.finetune_links["Default"]
                         self.model = single_model_finetune(
-                            self.model, finetune_rule_single, self.get_sample_func
+                            self.model,
+                            finetune_rule_single,
+                            self.get_sample_func,
+                            model_params,
                         )
                     else:
                         for model_key in self.model_keys:
@@ -667,6 +671,7 @@ def single_model_finetune(
                                     self.model[model_key],
                                     finetune_rule_single,
                                     self.get_sample_func[model_key],
+                                    model_params["model_dict"][model_key],
                                 )
                             else:
                                 log.info(
@@ -1088,6 +1093,7 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                     self.model,
                     self.get_sample_func,
                     _bias_adjust_mode="change-by-statistic",
+                    preset_out_bias=self.wrapper.model_params.get("preset_out_bias"),
                 )
             else:
                 for model_key in self.model_keys:
@@ -1095,6 +1101,9 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                         self.model[model_key],
                         self.get_sample_func[model_key],
                         _bias_adjust_mode="change-by-statistic",
+                        preset_out_bias=self.wrapper.model_params["model_dict"][
+                            model_key
+                        ].get("preset_out_bias"),
                     )
             self.latest_model = Path(self.save_ckpt + f"-{self.num_steps}.pd")
             cur_lr = self.lr_schedule.value(self.num_steps - 1)
@@ -1456,13 +1465,13 @@ def model_change_out_bias(
     _model: Any,
     _sample_func: Any,
     _bias_adjust_mode: str = "change-by-statistic",
-    apply_preset: bool = False,
+    preset_out_bias: dict | None = None,
 ) -> None:
     old_bias = deepcopy(_model.get_out_bias())
     _model.change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
-        apply_preset=apply_preset,
+        preset_out_bias=preset_out_bias,
     )
     new_bias = deepcopy(_model.get_out_bias())
 
diff --git a/deepmd/pt/model/atomic_model/base_atomic_model.py b/deepmd/pt/model/atomic_model/base_atomic_model.py
index 01a95dad85..82cc7829f9 100644
--- a/deepmd/pt/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pt/model/atomic_model/base_atomic_model.py
@@ -629,7 +629,7 @@ def change_out_bias(
         bias_adjust_mode: str = "change-by-statistic",
         model_forward: Callable[..., dict[str, torch.Tensor]] | None = None,
         observed_type: list[str] | None = None,
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change the output bias according to the input data and the pretrained model.
 
@@ -655,11 +655,11 @@ def change_out_bias(
             preset value, and the types absent from the data keep zero; no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored unless
-            apply_preset is True for an explicitly provided downstream preset.
-        apply_preset : bool
-            Apply the current configuration's preset during residual fitting.
-            Enable only when the downstream operation explicitly supplies it.
+            In 'change-by-statistic' mode, stored presets are ignored.
+        preset_out_bias : dict, optional
+            An explicit downstream preset. Assigned outputs use this bias and
+            skip fitting; other outputs fit residuals against the stored bias.
+            In 'set-by-statistic' mode, the model preset is used when omitted.
         model_forward : Callable[..., dict[str, torch.Tensor]], optional
             Predictor of the complete atomic outputs used by 'change-by-statistic'.
             Defaults to the forward of this atomic model; a model that adds
@@ -671,17 +671,22 @@ def change_out_bias(
         if bias_adjust_mode not in ("change-by-statistic", "set-by-statistic"):
             raise RuntimeError("Unknown bias_adjust_mode mode: " + bias_adjust_mode)
         change = bias_adjust_mode == "change-by-statistic"
+        preset = (
+            normalize_preset_out_bias(preset_out_bias, self.type_map)
+            if preset_out_bias is not None
+            else (None if change else self.preset_out_bias)
+        )
         distinguish_types = self.get_compute_stats_distinguish_types()
-        check_preset_out_bias(self.preset_out_bias, self.bias_keys, distinguish_types)
+        check_preset_out_bias(preset, self.bias_keys, distinguish_types)
         sampled = sample_merged
         # === Step 1. Outputs fixed by the preset ===
         fitted_keys = self.bias_keys
-        if self.preset_out_bias and (not change or apply_preset):
+        if preset:
             if observed_type is None:
                 sampled = sample_merged() if callable(sample_merged) else sample_merged
                 observed_type = collect_observed_types(sampled, self.type_map)
             rows = preset_out_bias_rows(
-                self.preset_out_bias,
+                preset,
                 self.type_map,
                 observed_type,
                 to_numpy_array(self.out_bias),
diff --git a/deepmd/pt/model/model/make_model.py b/deepmd/pt/model/model/make_model.py
index 523f93b3cf..5bf5af1967 100644
--- a/deepmd/pt/model/model/make_model.py
+++ b/deepmd/pt/model/model/make_model.py
@@ -335,7 +335,7 @@ def change_out_bias(
             self,
             merged: Any,
             bias_adjust_mode: str = "change-by-statistic",
-            apply_preset: bool = False,
+            preset_out_bias: dict | None = None,
         ) -> None:
             """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -360,7 +360,7 @@ def change_out_bias(
             self.atomic_model.change_out_bias(
                 merged,
                 bias_adjust_mode=bias_adjust_mode,
-                apply_preset=apply_preset,
+                preset_out_bias=preset_out_bias,
                 model_forward=self.predict_atomic_outputs_for_stat,
             )
 
diff --git a/deepmd/pt/model/model/sezm_spin_model.py b/deepmd/pt/model/model/sezm_spin_model.py
index 7cbe965302..1a5389e3f9 100644
--- a/deepmd/pt/model/model/sezm_spin_model.py
+++ b/deepmd/pt/model/model/sezm_spin_model.py
@@ -432,7 +432,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict[str, Any]]] | list[dict[str, Any]],
         bias_adjust_mode: str = "change-by-statistic",
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change output bias using spin-expanded sampled data."""
         spin_sampled_func = self._get_spin_sampled_func(
@@ -441,7 +441,7 @@ def change_out_bias(
         super().change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
-            apply_preset=apply_preset,
+            preset_out_bias=preset_out_bias,
         )
 
     def change_type_map(
diff --git a/deepmd/pt/model/model/spin_model.py b/deepmd/pt/model/model/spin_model.py
index cb8c303ce0..5197f6d16b 100644
--- a/deepmd/pt/model/model/spin_model.py
+++ b/deepmd/pt/model/model/spin_model.py
@@ -518,7 +518,7 @@ def change_out_bias(
         self,
         merged: Callable[[], list[dict]] | list[dict],
         bias_adjust_mode: str = "change-by-statistic",
-        apply_preset: bool = False,
+        preset_out_bias: dict | None = None,
     ) -> None:
         """Change the output bias of atomic model according to the input data and the pretrained model.
 
@@ -543,7 +543,7 @@ def change_out_bias(
         self.backbone_model.change_out_bias(
             spin_sampled_func,
             bias_adjust_mode=bias_adjust_mode,
-            apply_preset=apply_preset,
+            preset_out_bias=preset_out_bias,
         )
 
     def change_type_map(
diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py
index 2681344fd6..7b73165a38 100644
--- a/deepmd/pt/train/training.py
+++ b/deepmd/pt/train/training.py
@@ -975,7 +975,11 @@ def update_finetune_bias(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule.get_random_fitting()
                             else "set-by-statistic",
-                            apply_preset=True,
+                            preset_out_bias=(
+                                model_params["model_dict"][_model_key]
+                                if self.multi_task
+                                else model_params
+                            ).get("preset_out_bias"),
                         )
                         if self.multi_task:
                             self.model[_model_key] = model
@@ -1872,6 +1876,7 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                     self.model,
                     self.get_sample_func,
                     _bias_adjust_mode="change-by-statistic",
+                    preset_out_bias=self.wrapper.model_params.get("preset_out_bias"),
                 )
             else:
                 for model_key in self.model_keys:
@@ -1879,6 +1884,9 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                         self.model[model_key],
                         self.get_sample_func[model_key],
                         _bias_adjust_mode="change-by-statistic",
+                        preset_out_bias=self.wrapper.model_params["model_dict"][
+                            model_key
+                        ].get("preset_out_bias"),
                     )
             self.latest_model = self.ckpt_store.path_for(self.num_steps)
             cur_lr = self.lr_schedule.value(self.num_steps - 1)
@@ -2601,7 +2609,7 @@ def model_change_out_bias(
     _model: Any,
     _sample_func: Callable[[], Any],
     _bias_adjust_mode: str = "change-by-statistic",
-    apply_preset: bool = False,
+    preset_out_bias: dict | None = None,
 ) -> Any:
     from deepmd.pt.model.model.dp_model import (
         DPModelCommon,
@@ -2612,5 +2620,5 @@ def model_change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
         recompute_input_stats=isinstance(_model, DPModelCommon),
-        apply_preset=apply_preset,
+        preset_out_bias=preset_out_bias,
     )
diff --git a/deepmd/utils/argcheck.py b/deepmd/utils/argcheck.py
index 1457bb4ca4..4632c2bff8 100644
--- a/deepmd/utils/argcheck.py
+++ b/deepmd/utils/argcheck.py
@@ -3649,6 +3649,7 @@ def model_args(
         "output is taken from the preset without statistics when a model is initialized. During fine-tuning, "
         "a preset explicitly provided in the downstream input overrides the loaded bias and skips fitting for "
         "that output; without a downstream preset, the loaded bias is adjusted by fitting residuals. "
+        "Post-training bias updates use the same preset from the current training input. "
         "`dp change-bias` in change mode fits residuals without reapplying the model's stored preset. "
         "Dipole models apply no output bias and take no preset."
     )
diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 5313e9f57d..3f0b4ae875 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -340,19 +340,32 @@ def test_preset_bias(self) -> None:
             out_bias["foo"], np.array([2.0, -5.0]).reshape(2, 1)
         )
         assert not np.allclose(out_bias["bar"], bar_bias)
+        fitted_bar_bias = out_bias["bar"].copy()
 
