fix(pt): add finetune_head to argcheck

deepmd/utils/argcheck.py

@@ -1533,6 +1533,10 @@
     doc_spin = "The settings for systems with spin."
     doc_atom_exclude_types = "Exclude the atomic contribution of the listed atom types"
     doc_pair_exclude_types = "The atom pairs of the listed types are not treated to be neighbors, i.e. they do not see each other."
+    doc_finetune_head = (
+        "The chosen fitting net to fine-tune on, when doing multi-task fine-tuning. "
+        "If not set or set to 'RANDOM', the fitting net will be randomly initialized."
+    )
 
     hybrid_models = []
     if not exclude_hybrid:
@@ -1629,6 +1633,12 @@
                 fold_subdoc=True,
             ),
             Argument("spin", dict, spin_args(), [], optional=True, doc=doc_spin),
+            Argument(
+                "finetune_head",
+                str,
+                optional=True,
+                doc=doc_only_pt_supported + doc_finetune_head,
+            ),
         ],
         [
             Variant(

source/tests/pt/model/water/multitask.json

@@ -68,7 +68,6 @@
     "_comment": "that's all"
   },
   "loss_dict": {
-    "_comment": " that's all",
     "model_1": {
       "type": "ener",
       "start_pref_e": 0.02,

source/tests/pt/test_multitask.py

@@ -21,6 +21,12 @@
 from deepmd.pt.utils.multi_task import (
     preprocess_shared_params,
 )
+from deepmd.utils.argcheck import (
+    normalize,
+)
+from deepmd.utils.compat import (
+    update_deepmd_input,
+)
 
 from .model.test_permutation import (
     model_dpa1,
@@ -39,6 +45,8 @@ def setUpModule():
 class MultiTaskTrainTest:
     def test_multitask_train(self):
         # test multitask training
+        self.config = update_deepmd_input(self.config, warning=True)
+        self.config = normalize(self.config, multi_task=True)
         trainer = get_trainer(deepcopy(self.config), shared_links=self.shared_links)
         trainer.run()
         # check model keys
@@ -124,6 +132,8 @@ def test_multitask_train(self):
             finetune_model,
             self.origin_config["model"],
         )
+        self.origin_config = update_deepmd_input(self.origin_config, warning=True)
+        self.origin_config = normalize(self.origin_config, multi_task=True)
         trainer_finetune = get_trainer(
             deepcopy(self.origin_config),
             finetune_model=finetune_model,