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Fix: define calc out of for loop #420

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Merged
anyangml merged 2 commits into from
Apr 7, 2026
Merged

Fix: define calc out of for loop #420

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7ad01a8
fix: define calc out of for loop
anyangml Apr 7, 2026
58071eb
chore:lint
anyangml Apr 7, 2026
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4 changes: 3 additions & 1 deletion lambench/metrics/vishelper/metrics_calculations.py
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Original file line number Diff line number Diff line change
Expand Up @@ -159,7 +159,9 @@ def calculate_generalizability_downstream_score(self) -> tuple[dict, dict]:
) # drop models with missing domain results

# # Now aggregate all domains to get the final generalizability metrics for each model
return domain_results.to_dict(orient="index"), domain_results.mean(axis=1).to_dict()
return domain_results.to_dict(orient="index"), domain_results.mean(
axis=1
).to_dict()

def calculate_stability_results(self) -> dict[str, float]:
"""This calculates the stability score for a given LAM."""
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5 changes: 3 additions & 2 deletions lambench/tasks/calculator/elastic/elastic.py
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Expand Up @@ -102,9 +102,10 @@ def get_elastic_for_one(
"""
atoms = read(StringIO(atom_info["poscar"]), format="vasp")

calc = model.calc
relaxed_atoms = model.run_ase_relaxation(
atoms=atoms,
calc=model.calc,
calc=calc,
fmax=fmax,
steps=max_steps,
fix_symmetry=False,
Expand All @@ -119,7 +120,7 @@ def get_elastic_for_one(
stresses = []
for deformed_structure in deformed_structure_set:
atoms = deformed_structure.to_ase_atoms()
atoms.calc = model.calc
atoms.calc = calc
stresses.append(atoms.get_stress(voigt=False))

strains = [
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4 changes: 3 additions & 1 deletion lambench/tasks/calculator/torsionnet/torsionnet.py
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Expand Up @@ -30,6 +30,8 @@ def run_torsionnet(
result = {} # predicted energy
label = {} # label energy

calc = model.calc

# 500 fragments from Torsionnet500 dataset
for fragment in tqdm(test_data.iterdir()):
if not fragment.is_dir():
Expand All @@ -40,7 +42,7 @@ def run_torsionnet(
for frame in dpdata.LabeledSystem(file_name=fragment, fmt="deepmd/raw"):
assert len(frame) == 1
atoms: Atoms = frame.to_ase_structure()[0] # type: ignore
atoms.calc = model.calc
atoms.calc = calc
pred_energy = atoms.get_potential_energy() * 23.0609 # eV to kcal/mol
result[fragment.name].append(pred_energy)
label_energy = frame.data["energies"][0]
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