         # An explicit downstream preset overrides the fitted bias.
         new_foo_bias = foo_bias + 7.0
-        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
         md0.change_out_bias(
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            apply_preset=True,
+            preset_out_bias={
+                "foo": new_foo_bias.tolist(),
+                "bar": bar_bias.tolist(),
+            },
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(out_bias["foo"], new_foo_bias)
         np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
 
+        # Presets for other outputs in the checkpoint are not downstream inputs.
+        md0.change_out_bias(
+            self.merged_output_stat,
+            preset_out_bias={"foo": new_foo_bias.tolist()},
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(out_bias["foo"], new_foo_bias)
+        np.testing.assert_almost_equal(out_bias["bar"], fitted_bar_bias)
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
+
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPDPAtomicModel(
             ds,
diff --git a/source/tests/common/test_dpmodel_train.py b/source/tests/common/test_dpmodel_train.py
index 884346d710..d97bc1665b 100644
--- a/source/tests/common/test_dpmodel_train.py
+++ b/source/tests/common/test_dpmodel_train.py
@@ -26,8 +26,8 @@ def __init__(self, bias: float = 0.0) -> None:
     def get_out_bias(self):
         return self.out_bias
 
-    def change_out_bias(self, sample_func, bias_adjust_mode, apply_preset=False):
-        self.apply_preset = apply_preset
+    def change_out_bias(self, sample_func, bias_adjust_mode, preset_out_bias=None):
+        self.preset_out_bias = preset_out_bias
         self.change_calls.append((sample_func, bias_adjust_mode))
         self.out_bias = self.out_bias + 1.0
 
@@ -46,9 +46,10 @@ def sample_func():
             return []
 
         change_model_out_bias(model, sample_func)
-        self.assertFalse(model.apply_preset)
-        change_model_out_bias(model, sample_func, apply_preset=True)
-        self.assertTrue(model.apply_preset)
+        self.assertIsNone(model.preset_out_bias)
+        preset = {"energy": [1.0, 2.0]}
+        change_model_out_bias(model, sample_func, preset_out_bias=preset)
+        self.assertEqual(model.preset_out_bias, preset)
 
     def test_change_model_out_bias_recomputes_input_stats_when_requested(self):
         model = FakeModel()
@@ -82,9 +83,12 @@ def test_change_model_out_bias_by_task_updates_all_models(self):
             models,
             sample_funcs,
             ["task_a", "task_b"],
+            preset_out_bias_by_task={"task_a": {"energy": [1.0, 2.0]}},
         )
 
         self.assertIs(returned, models)
+        self.assertEqual(models["task_a"].preset_out_bias, {"energy": [1.0, 2.0]})
+        self.assertIsNone(models["task_b"].preset_out_bias)
         np.testing.assert_allclose(models["task_a"].get_out_bias(), np.ones((1, 2, 1)))
         np.testing.assert_allclose(
             models["task_b"].get_out_bias(),
diff --git a/source/tests/jax/test_training.py b/source/tests/jax/test_training.py
index 913a851fe3..76eb252bbe 100644
--- a/source/tests/jax/test_training.py
+++ b/source/tests/jax/test_training.py
@@ -753,6 +753,9 @@ def _bias_sync_trainer(rank: int) -> DPTrainer:
     trainer.models = {DEFAULT_TASK_KEY: _BiasModel(0.0)}
     trainer._sample_funcs = {DEFAULT_TASK_KEY: object()}
     trainer.model_keys = [DEFAULT_TASK_KEY]
+    trainer.model_params_by_task = {
+        DEFAULT_TASK_KEY: {"preset_out_bias": {"energy": [1.0]}}
+    }
     return trainer
 
 
@@ -777,6 +780,9 @@ def change_bias(models, *args, **kwargs) -> None:
         trainer._change_bias_after_training()
 
     change_model_out_bias_by_task.assert_called_once()
+    assert change_model_out_bias_by_task.call_args.kwargs[
+        "preset_out_bias_by_task"
+    ] == {DEFAULT_TASK_KEY: {"energy": [1.0]}}
     broadcast_one_to_all.assert_called_once()
     assert broadcast_one_to_all.call_args.kwargs["is_source"] is True
     np.testing.assert_allclose(
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index 93c3096f27..0cca5e2025 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -374,19 +374,33 @@ def cvt_ret(x):
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
         )
         assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
+        fitted_bar_bias = to_numpy_array(out_bias["bar"]).copy()
 
         # An explicit downstream preset overrides the fitted bias.
         new_foo_bias = foo_bias + 7.0
-        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
         BaseAtomicModel.change_out_bias(
             md0,
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            apply_preset=True,
+            preset_out_bias={
+                "foo": new_foo_bias.tolist(),
+                "bar": bar_bias.tolist(),
+            },
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
         np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+
+        # Presets for other outputs in the checkpoint are not downstream inputs.
+        BaseAtomicModel.change_out_bias(
+            md0,
+            self.merged_output_stat,
+            preset_out_bias={"foo": new_foo_bias.tolist()},
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), fitted_bar_bias)
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index 81ceec0577..57962c8a1d 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -400,19 +400,33 @@ def cvt_ret(x):
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
         )
         assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
+        fitted_bar_bias = to_numpy_array(out_bias["bar"]).copy()
 
         # An explicit downstream preset overrides the fitted bias.
         new_foo_bias = foo_bias + 7.0
-        md0.preset_out_bias["foo"] = new_foo_bias.tolist()
         BaseAtomicModel.change_out_bias(
             md0,
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            apply_preset=True,
+            preset_out_bias={
+                "foo": new_foo_bias.tolist(),
+                "bar": bar_bias.tolist(),
+            },
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
         np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+
+        # Presets for other outputs in the checkpoint are not downstream inputs.
+        BaseAtomicModel.change_out_bias(
+            md0,
+            self.merged_output_stat,
+            preset_out_bias={"foo": new_foo_bias.tolist()},
+        )
+        out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), fitted_bar_bias)
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/test_training.py b/source/tests/pt/test_training.py
index 9cce8c02aa..b7dcba84c2 100644
--- a/source/tests/pt/test_training.py
+++ b/source/tests/pt/test_training.py
@@ -1388,7 +1388,9 @@ def test_ema_checkpoint_cleanup_removes_future_steps(self) -> None:
     def test_ema_checkpoint_keeps_changed_out_bias(
         self, mocked_change_out_bias
     ) -> None:
-        def change_out_bias(model, sample_func, _bias_adjust_mode):
+        def change_out_bias(
+            model, sample_func, _bias_adjust_mode, preset_out_bias=None
+        ):
             model.set_out_bias(model.get_out_bias() + 1.0)
             return model
 

From f682c8d10438bb10c69467ec0951bf1cba79c2b2 Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 13:13:51 +0800
Subject: [PATCH 4/9] fix(cli): scope preset bias override to standalone
 change-bias

---
 .../dpmodel/atomic_model/base_atomic_model.py | 13 ++---
 deepmd/dpmodel/train/trainer.py               | 11 ++--
 deepmd/jax/train/trainer.py                   |  7 ---
 deepmd/pd/entrypoints/main.py                 |  5 +-
 .../model/atomic_model/base_atomic_model.py   | 13 ++---
 deepmd/pd/train/training.py                   | 17 ++----
 deepmd/pt/entrypoints/main.py                 |  5 +-
 .../model/atomic_model/base_atomic_model.py   | 13 ++---
 deepmd/pt/train/training.py                   |  9 ----
 deepmd/utils/argcheck.py                      |  8 ++-
 .../dpmodel/test_atomic_model_global_stat.py  | 49 ++++++-----------
 source/tests/common/test_dpmodel_train.py     | 18 +------
 source/tests/jax/test_training.py             |  6 ---
 .../pd/model/test_atomic_model_global_stat.py | 53 ++++++-------------
 .../pt/model/test_atomic_model_global_stat.py | 53 ++++++-------------
 source/tests/pt/test_change_bias.py           | 26 +++++++++
 source/tests/pt/test_training.py              |  4 +-
 17 files changed, 120 insertions(+), 190 deletions(-)

