inconsistent input fix #399
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…onsistent_label_fix
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| common_keys = set(self.data[0].calc.results.keys()) | ||
| for atoms in self.data[1:]: | ||
| common_keys &= set(atoms.calc.results.keys()) | ||
| for atoms in self.validation_data: | ||
| common_keys &= set(atoms.calc.results.keys()) | ||
| log.warning(f"common keys = {common_keys}") | ||
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| new_frames = [] | ||
| for atoms in self.data: | ||
| results = {} | ||
| for key in common_keys: | ||
| results[key] = atoms.calc.results[key] | ||
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| symbols = atoms.get_chemical_symbols() | ||
| pbc = atoms.get_pbc() | ||
| positions = atoms.get_positions() | ||
| cell = atoms.get_cell() | ||
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| new_atoms = ase.Atoms( | ||
| symbols=symbols, positions=positions, cell=cell, pbc=pbc | ||
| ) | ||
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| calc = ase.calculators.singlepoint.SinglePointCalculator( | ||
| new_atoms, **results | ||
| ) | ||
| new_atoms.calc = calc | ||
| new_frames.append(new_atoms) | ||
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| new_val_frames = [] | ||
| for atoms in self.validation_data: | ||
| results = {} | ||
| for key in common_keys: | ||
| results[key] = atoms.calc.results[key] | ||
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| symbols = atoms.get_chemical_symbols() | ||
| pbc = atoms.get_pbc() | ||
| positions = atoms.get_positions() | ||
| cell = atoms.get_cell() | ||
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| new_val_atoms = ase.Atoms( | ||
| symbols=symbols, positions=positions, cell=cell, pbc=pbc | ||
| ) | ||
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| calc = ase.calculators.singlepoint.SinglePointCalculator( | ||
| new_val_atoms, **results | ||
| ) | ||
| new_val_atoms.calc = calc | ||
| new_val_frames.append(new_val_atoms) | ||
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| ase.io.write(self.train_data_file.as_posix(), new_frames) | ||
| ase.io.write(self.validation_data_file.as_posix(), new_val_frames) |
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When a dataset with inconsistent labels is loaded Apax fails even if the label is not used in the training. Now common labels across the dataset are checked and logged.