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12 | 12 |
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13 | 13 |
|
14 | 14 | try: |
15 | | - from metatomic.torch import ase_calculator |
16 | | - from metatrain.utils.io import load_model |
| 15 | + from metatomic.torch import AtomisticModel |
| 16 | + from metatomic_ase import MetatomicCalculator |
| 17 | + from upet import get_upet |
17 | 18 |
|
18 | 19 | from torch_sim.models.metatomic import MetatomicModel |
19 | 20 | except ImportError: |
|
24 | 25 |
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25 | 26 |
|
26 | 27 | @pytest.fixture |
27 | | -def metatomic_calculator(): |
28 | | - """Load a pretrained metatomic model for testing.""" |
29 | | - model_url = "https://huggingface.co/lab-cosmo/pet-mad/resolve/v1.1.0/models/pet-mad-v1.1.0.ckpt" |
30 | | - return ase_calculator.MetatomicCalculator( |
31 | | - model=load_model(model_url).export(), device=DEVICE |
32 | | - ) |
| 28 | +def metatomic_module() -> AtomisticModel: |
| 29 | + return get_upet(model="pet-mad") |
33 | 30 |
|
34 | 31 |
|
35 | 32 | @pytest.fixture |
36 | | -def metatomic_model() -> MetatomicModel: |
37 | | - """Create an MetatomicModel wrapper for the pretrained model.""" |
38 | | - return MetatomicModel(model="pet-mad", device=DEVICE) |
| 33 | +def metatomic_calculator(metatomic_module: AtomisticModel) -> MetatomicCalculator: |
| 34 | + return MetatomicCalculator(model=metatomic_module, device=DEVICE) |
| 35 | + |
| 36 | + |
| 37 | +@pytest.fixture |
| 38 | +def metatomic_model(metatomic_module: AtomisticModel) -> MetatomicModel: |
| 39 | + return MetatomicModel(model=metatomic_module, device=DEVICE) |
39 | 40 |
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40 | 41 |
|
41 | 42 | def test_metatomic_initialization() -> None: |
42 | | - """Test that the metatomic model initializes correctly.""" |
43 | | - model = MetatomicModel( |
44 | | - model="pet-mad", |
45 | | - device=DEVICE, |
46 | | - ) |
| 43 | + model = MetatomicModel(model=get_upet(model="pet-mad"), device=DEVICE) |
47 | 44 | assert model.device == DEVICE |
48 | 45 | assert model.dtype == torch.float32 |
49 | 46 |
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