diff --git a/deepmd/dpmodel/atomic_model/base_atomic_model.py b/deepmd/dpmodel/atomic_model/base_atomic_model.py
index 871cf15efb..b7243ea4ea 100644
--- a/deepmd/dpmodel/atomic_model/base_atomic_model.py
+++ b/deepmd/dpmodel/atomic_model/base_atomic_model.py
@@ -818,17 +818,18 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
-            is fixed by the preset:
+            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero; no
+            preset value, and the types absent from the data keep zero
+            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored.
         preset_out_bias : dict, optional
             An explicit downstream preset. Assigned outputs use this bias and
             skip fitting; other outputs fit residuals against the stored bias.
-            In 'set-by-statistic' mode, the model preset is used when omitted.
+            The model preset is used when omitted, preserving training and
+            fine-tuning behavior. Pass an empty dict to fit from the data
+            without reapplying the model's stored preset.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -846,7 +847,7 @@ def change_out_bias(
         preset = (
             normalize_preset_out_bias(preset_out_bias, self.type_map)
             if preset_out_bias is not None
-            else (None if change else self.preset_out_bias)
+            else self.preset_out_bias
         )
         distinguish_types = self.get_compute_stats_distinguish_types()
         check_preset_out_bias(preset, self.bias_keys, distinguish_types)
diff --git a/deepmd/dpmodel/train/trainer.py b/deepmd/dpmodel/train/trainer.py
index 89c0203571..d2dd7703a5 100644
--- a/deepmd/dpmodel/train/trainer.py
+++ b/deepmd/dpmodel/train/trainer.py
@@ -78,10 +78,13 @@ def change_model_out_bias(
 ) -> Any:
     """Change one model's output bias and log the before/after values."""
     old_bias = deepcopy(model.get_out_bias())
+    preset_kwargs = (
+        {"preset_out_bias": preset_out_bias} if preset_out_bias is not None else {}
+    )
     model.change_out_bias(
         sample_func,
         bias_adjust_mode=bias_adjust_mode,
-        preset_out_bias=preset_out_bias,
+        **preset_kwargs,
     )
     new_bias = deepcopy(model.get_out_bias())
 
@@ -104,7 +107,6 @@ def change_model_out_bias_by_task(
     *,
     bias_adjust_mode: str = "change-by-statistic",
     recompute_input_stats: bool = False,
-    preset_out_bias_by_task: Mapping[str, dict | None] | None = None,
 ) -> MutableMapping[str, Any]:
     """Change output bias for all requested training-task models."""
     log.info("Changing output bias after training.")
@@ -114,11 +116,6 @@ def change_model_out_bias_by_task(
             sample_funcs[model_key],
             bias_adjust_mode=bias_adjust_mode,
             recompute_input_stats=recompute_input_stats,
-            preset_out_bias=(
-                preset_out_bias_by_task.get(model_key)
-                if preset_out_bias_by_task is not None
-                else None
-            ),
         )
     return models
 
diff --git a/deepmd/jax/train/trainer.py b/deepmd/jax/train/trainer.py
index f906d82eb3..a35de2a49b 100644
--- a/deepmd/jax/train/trainer.py
+++ b/deepmd/jax/train/trainer.py
@@ -616,9 +616,6 @@ def _apply_finetune(self) -> None:
             self.models[model_key].change_out_bias(
                 self._sample_funcs[model_key],
                 bias_adjust_mode=bias_mode,
-                preset_out_bias=self.model_params_by_task[model_key].get(
-                    "preset_out_bias"
-                ),
             )
 
     def _initialize_stat(self, model_key: str) -> None:
@@ -931,10 +928,6 @@ def _change_bias_after_training(self) -> None:
                 self._sample_funcs,
                 self.model_keys,
                 bias_adjust_mode="change-by-statistic",
-                preset_out_bias_by_task={
-                    key: self.model_params_by_task[key].get("preset_out_bias")
-                    for key in self.model_keys
-                },
             )
         self._broadcast_model_states()
 
diff --git a/deepmd/pd/entrypoints/main.py b/deepmd/pd/entrypoints/main.py
index cf15e99192..237c860125 100644
--- a/deepmd/pd/entrypoints/main.py
+++ b/deepmd/pd/entrypoints/main.py
@@ -552,7 +552,10 @@ def change_bias(
             nbatches,
         )
         updated_model = training.model_change_out_bias(
-            model_to_change, sampled_data, _bias_adjust_mode=bias_adjust_mode
+            model_to_change,
+            sampled_data,
+            _bias_adjust_mode=bias_adjust_mode,
+            preset_out_bias={},
         )
 
     if not multi_task:
diff --git a/deepmd/pd/model/atomic_model/base_atomic_model.py b/deepmd/pd/model/atomic_model/base_atomic_model.py
index 5ae71b42c7..7618ce7ee3 100644
--- a/deepmd/pd/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pd/model/atomic_model/base_atomic_model.py
@@ -519,17 +519,18 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
-            is fixed by the preset:
+            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero; no
+            preset value, and the types absent from the data keep zero
+            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored.
         preset_out_bias : dict, optional
             An explicit downstream preset. Assigned outputs use this bias and
             skip fitting; other outputs fit residuals against the stored bias.
-            In 'set-by-statistic' mode, the model preset is used when omitted.
+            The model preset is used when omitted, preserving training and
+            fine-tuning behavior. Pass an empty dict to fit from the data
+            without reapplying the model's stored preset.
         stat_file_path : Optional[DPPath]
             The path to the stat file.
         observed_type : list[str], optional
@@ -542,7 +543,7 @@ def change_out_bias(
         preset = (
             normalize_preset_out_bias(preset_out_bias, self.type_map)
             if preset_out_bias is not None
-            else (None if change else self.preset_out_bias)
+            else self.preset_out_bias
         )
         distinguish_types = self.get_compute_stats_distinguish_types()
         check_preset_out_bias(preset, self.bias_keys, distinguish_types)
diff --git a/deepmd/pd/train/training.py b/deepmd/pd/train/training.py
index ccce989229..7db7d89895 100644
--- a/deepmd/pd/train/training.py
+++ b/deepmd/pd/train/training.py
@@ -640,7 +640,6 @@ def single_model_finetune(
                         _model: Any,
                         _finetune_rule_single: Any,
                         _sample_func: Any,
-                        _model_params: dict,
                     ) -> Any:
                         _model = model_change_out_bias(
                             _model,
@@ -648,17 +647,13 @@ def single_model_finetune(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule_single.get_random_fitting()
                             else "set-by-statistic",
-                            preset_out_bias=_model_params.get("preset_out_bias"),
                         )
                         return _model
 
                     if not self.multi_task:
                         finetune_rule_single = self.finetune_links["Default"]
                         self.model = single_model_finetune(
-                            self.model,
-                            finetune_rule_single,
-                            self.get_sample_func,
-                            model_params,
+                            self.model, finetune_rule_single, self.get_sample_func
                         )
                     else:
                         for model_key in self.model_keys:
@@ -671,7 +666,6 @@ def single_model_finetune(
                                     self.model[model_key],
                                     finetune_rule_single,
                                     self.get_sample_func[model_key],
-                                    model_params["model_dict"][model_key],
                                 )
                             else:
                                 log.info(
@@ -1093,7 +1087,6 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                     self.model,
                     self.get_sample_func,
                     _bias_adjust_mode="change-by-statistic",
-                    preset_out_bias=self.wrapper.model_params.get("preset_out_bias"),
                 )
             else:
                 for model_key in self.model_keys:
@@ -1101,9 +1094,6 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                         self.model[model_key],
                         self.get_sample_func[model_key],
                         _bias_adjust_mode="change-by-statistic",
-                        preset_out_bias=self.wrapper.model_params["model_dict"][
-                            model_key
-                        ].get("preset_out_bias"),
                     )
             self.latest_model = Path(self.save_ckpt + f"-{self.num_steps}.pd")
             cur_lr = self.lr_schedule.value(self.num_steps - 1)
@@ -1468,10 +1458,13 @@ def model_change_out_bias(
     preset_out_bias: dict | None = None,
 ) -> None:
     old_bias = deepcopy(_model.get_out_bias())
+    preset_kwargs = (
+        {"preset_out_bias": preset_out_bias} if preset_out_bias is not None else {}
+    )
     _model.change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
-        preset_out_bias=preset_out_bias,
+        **preset_kwargs,
     )
     new_bias = deepcopy(_model.get_out_bias())
 
diff --git a/deepmd/pt/entrypoints/main.py b/deepmd/pt/entrypoints/main.py
index da6b890d13..33b90ade7f 100644
--- a/deepmd/pt/entrypoints/main.py
+++ b/deepmd/pt/entrypoints/main.py
@@ -623,7 +623,10 @@ def change_bias(
             nbatches,
         )
         updated_model = training.model_change_out_bias(
-            model_to_change, sampled_data, _bias_adjust_mode=bias_adjust_mode
+            model_to_change,
+            sampled_data,
+            _bias_adjust_mode=bias_adjust_mode,
+            preset_out_bias={},
         )
 
