fix the interface for multihead

mace/cli/fine_tuning_select.py

@@ -99,7 +99,7 @@ def calculate_descriptors(
     atoms: t.List[ase.Atoms | ase.Atom], calc: MACECalculator, cutoffs: None | dict
 ) -> None:
     print("Calculating descriptors")
-    for mol in tqdm(atoms):
+    for mol in atoms:
         descriptors = calc.get_descriptors(mol.copy(), invariants_only=True)
         # average descriptors over atoms for each element
         descriptors_dict = {
@@ -182,7 +182,8 @@ def assemble_descriptors(self) -> np.ndarray:
                     len(self.atoms_list),
                     len(self.species),
                     len(list(self.atoms_list[0].info["mace_descriptors"].values())[0]),
-                )
+                ),
+                dtype=np.float32,
             )
         )
         for i, atoms in enumerate(self.atoms_list):
@@ -216,10 +217,6 @@ def select_samples(
             atoms_list_pt = ase.io.read(args.configs_pt, index=":")
             for i, atoms in enumerate(atoms_list_pt):
                 atoms.info["mace_descriptors"] = descriptors[i]
-            print(
-                "Filtering configurations based on the finetuning set,"
-                f"filtering type: combinations, elements: {all_species_ft}"
-            )
             atoms_list_pt = [
                 x
                 for x in atoms_list_pt

mace/cli/run_train.py

@@ -177,7 +177,13 @@ def main() -> None:
 
         if args.multiheads_finetuning:
             logging.info("Using multiheads finetuning mode")
-            heads = list(set(["pbe_mp"] + heads))
+            if heads is not None:
+                heads = list(set(["pbe_mp"] + heads))
+                args.heads = heads
+            else:
+                heads = ["pbe_mp", "Default"]
+                args.heads = heads
+            logging.info(f"Using heads: {heads}")
             try:
                 checkpoint_url = "https://tinyurl.com/mw2wetc5"
                 cache_dir = os.path.expanduser("~/.cache/mace")
@@ -214,13 +220,13 @@ def main() -> None:
                     "weight_ft": 1.0,
                     "filtering_type": "combination",
                     "output": f"{cache_dir}/mp_finetuning.xyz",
-                    "descriptors": None,
+                    "descriptors": r"D:\Work\mace_mp\descriptors.npy",
                     "device": args.device,
                     "default_dtype": args.default_dtype,
                 }
                 select_samples(dict_to_namespace(args_samples))
                 collections_mp, _, _ = get_dataset_from_xyz(
-                    train_path=dataset_mp,
+                    train_path=f"{cache_dir}/mp_finetuning.xyz",
                     valid_path=None,
                     valid_fraction=args.valid_fraction,
                     config_type_weights=config_type_weights,
@@ -277,9 +283,9 @@ def main() -> None:
         else:
             atomic_energies_dict = get_atomic_energies(args.E0s, None, z_table, heads)
     if args.multiheads_finetuning:
-        with open("mace\calculators\foundations_models\mp_vasp_e0.json", "r") as file:
+        with open(r"mace\calculators\foundations_models\mp_vasp_e0.json", "r") as file:
             E0s_mp = json.load(file)
-        atomic_energies_dict["pbe_mp"] = {E0s_mp["pbe"][z] for z in z_table.zs}
+        atomic_energies_dict["pbe_mp"] = {z: E0s_mp["pbe"][f"{z}"] for z in z_table.zs}
 
     if args.model == "AtomicDipolesMACE":
         atomic_energies = None

mace/data/utils.py

@@ -231,7 +231,6 @@ def load_from_xyz(
         )
         stress_key = "REF_stress"
 
-    # Process each atom only once
     for atoms in atoms_list:
         if energy_key == "REF_energy":
             try:

mace/tools/arg_parser.py

@@ -372,7 +372,7 @@ def build_default_arg_parser() -> argparse.ArgumentParser:
         "--stress_key",
         help="Key of reference stress in training xyz",
         type=str,
-        default="stress",
+        default="REF_stress",
     )
     parser.add_argument(
         "--dipole_key",