     if not multi_task:
diff --git a/deepmd/pt/model/atomic_model/base_atomic_model.py b/deepmd/pt/model/atomic_model/base_atomic_model.py
index 82cc7829f9..48d26b73ba 100644
--- a/deepmd/pt/model/atomic_model/base_atomic_model.py
+++ b/deepmd/pt/model/atomic_model/base_atomic_model.py
@@ -649,17 +649,18 @@ def change_out_bias(
             'change-by-statistic' : perform predictions on labels of target dataset,
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
-            In 'set-by-statistic' mode, an output assigned in `preset_out_bias`
-            is fixed by the preset:
+            An output assigned in `preset_out_bias` is fixed by the preset in both modes:
             every element in the data must be assigned, the assigned types take the
-            preset value, and the types absent from the data keep zero; no
+            preset value, and the types absent from the data keep zero
+            ('set-by-statistic') or their stored bias ('change-by-statistic'); no
             statistics are computed, read or written for such an output, whose
             output std keeps its stored value.
-            In 'change-by-statistic' mode, stored presets are ignored.
         preset_out_bias : dict, optional
             An explicit downstream preset. Assigned outputs use this bias and
             skip fitting; other outputs fit residuals against the stored bias.
-            In 'set-by-statistic' mode, the model preset is used when omitted.
+            The model preset is used when omitted, preserving training and
+            fine-tuning behavior. Pass an empty dict to fit from the data
+            without reapplying the model's stored preset.
         model_forward : Callable[..., dict[str, torch.Tensor]], optional
             Predictor of the complete atomic outputs used by 'change-by-statistic'.
             Defaults to the forward of this atomic model; a model that adds
@@ -674,7 +675,7 @@ def change_out_bias(
         preset = (
             normalize_preset_out_bias(preset_out_bias, self.type_map)
             if preset_out_bias is not None
-            else (None if change else self.preset_out_bias)
+            else self.preset_out_bias
         )
         distinguish_types = self.get_compute_stats_distinguish_types()
         check_preset_out_bias(preset, self.bias_keys, distinguish_types)
diff --git a/deepmd/pt/train/training.py b/deepmd/pt/train/training.py
index 7b73165a38..205203e865 100644
--- a/deepmd/pt/train/training.py
+++ b/deepmd/pt/train/training.py
@@ -975,11 +975,6 @@ def update_finetune_bias(
                             _bias_adjust_mode="change-by-statistic"
                             if not _finetune_rule.get_random_fitting()
                             else "set-by-statistic",
-                            preset_out_bias=(
-                                model_params["model_dict"][_model_key]
-                                if self.multi_task
-                                else model_params
-                            ).get("preset_out_bias"),
                         )
                         if self.multi_task:
                             self.model[_model_key] = model
@@ -1876,7 +1871,6 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                     self.model,
                     self.get_sample_func,
                     _bias_adjust_mode="change-by-statistic",
-                    preset_out_bias=self.wrapper.model_params.get("preset_out_bias"),
                 )
             else:
                 for model_key in self.model_keys:
@@ -1884,9 +1878,6 @@ def log_loss_valid(_task_key: str = "Default") -> dict:
                         self.model[model_key],
                         self.get_sample_func[model_key],
                         _bias_adjust_mode="change-by-statistic",
-                        preset_out_bias=self.wrapper.model_params["model_dict"][
-                            model_key
-                        ].get("preset_out_bias"),
                     )
             self.latest_model = self.ckpt_store.path_for(self.num_steps)
             cur_lr = self.lr_schedule.value(self.num_steps - 1)
diff --git a/deepmd/utils/argcheck.py b/deepmd/utils/argcheck.py
index 4632c2bff8..2b7698fde2 100644
--- a/deepmd/utils/argcheck.py
+++ b/deepmd/utils/argcheck.py
@@ -3646,11 +3646,9 @@ def model_args(
         "for tensor outputs, e.g. `{'dipole': [null, [0., 1., 2.]]}`. "
         "Elements outside the `type_map` are ignored and every element that occurs in the data must be assigned. "
         "A table is resolved once when the input is processed and its values are stored in the model. An assigned "
-        "output is taken from the preset without statistics when a model is initialized. During fine-tuning, "
-        "a preset explicitly provided in the downstream input overrides the loaded bias and skips fitting for "
-        "that output; without a downstream preset, the loaded bias is adjusted by fitting residuals. "
-        "Post-training bias updates use the same preset from the current training input. "
-        "`dp change-bias` in change mode fits residuals without reapplying the model's stored preset. "
+        "output is taken from the preset without statistics, both when a model is initialized and when its bias is "
+        "changed by fine-tuning. `dp change-bias` fits from its input data without reapplying the model's stored "
+        "preset; explicit `--bias-value` values override the bias directly. "
         "Dipole models apply no output bias and take no preset."
     )
     doc_finetune_head = (
diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 3f0b4ae875..7760cce9cd 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -319,52 +319,37 @@ def test_preset_bias(self) -> None:
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
 
-        # 3. change-by-statistic treats the preset as the stored starting bias
-        # and fits a downstream residual shift.
+        # 3. change-by-statistic keeps every assigned type at its preset
         md0.change_out_bias(
             self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        args_stat = [
-            self.coord_ext,
-            np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
-            self.nlist,
-        ]
-        ret3 = md0.forward_common_atomic(*args_stat)
-        expected_ret3 = {}
-        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
-        expected_ret3["pix"] = ret0["pix"]
-        for kk in ["foo", "pix"]:
-            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
+        ret3 = md0.forward_common_atomic(*args)
+        for kk in ["foo", "pix", "bar"]:
+            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(
-            out_bias["foo"], np.array([2.0, -5.0]).reshape(2, 1)
-        )
-        assert not np.allclose(out_bias["bar"], bar_bias)
-        fitted_bar_bias = out_bias["bar"].copy()
+        np.testing.assert_almost_equal(out_bias["foo"], foo_bias)
+        np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
 
-        # An explicit downstream preset overrides the fitted bias.
-        new_foo_bias = foo_bias + 7.0
+        # Standalone change-bias explicitly ignores the checkpoint preset.
         md0.change_out_bias(
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            preset_out_bias={
-                "foo": new_foo_bias.tolist(),
-                "bar": bar_bias.tolist(),
-            },
+            preset_out_bias={},
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(out_bias["foo"], new_foo_bias)
-        np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
+        np.testing.assert_almost_equal(
+            out_bias["foo"], np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(out_bias["bar"], bar_bias)
 
-        # Presets for other outputs in the checkpoint are not downstream inputs.
+        # The override does not remove the model's configured preset.
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
         md0.change_out_bias(
-            self.merged_output_stat,
-            preset_out_bias={"foo": new_foo_bias.tolist()},
+            self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(out_bias["foo"], new_foo_bias)
-        np.testing.assert_almost_equal(out_bias["bar"], fitted_bar_bias)
-        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
+        np.testing.assert_almost_equal(out_bias["foo"], foo_bias)
+        np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
 
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPDPAtomicModel(
diff --git a/source/tests/common/test_dpmodel_train.py b/source/tests/common/test_dpmodel_train.py
index d97bc1665b..22149f8e99 100644
--- a/source/tests/common/test_dpmodel_train.py
+++ b/source/tests/common/test_dpmodel_train.py
@@ -26,8 +26,7 @@ def __init__(self, bias: float = 0.0) -> None:
     def get_out_bias(self):
         return self.out_bias
 
-    def change_out_bias(self, sample_func, bias_adjust_mode, preset_out_bias=None):
-        self.preset_out_bias = preset_out_bias
+    def change_out_bias(self, sample_func, bias_adjust_mode):
         self.change_calls.append((sample_func, bias_adjust_mode))
         self.out_bias = self.out_bias + 1.0
 
@@ -39,18 +38,6 @@ def get_fitting_net(self):
 
 
 class TestChangeModelOutBias(unittest.TestCase):
-    def test_change_model_out_bias_explicit_preset(self):
-        model = FakeModel()
-
-        def sample_func():
-            return []
-
-        change_model_out_bias(model, sample_func)
-        self.assertIsNone(model.preset_out_bias)
-        preset = {"energy": [1.0, 2.0]}
-        change_model_out_bias(model, sample_func, preset_out_bias=preset)
-        self.assertEqual(model.preset_out_bias, preset)
-
     def test_change_model_out_bias_recomputes_input_stats_when_requested(self):
         model = FakeModel()
 
@@ -83,12 +70,9 @@ def test_change_model_out_bias_by_task_updates_all_models(self):
             models,
             sample_funcs,
             ["task_a", "task_b"],
-            preset_out_bias_by_task={"task_a": {"energy": [1.0, 2.0]}},
         )
 
         self.assertIs(returned, models)
-        self.assertEqual(models["task_a"].preset_out_bias, {"energy": [1.0, 2.0]})
-        self.assertIsNone(models["task_b"].preset_out_bias)
         np.testing.assert_allclose(models["task_a"].get_out_bias(), np.ones((1, 2, 1)))
         np.testing.assert_allclose(
             models["task_b"].get_out_bias(),
diff --git a/source/tests/jax/test_training.py b/source/tests/jax/test_training.py
index 76eb252bbe..913a851fe3 100644
--- a/source/tests/jax/test_training.py
+++ b/source/tests/jax/test_training.py
@@ -753,9 +753,6 @@ def _bias_sync_trainer(rank: int) -> DPTrainer:
     trainer.models = {DEFAULT_TASK_KEY: _BiasModel(0.0)}
     trainer._sample_funcs = {DEFAULT_TASK_KEY: object()}
     trainer.model_keys = [DEFAULT_TASK_KEY]
-    trainer.model_params_by_task = {
-        DEFAULT_TASK_KEY: {"preset_out_bias": {"energy": [1.0]}}
-    }
     return trainer
 
 
@@ -780,9 +777,6 @@ def change_bias(models, *args, **kwargs) -> None:
         trainer._change_bias_after_training()
 
     change_model_out_bias_by_task.assert_called_once()
-    assert change_model_out_bias_by_task.call_args.kwargs[
-        "preset_out_bias_by_task"
-    ] == {DEFAULT_TASK_KEY: {"energy": [1.0]}}
     broadcast_one_to_all.assert_called_once()
     assert broadcast_one_to_all.call_args.kwargs["is_source"] is True
     np.testing.assert_allclose(
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index 0cca5e2025..ff747eb518 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -349,58 +349,39 @@ def cvt_ret(x):
         expected_ret1["bar"] = ret0["bar"] + bar_bias[at]
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
-        # 3. change-by-statistic treats the preset as the stored starting bias
-        # and fits a downstream residual shift.
+        # 3. change-by-statistic keeps every assigned type at its preset
         BaseAtomicModel.change_out_bias(
             md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        args_stat = [
-            to_paddle_tensor(ii)
-            for ii in [
-                self.coord_ext,
-                np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
-                self.nlist,
-            ]
-        ]
-        ret3 = md0.forward_common_atomic(*args_stat)
+        ret3 = md0.forward_common_atomic(*args)
         ret3 = cvt_ret(ret3)
-        expected_ret3 = {}
-        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
-        expected_ret3["pix"] = ret0["pix"]
-        for kk in ["foo", "pix"]:
-            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
+        for kk in ["foo", "pix", "bar"]:
+            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(
-            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
-        )
-        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
-        fitted_bar_bias = to_numpy_array(out_bias["bar"]).copy()
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
 
-        # An explicit downstream preset overrides the fitted bias.
-        new_foo_bias = foo_bias + 7.0
+        # Standalone change-bias explicitly ignores the checkpoint preset.
         BaseAtomicModel.change_out_bias(
             md0,
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            preset_out_bias={
-                "foo": new_foo_bias.tolist(),
-                "bar": bar_bias.tolist(),
-            },
+            preset_out_bias={},
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+        np.testing.assert_almost_equal(
+            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
 
-        # Presets for other outputs in the checkpoint are not downstream inputs.
+        # The override does not remove the model's configured preset.
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
         BaseAtomicModel.change_out_bias(
-            md0,
-            self.merged_output_stat,
-            preset_out_bias={"foo": new_foo_bias.tolist()},
+            md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), fitted_bar_bias)
-        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index 57962c8a1d..3e304ee1d7 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -375,58 +375,39 @@ def cvt_ret(x):
         expected_ret1["bar"] = ret0["bar"] + bar_bias[at]
         for kk in ["foo", "pix", "bar"]:
             np.testing.assert_almost_equal(ret1[kk], expected_ret1[kk])
-        # 3. change-by-statistic treats the preset as the stored starting bias
-        # and fits a downstream residual shift.
+        # 3. change-by-statistic keeps every assigned type at its preset
         BaseAtomicModel.change_out_bias(
             md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
-        args_stat = [
-            to_torch_tensor(ii)
-            for ii in [
-                self.coord_ext,
-                np.array(self.merged_output_stat[0]["atype_ext"], dtype=np.int64),
-                self.nlist,
-            ]
-        ]
-        ret3 = md0.forward_common_atomic(*args_stat, fparam=self.fparam)
+        ret3 = md0.forward_common_atomic(*args, fparam=self.fparam)
         ret3 = cvt_ret(ret3)
-        expected_ret3 = {}
-        expected_ret3["foo"] = np.array([[3, 4, -2], [6, 0, 1]]).reshape(2, 3, 1)
-        expected_ret3["pix"] = ret0["pix"]
-        for kk in ["foo", "pix"]:
-            np.testing.assert_almost_equal(ret3[kk], expected_ret3[kk])
+        for kk in ["foo", "pix", "bar"]:
+            np.testing.assert_almost_equal(ret3[kk], ret1[kk])
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(
-            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
-        )
-        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
-        fitted_bar_bias = to_numpy_array(out_bias["bar"]).copy()
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
 
-        # An explicit downstream preset overrides the fitted bias.
-        new_foo_bias = foo_bias + 7.0
+        # Standalone change-bias explicitly ignores the checkpoint preset.
         BaseAtomicModel.change_out_bias(
             md0,
             self.merged_output_stat,
             bias_adjust_mode="change-by-statistic",
-            preset_out_bias={
-                "foo": new_foo_bias.tolist(),
-                "bar": bar_bias.tolist(),
-            },
+            preset_out_bias={},
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
+        np.testing.assert_almost_equal(
+            to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
+        )
+        assert not np.allclose(to_numpy_array(out_bias["bar"]), bar_bias)
 
-        # Presets for other outputs in the checkpoint are not downstream inputs.
+        # The override does not remove the model's configured preset.
+        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
         BaseAtomicModel.change_out_bias(
-            md0,
-            self.merged_output_stat,
-            preset_out_bias={"foo": new_foo_bias.tolist()},
+            md0, self.merged_output_stat, bias_adjust_mode="change-by-statistic"
         )
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), new_foo_bias)
-        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), fitted_bar_bias)
-        np.testing.assert_almost_equal(md0.preset_out_bias["foo"], foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["foo"]), foo_bias)
+        np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
         # 4. a preset that leaves an observed type unassigned is rejected
         md1 = DPAtomicModel(
             ds,
diff --git a/source/tests/pt/test_change_bias.py b/source/tests/pt/test_change_bias.py
index 746656ac8c..f7e3060293 100644
--- a/source/tests/pt/test_change_bias.py
+++ b/source/tests/pt/test_change_bias.py
@@ -144,6 +144,32 @@ def test_change_bias_with_data_sys_file(self) -> None:
         expected_bias = expected_model.get_out_bias()
         torch.testing.assert_close(updated_bias, expected_bias)
 
+    def test_change_bias_ignores_checkpoint_preset(self) -> None:
+        checkpoint = torch.load(
+            str(self.model_path), map_location=DEVICE, weights_only=True
+        )
+        preset = {"energy": [1.0e6] * len(self.config["model"]["type_map"])}
+        checkpoint["model"]["_extra_state"]["model_params"]["preset_out_bias"] = preset
+        torch.save(checkpoint, self.model_path)
+        run_dp(
+            f"dp --pt change-bias {self.model_path!s} -s {self.data_file[0]} -o {self.model_path_data_bias!s}"
+        )
+        updated = torch.load(
+            str(self.model_path_data_bias), map_location=DEVICE, weights_only=True
+        )
+        model_params = updated["model"]["_extra_state"]["model_params"]
+        self.assertEqual(model_params["preset_out_bias"], preset)
+        wrapper = ModelWrapper(get_model_for_wrapper(model_params))
+        wrapper.load_state_dict(updated["model"])
+        expected_model = model_change_out_bias(
+            self.trainer.wrapper.model["Default"],
+            self.sampled,
+            _bias_adjust_mode="change-by-statistic",
+        )
+        torch.testing.assert_close(
+            wrapper.model["Default"].get_out_bias(), expected_model.get_out_bias()
+        )
+
     def test_change_bias_with_user_defined(self) -> None:
         user_bias = [0.1, 3.2, -0.5]
         run_dp(
diff --git a/source/tests/pt/test_training.py b/source/tests/pt/test_training.py
index b7dcba84c2..9cce8c02aa 100644
--- a/source/tests/pt/test_training.py
+++ b/source/tests/pt/test_training.py
@@ -1388,9 +1388,7 @@ def test_ema_checkpoint_cleanup_removes_future_steps(self) -> None:
     def test_ema_checkpoint_keeps_changed_out_bias(
         self, mocked_change_out_bias
     ) -> None:
-        def change_out_bias(
-            model, sample_func, _bias_adjust_mode, preset_out_bias=None
-        ):
+        def change_out_bias(model, sample_func, _bias_adjust_mode):
             model.set_out_bias(model.get_out_bias() + 1.0)
             return model
 

From 79beec01e8369cb7f514f9b39cafc6a800b9d456 Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 14:27:28 +0800
Subject: [PATCH 5/9] fix(pt_expt): ignore checkpoint presets in standalone
 change-bias

---
 deepmd/pt_expt/entrypoints/main.py       |  5 +-
 deepmd/pt_expt/train/training.py         |  5 ++
 source/tests/pt_expt/test_change_bias.py | 73 +++++++++++++++++++++++-
 3 files changed, 80 insertions(+), 3 deletions(-)

diff --git a/deepmd/pt_expt/entrypoints/main.py b/deepmd/pt_expt/entrypoints/main.py
index 7a381b4938..1e4ae0b0ad 100644
--- a/deepmd/pt_expt/entrypoints/main.py
+++ b/deepmd/pt_expt/entrypoints/main.py
@@ -825,7 +825,10 @@ def change_bias(
             nbatches = min(data.get_nbatches())
         sampled_data = make_stat_input(data, nbatches)
         model_to_change = model_change_out_bias(
-            model_to_change, sampled_data, _bias_adjust_mode=bias_adjust_mode
+            model_to_change,
+            sampled_data,
+            _bias_adjust_mode=bias_adjust_mode,
+            preset_out_bias={},
         )
 
     if input_file.endswith(".pt"):
diff --git a/deepmd/pt_expt/train/training.py b/deepmd/pt_expt/train/training.py
index 9130f5753b..e98d724970 100644
--- a/deepmd/pt_expt/train/training.py
+++ b/deepmd/pt_expt/train/training.py
@@ -3441,6 +3441,7 @@ def model_change_out_bias(
     _model: Any,
     _sample_func: Any,
     _bias_adjust_mode: str = "change-by-statistic",
+    preset_out_bias: dict | None = None,
 ) -> Any:
     """Change the output bias of a model based on sampled data.
 
@@ -3452,6 +3453,9 @@ def model_change_out_bias(
         Callable that returns sampled data for bias computation.
     _bias_adjust_mode
         ``"change-by-statistic"`` or ``"set-by-statistic"``.
+    preset_out_bias
+        Optional preset override. An empty mapping ignores checkpoint presets;
+        omitting it preserves training and fine-tuning behavior.
 
     Returns
     -------
@@ -3466,6 +3470,7 @@ def model_change_out_bias(
         _sample_func,
         bias_adjust_mode=_bias_adjust_mode,
         recompute_input_stats=isinstance(_model, DPModelCommon),
+        preset_out_bias=preset_out_bias,
     )
 
 
diff --git a/source/tests/pt_expt/test_change_bias.py b/source/tests/pt_expt/test_change_bias.py
index 2401aa59c5..719ada14b3 100644
--- a/source/tests/pt_expt/test_change_bias.py
+++ b/source/tests/pt_expt/test_change_bias.py
@@ -19,18 +19,27 @@
 from deepmd.pt_expt.model.get_model import (
     get_model,
 )
+from deepmd.pt_expt.train.training import (
+    model_change_out_bias,
+)
 from deepmd.pt_expt.train.wrapper import (
     ModelWrapper,
 )
 from deepmd.pt_expt.utils.env import (
     DEVICE,
 )
+from deepmd.pt_expt.utils.stat import (
+    make_stat_input,
+)
 from deepmd.utils.argcheck import (
     normalize,
 )
 from deepmd.utils.compat import (
     update_deepmd_input,
 )
+from deepmd.utils.data_system import (
+    DeepmdDataSystem,
+)
 
 
 def to_numpy(x):
@@ -184,6 +193,7 @@ def setUpClass(cls) -> None:
 
         # Build & train 1-step model
         config = _make_config(data_dir)
+        config["model"]["preset_out_bias"] = {"energy": [-10.0, -13.6]}
         config = update_deepmd_input(config, warning=False)
         config = normalize(config)
         config["training"]["save_ckpt"] = "model.ckpt"
@@ -193,8 +203,18 @@ def setUpClass(cls) -> None:
 
         cls.model_path = os.path.join(cls.tmpdir, "model.ckpt.pt")
 
-        # Record original bias
-        cls.original_bias = to_numpy(trainer.wrapper.model["Default"].get_out_bias())
+        # A checkpoint may already carry a downstream-adjusted finite bias.
+        model = trainer.wrapper.model["Default"]
+        old_bias = model.get_out_bias()
+        model.set_out_bias(
+            torch.as_tensor(
+                [7.0, 8.0], dtype=old_bias.dtype, device=old_bias.device
+            ).reshape(old_bias.shape)
+        )
+        checkpoint = torch.load(cls.model_path, map_location=DEVICE, weights_only=True)
+        checkpoint["model"] = trainer.wrapper.state_dict()
+        torch.save(checkpoint, cls.model_path)
+        cls.original_bias = to_numpy(model.get_out_bias()).copy()
 
         # Pre-freeze shared .pte and .pt2 files so individual tests don't
         # each pay the AOTInductor compilation cost (~82s per .pt2).
@@ -231,6 +251,44 @@ def _load_model_from_ckpt(self, ckpt_path: str):
         wrapper.load_state_dict(model_state)
         return model
 
+    def _expected_fitted_bias(self):
+        model = self._load_model_from_ckpt(self.model_path)
+        # Compare against the established no-preset statistics path with the
+        # same network and adjusted bias, rather than starting from the preset.
+        model.atomic_model.preset_out_bias = None
+        data = DeepmdDataSystem(
+            systems=self.data_file,
+            batch_size=1,
+            test_size=1,
+            rcut=model.get_rcut(),
+            type_map=model.get_type_map(),
+        )
+        from deepmd.pt_expt.train.training import (
+            get_loss,
+        )
+
+        loss = get_loss({"inference": True}, 1.0, len(model.get_type_map()), model)
+        data.add_data_requirements(loss.label_requirement)
+        sampled = make_stat_input(data, min(data.get_nbatches()))
+        return to_numpy(model_change_out_bias(model, sampled).get_out_bias())
+
+    def _assert_preset_bias_update(self, model) -> None:
+        np.testing.assert_allclose(
+            to_numpy(model.get_out_bias()), self._expected_fitted_bias(), atol=1e-10
+        )
+        self.assertEqual(
+            model.atomic_model.preset_out_bias, {"energy": [[-10.0], [-13.6]]}
+        )
+
+    def test_default_bias_helper_preserves_preset_behavior(self) -> None:
+        model = self._load_model_from_ckpt(self.model_path)
+        np.testing.assert_allclose(to_numpy(model.get_out_bias()), self.original_bias)
+        sampled = [{"atype": np.array([[0, 1]], dtype=np.int32)}]
+        model_change_out_bias(model, sampled)
+        np.testing.assert_allclose(
+            to_numpy(model.get_out_bias()).reshape(-1), [-10.0, -13.6]
+        )
+
     def test_change_bias_with_data(self) -> None:
         output_path = os.path.join(self.tmpdir, "model_data_bias.pt")
         run_dp(
@@ -239,6 +297,7 @@ def test_change_bias_with_data(self) -> None:
         )
         updated_model = self._load_model_from_ckpt(output_path)
         updated_bias = to_numpy(updated_model.get_out_bias())
+        self._assert_preset_bias_update(updated_model)
         original_bias = np.array(self.original_bias)
         # Bias should have changed from the original
         self.assertFalse(
@@ -333,6 +392,11 @@ def test_change_bias_frozen_pte(self) -> None:
         updated_data = serialize_from_file(output_pte)
         updated_model = BaseModel.deserialize(updated_data["model"])
         updated_bias = to_numpy(updated_model.get_out_bias())
+        self._assert_preset_bias_update(updated_model)
+        self.assertEqual(
+            updated_data["model_def_script"]["preset_out_bias"],
+            self.config["model"]["preset_out_bias"],
+        )
 
         # Bias should have changed
         self.assertFalse(
@@ -362,6 +426,11 @@ def test_change_bias_frozen_pt2(self) -> None:
         updated_data = serialize_from_file(output_pt2)
         updated_model = BaseModel.deserialize(updated_data["model"])
         updated_bias = to_numpy(updated_model.get_out_bias())
+        self._assert_preset_bias_update(updated_model)
+        self.assertEqual(
+            updated_data["model_def_script"]["preset_out_bias"],
+            self.config["model"]["preset_out_bias"],
+        )
 
         self.assertFalse(
             np.allclose(original_bias, updated_bias),

From b72a481f1e123344c8f0b9f36962ea95e966684d Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Tue, 13 Oct 2026 15:20:47 +0800
Subject: [PATCH 6/9] fix(spin): map downstream bias presets to virtual type
 layout

---
 deepmd/dpmodel/model/spin_model.py            |  8 +++++++
 deepmd/pt/model/model/sezm_spin_model.py      |  8 +++++++
 deepmd/pt/model/model/spin_model.py           |  8 +++++++
 .../dpmodel/test_spin_model_virtual_types.py  | 12 ++++++++++
 source/tests/pd/test_change_bias.py           | 23 +++++++++++++++++++
 source/tests/pt/model/test_sezm_spin_model.py | 15 ++++++++++++
 .../pt/model/test_spin_model_virtual_types.py | 13 +++++++++++
 7 files changed, 87 insertions(+)

diff --git a/deepmd/dpmodel/model/spin_model.py b/deepmd/dpmodel/model/spin_model.py
index 8930e84e35..ffebdf7870 100644
--- a/deepmd/dpmodel/model/spin_model.py
+++ b/deepmd/dpmodel/model/spin_model.py
@@ -34,6 +34,10 @@
 from deepmd.utils.spin import (
     Spin,
 )
+from deepmd.utils.preset_out_bias import (
+    normalize_preset_out_bias,
+    remap_preset_out_bias,
+)
 
 _NATOMS_VEC_KEYS = ("natoms", "real_natoms_vec")
 _SPIN_STAT_RESERVED_KEYS = frozenset(
@@ -622,6 +626,10 @@ def change_out_bias(
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
         """
+        preset_out_bias = remap_preset_out_bias(
+            normalize_preset_out_bias(preset_out_bias, self.get_type_map()),
+            list(range(self.get_ntypes())) + [-1] * self.get_ntypes(),
+        )
         spin_sampled_func = self._get_spin_sampled_func(
             merged if callable(merged) else lambda: merged
         )
diff --git a/deepmd/pt/model/model/sezm_spin_model.py b/deepmd/pt/model/model/sezm_spin_model.py
index 1a5389e3f9..83e4489d87 100644
--- a/deepmd/pt/model/model/sezm_spin_model.py
+++ b/deepmd/pt/model/model/sezm_spin_model.py
@@ -47,6 +47,10 @@
 from deepmd.utils.spin import (
     Spin,
 )
+from deepmd.utils.preset_out_bias import (
+    normalize_preset_out_bias,
+    remap_preset_out_bias,
+)
 from deepmd.utils.version import (
     check_version_compatibility,
 )
@@ -435,6 +439,10 @@ def change_out_bias(
         preset_out_bias: dict | None = None,
     ) -> None:
         """Change output bias using spin-expanded sampled data."""
+        preset_out_bias = remap_preset_out_bias(
+            normalize_preset_out_bias(preset_out_bias, self.get_type_map()),
+            list(range(self.get_ntypes())) + [-1] * self.get_ntypes(),
+        )
         spin_sampled_func = self._get_spin_sampled_func(
             merged if callable(merged) else lambda: merged
         )
diff --git a/deepmd/pt/model/model/spin_model.py b/deepmd/pt/model/model/spin_model.py
index 5197f6d16b..ab5a93d9e4 100644
--- a/deepmd/pt/model/model/spin_model.py
+++ b/deepmd/pt/model/model/spin_model.py
@@ -30,6 +30,10 @@
 from deepmd.utils.spin import (
     Spin,
 )
+from deepmd.utils.preset_out_bias import (
+    normalize_preset_out_bias,
+    remap_preset_out_bias,
+)
 
 from .make_model import (
     make_model,
@@ -537,6 +541,10 @@ def change_out_bias(
                     and do least square on the errors to obtain the target shift as bias.
             'set-by-statistic' : directly use the statistic output bias in the target dataset.
         """
+        preset_out_bias = remap_preset_out_bias(
+            normalize_preset_out_bias(preset_out_bias, self.get_type_map()),
+            list(range(self.get_ntypes())) + [-1] * self.get_ntypes(),
+        )
         spin_sampled_func = self._get_spin_sampled_func(
             merged if callable(merged) else lambda: merged
         )
diff --git a/source/tests/common/dpmodel/test_spin_model_virtual_types.py b/source/tests/common/dpmodel/test_spin_model_virtual_types.py
index 727eac3b53..4795dfb971 100644
--- a/source/tests/common/dpmodel/test_spin_model_virtual_types.py
+++ b/source/tests/common/dpmodel/test_spin_model_virtual_types.py
@@ -80,6 +80,18 @@ def test_dense_spin_expansion_preserves_virtual_types(model) -> None:
     )
 
 
+def test_real_type_sequence_bias_override(model) -> None:
+    sample = {
+        "coord": np.arange(9, dtype=np.float64).reshape(1, 3, 3),
+        "atype": np.array([[0, 1, 2]], dtype=np.int32),
+        "spin": np.ones((1, 3, 3), dtype=np.float64),
+    }
+    model.change_out_bias([sample], preset_out_bias={"energy": [1.0, 2.0, 3.0]})
+    np.testing.assert_allclose(
+        to_numpy_array(model.get_out_bias()).reshape(-1), [1.0, 2.0, 3.0, 0.0, 0.0, 0.0]
+    )
+
+
 def test_lower_spin_expansion_preserves_virtual_types(model) -> None:
     """Local and ghost placeholders remain negative in the switched layout."""
     extended_coord = np.arange(12, dtype=np.float64).reshape(1, 4, 3)
diff --git a/source/tests/pd/test_change_bias.py b/source/tests/pd/test_change_bias.py
index 2d87b739ff..36c2f0290c 100644
--- a/source/tests/pd/test_change_bias.py
+++ b/source/tests/pd/test_change_bias.py
@@ -140,6 +140,29 @@ def test_change_bias_with_user_defined(self):
         )
         np.testing.assert_allclose(updated_bias.numpy(), expected_bias.numpy())
 
+    def test_change_bias_ignores_checkpoint_preset(self):
+        checkpoint = paddle.load(str(self.model_path))
+        preset = {"energy": [1.0e6] * len(self.config["model"]["type_map"])}
+        checkpoint["model"]["_extra_state"]["model_params"]["preset_out_bias"] = preset
+        paddle.save(checkpoint, str(self.model_path))
+        run_dp(
+            f"dp --pd change-bias {self.model_path!s} -s {self.data_file[0]} -o {self.model_path_data_bias!s}"
+        )
+        updated = paddle.load(str(self.model_path_data_bias))
+        model_params = updated["model"]["_extra_state"]["model_params"]
+        self.assertEqual(model_params["preset_out_bias"], preset)
+        wrapper = ModelWrapper(get_model_for_wrapper(model_params))
+        wrapper.set_state_dict(updated["model"])
+        expected_model = model_change_out_bias(
+            self.trainer.wrapper.model["Default"],
+            self.sampled,
+            _bias_adjust_mode="change-by-statistic",
+        )
+        np.testing.assert_allclose(
+            wrapper.model["Default"].get_out_bias().numpy(),
+            expected_model.get_out_bias().numpy(),
+        )
+
     def tearDown(self):
         for f in os.listdir("."):
             if f.startswith("change-bias-model") and f.endswith(".pd"):
diff --git a/source/tests/pt/model/test_sezm_spin_model.py b/source/tests/pt/model/test_sezm_spin_model.py
index 314a715364..dcfa932228 100644
--- a/source/tests/pt/model/test_sezm_spin_model.py
+++ b/source/tests/pt/model/test_sezm_spin_model.py
@@ -438,6 +438,21 @@ def test_zbl_change_out_bias_is_invariant_for_self_labels(self) -> None:
             rtol=1.0e-12,
         )
 
+    def test_real_type_sequence_bias_override(self) -> None:
+        model = get_model(self._build_model_params()).to(self.device)
+        sample = {
+            "coord": self.coord,
+            "atype": self.atype,
+            "spin": self.spin,
+            "box": self.box,
+        }
+        model.change_out_bias([sample], preset_out_bias={"energy": [1.0, 2.0]})
+        bias = model.get_out_bias()
+        torch.testing.assert_close(
+            bias.reshape(-1),
+            torch.tensor([1.0, 2.0, 0.0, 0.0], dtype=bias.dtype, device=bias.device),
+        )
+
     def test_zbl_statistics_use_physical_spin_neighbor_topology(self) -> None:
         """Statistics preserve real-nlist expansion when `sel` is saturated."""
         params = self._build_model_params(bridging_method="ZBL")
diff --git a/source/tests/pt/model/test_spin_model_virtual_types.py b/source/tests/pt/model/test_spin_model_virtual_types.py
index b8d8dbf772..8193751b06 100644
--- a/source/tests/pt/model/test_spin_model_virtual_types.py
+++ b/source/tests/pt/model/test_spin_model_virtual_types.py
@@ -61,6 +61,19 @@ def _tensor(array: np.ndarray) -> torch.Tensor:
 class TestPtSpinModelVirtualTypes(unittest.TestCase):
     """Every pt lookup must mask ``atype < 0`` exactly as dpmodel does."""
 
+    def test_real_type_sequence_bias_override(self) -> None:
+        model = get_pt_model(MODEL_CONFIG)
+        sample = {
+            "coord": _tensor(np.arange(9, dtype=np.float64).reshape(1, 3, 3)),
+            "atype": _tensor(np.array([[0, 1, 2]], dtype=np.int64)),
+            "spin": _tensor(np.ones((1, 3, 3), dtype=np.float64)),
+        }
+        model.change_out_bias([sample], preset_out_bias={"energy": [1.0, 2.0, 3.0]})
+        np.testing.assert_allclose(
+            to_numpy_array(model.get_out_bias()).reshape(-1),
+            [1.0, 2.0, 3.0, 0.0, 0.0, 0.0],
+        )
+
     def test_dense_spin_expansion_preserves_virtual_types(self) -> None:
         model = get_pt_model(MODEL_CONFIG)
         coord = np.arange(9, dtype=np.float64).reshape(1, 3, 3)

From 4f5af649bb88751a236b5c11634383df8714bcf3 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Tue, 13 Oct 2026 07:21:59 +0000
Subject: [PATCH 7/9] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 deepmd/dpmodel/model/spin_model.py       | 6 +++---
 deepmd/pt/model/model/sezm_spin_model.py | 6 +++---
 deepmd/pt/model/model/spin_model.py      | 6 +++---
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/deepmd/dpmodel/model/spin_model.py b/deepmd/dpmodel/model/spin_model.py
index ffebdf7870..f97a1d60ea 100644
--- a/deepmd/dpmodel/model/spin_model.py
+++ b/deepmd/dpmodel/model/spin_model.py
@@ -31,13 +31,13 @@
 from deepmd.dpmodel.output_def import (
     ModelOutputDef,
 )
-from deepmd.utils.spin import (
-    Spin,
-)
 from deepmd.utils.preset_out_bias import (
     normalize_preset_out_bias,
     remap_preset_out_bias,
 )
+from deepmd.utils.spin import (
+    Spin,
+)
 
 _NATOMS_VEC_KEYS = ("natoms", "real_natoms_vec")
 _SPIN_STAT_RESERVED_KEYS = frozenset(
diff --git a/deepmd/pt/model/model/sezm_spin_model.py b/deepmd/pt/model/model/sezm_spin_model.py
index 83e4489d87..779d07376d 100644
--- a/deepmd/pt/model/model/sezm_spin_model.py
+++ b/deepmd/pt/model/model/sezm_spin_model.py
@@ -44,13 +44,13 @@
 from deepmd.utils.path import (
     DPPath,
 )
-from deepmd.utils.spin import (
-    Spin,
-)
 from deepmd.utils.preset_out_bias import (
     normalize_preset_out_bias,
     remap_preset_out_bias,
 )
+from deepmd.utils.spin import (
+    Spin,
+)
 from deepmd.utils.version import (
     check_version_compatibility,
 )
diff --git a/deepmd/pt/model/model/spin_model.py b/deepmd/pt/model/model/spin_model.py
index ab5a93d9e4..3ba467b851 100644
--- a/deepmd/pt/model/model/spin_model.py
+++ b/deepmd/pt/model/model/spin_model.py
@@ -27,13 +27,13 @@
 from deepmd.utils.path import (
     DPPath,
 )
-from deepmd.utils.spin import (
-    Spin,
-)
 from deepmd.utils.preset_out_bias import (
     normalize_preset_out_bias,
     remap_preset_out_bias,
 )
+from deepmd.utils.spin import (
+    Spin,
+)
 
 from .make_model import (
     make_model,

From 0be5abf17d51941cc28b8092ee9851a27ce9e83f Mon Sep 17 00:00:00 2001
From: Anyang Peng <137014849+anyangml@users.noreply.github.com>
Date: Wed, 14 Oct 2026 10:32:49 +0800
Subject: [PATCH 8/9] test(model): verify adjusted bias baseline during
 residual fitting

---
 .../dpmodel/test_atomic_model_global_stat.py  | 27 +++++++++++++----
 .../pd/model/test_atomic_model_global_stat.py | 29 +++++++++++++++----
 .../pt/model/test_atomic_model_global_stat.py | 29 +++++++++++++++----
 3 files changed, 68 insertions(+), 17 deletions(-)

diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 7760cce9cd..28873494d3 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -1,6 +1,9 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
+from unittest.mock import (
+    patch,
+)
 from pathlib import (
     Path,
 )
@@ -331,11 +334,25 @@ def test_preset_bias(self) -> None:
         np.testing.assert_almost_equal(out_bias["bar"], bar_bias)
 
         # Standalone change-bias explicitly ignores the checkpoint preset.
-        md0.change_out_bias(
-            self.merged_output_stat,
-            bias_adjust_mode="change-by-statistic",
-            preset_out_bias={},
-        )
+        adjusted_bias = foo_bias + 7.0
+        md0._store_out_stat({"foo": adjusted_bias})
+        forward = md0._get_forward_wrapper_func()
+        seen_biases = []
+
+        def check_forward(*args, **kwargs):
+            bias, _ = md0._fetch_out_stat(["foo"])
+            seen_biases.append(bias["foo"].copy())
+            return forward(*args, **kwargs)
+
+        with patch.object(md0, "_get_forward_wrapper_func", return_value=check_forward):
+            md0.change_out_bias(
+                self.merged_output_stat,
+                bias_adjust_mode="change-by-statistic",
+                preset_out_bias={},
+            )
+        self.assertTrue(seen_biases)
+        for seen_bias in seen_biases:
+            np.testing.assert_almost_equal(seen_bias, adjusted_bias)
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(
             out_bias["foo"], np.array([2.0, -5.0]).reshape(2, 1)
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index ff747eb518..557c8d1ea2 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -1,6 +1,9 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
+from unittest.mock import (
+    patch,
+)
 from pathlib import (
     Path,
 )
@@ -362,12 +365,26 @@ def cvt_ret(x):
         np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
 
         # Standalone change-bias explicitly ignores the checkpoint preset.
-        BaseAtomicModel.change_out_bias(
-            md0,
-            self.merged_output_stat,
-            bias_adjust_mode="change-by-statistic",
-            preset_out_bias={},
-        )
+        adjusted_bias = foo_bias + 7.0
+        md0._store_out_stat({"foo": to_paddle_tensor(adjusted_bias)})
+        forward = md0._get_forward_wrapper_func()
+        seen_biases = []
+
+        def check_forward(*args, **kwargs):
+            bias, _ = md0._fetch_out_stat(["foo"])
+            seen_biases.append(to_numpy_array(bias["foo"]).copy())
+            return forward(*args, **kwargs)
+
+        with patch.object(md0, "_get_forward_wrapper_func", return_value=check_forward):
+            BaseAtomicModel.change_out_bias(
+                md0,
+                self.merged_output_stat,
+                bias_adjust_mode="change-by-statistic",
+                preset_out_bias={},
+            )
+        self.assertTrue(seen_biases)
+        for seen_bias in seen_biases:
+            np.testing.assert_almost_equal(seen_bias, adjusted_bias)
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index 3e304ee1d7..388b2458e9 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -1,6 +1,9 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
+from unittest.mock import (
+    patch,
+)
 from pathlib import (
     Path,
 )
@@ -388,12 +391,26 @@ def cvt_ret(x):
         np.testing.assert_almost_equal(to_numpy_array(out_bias["bar"]), bar_bias)
 
         # Standalone change-bias explicitly ignores the checkpoint preset.
-        BaseAtomicModel.change_out_bias(
-            md0,
-            self.merged_output_stat,
-            bias_adjust_mode="change-by-statistic",
-            preset_out_bias={},
-        )
+        adjusted_bias = foo_bias + 7.0
+        md0._store_out_stat({"foo": to_torch_tensor(adjusted_bias)})
+        forward = md0._get_forward_wrapper_func()
+        seen_biases = []
+
+        def check_forward(*args, **kwargs):
+            bias, _ = md0._fetch_out_stat(["foo"])
+            seen_biases.append(to_numpy_array(bias["foo"]).copy())
+            return forward(*args, **kwargs)
+
+        with patch.object(md0, "_get_forward_wrapper_func", return_value=check_forward):
+            BaseAtomicModel.change_out_bias(
+                md0,
+                self.merged_output_stat,
+                bias_adjust_mode="change-by-statistic",
+                preset_out_bias={},
+            )
+        self.assertTrue(seen_biases)
+        for seen_bias in seen_biases:
+            np.testing.assert_almost_equal(seen_bias, adjusted_bias)
         out_bias, _ = md0._fetch_out_stat(["foo", "bar"])
         np.testing.assert_almost_equal(
             to_numpy_array(out_bias["foo"]), np.array([2.0, -5.0]).reshape(2, 1)

From 8a13bce37efa0314a43227daeccb8631419f6d5a Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 14 Oct 2026 02:33:56 +0000
Subject: [PATCH 9/9] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 .../tests/common/dpmodel/test_atomic_model_global_stat.py   | 6 +++---
 source/tests/pd/model/test_atomic_model_global_stat.py      | 6 +++---
 source/tests/pt/model/test_atomic_model_global_stat.py      | 6 +++---
 3 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/source/tests/common/dpmodel/test_atomic_model_global_stat.py b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
index 28873494d3..1ddc7d1acc 100644
--- a/source/tests/common/dpmodel/test_atomic_model_global_stat.py
+++ b/source/tests/common/dpmodel/test_atomic_model_global_stat.py
@@ -1,15 +1,15 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
-from unittest.mock import (
-    patch,
-)
 from pathlib import (
     Path,
 )
 from typing import (
     NoReturn,
 )
+from unittest.mock import (
+    patch,
+)
 
 import h5py
 import numpy as np
diff --git a/source/tests/pd/model/test_atomic_model_global_stat.py b/source/tests/pd/model/test_atomic_model_global_stat.py
index 557c8d1ea2..023bafb277 100644
--- a/source/tests/pd/model/test_atomic_model_global_stat.py
+++ b/source/tests/pd/model/test_atomic_model_global_stat.py
@@ -1,12 +1,12 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
-from unittest.mock import (
-    patch,
-)
 from pathlib import (
     Path,
 )
+from unittest.mock import (
+    patch,
+)
 
 import h5py
 import numpy as np
diff --git a/source/tests/pt/model/test_atomic_model_global_stat.py b/source/tests/pt/model/test_atomic_model_global_stat.py
index 388b2458e9..dc12dd23b6 100644
--- a/source/tests/pt/model/test_atomic_model_global_stat.py
+++ b/source/tests/pt/model/test_atomic_model_global_stat.py
@@ -1,15 +1,15 @@
 # SPDX-License-Identifier: LGPL-3.0-or-later
 import tempfile
 import unittest
-from unittest.mock import (
-    patch,
-)
 from pathlib import (
     Path,
 )
 from typing import (
     NoReturn,
 )
+from unittest.mock import (
+    patch,
+)
 
 import h5py
 import numpy as np