qm9

• Description:

QM9 consists of computed geometric, energetic, electronic, and thermodynamic properties for 134k stable small organic molecules made up of C, H, O, N, and F. As usual, we remove the uncharacterized molecules and provide the remaining 130,831.

• Homepage: https://doi.org/10.6084/m9.figshare.c.978904.v5

• Source code: tfds.datasets.qm9.Builder

• Versions:

  • 1.0.0 (default): Initial release.

• Download size: 82.62 MiB

• Dataset size: 177.16 MiB

• Feature structure:

FeaturesDict({
    'A': float32,
    'B': float32,
    'C': float32,
    'Cv': float32,
    'G': float32,
    'G_atomization': float32,
    'H': float32,
    'H_atomization': float32,
    'InChI': string,
    'InChI_relaxed': string,
    'Mulliken_charges': Tensor(shape=(29,), dtype=float32),
    'SMILES': string,
    'SMILES_relaxed': string,
    'U': float32,
    'U0': float32,
    'U0_atomization': float32,
    'U_atomization': float32,
    'alpha': float32,
    'charges': Tensor(shape=(29,), dtype=int64),
    'frequencies': Tensor(shape=(None,), dtype=float32),
    'gap': float32,
    'homo': float32,
    'index': int64,
    'lumo': float32,
    'mu': float32,
    'num_atoms': int64,
    'positions': Tensor(shape=(29, 3), dtype=float32),
    'r2': float32,
    'tag': string,
    'zpve': float32,
})

• Feature documentation:

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Citation:

@article{ramakrishnan2014quantum,
  title={Quantum chemistry structures and properties of 134 kilo molecules},
  author={Ramakrishnan, Raghunathan and Dral, Pavlo O and Rupp, Matthias and von Lilienfeld, O Anatole},
  journal={Scientific Data},
  volume={1},
  year={2014},
  publisher={Nature Publishing Group}
}

qm9/original (default config)

• Config description: QM9 does not define any splits. So this variant puts the full QM9 dataset in the train split, in the original order (no shuffling).

• Auto-cached (documentation): Only when shuffle_files=False (train)

• Splits:

• Examples (tfds.as_dataframe):

qm9/cormorant

• Config description: Dataset split used by Cormorant. 100,000 train, 17,748 validation, and 13,083 test samples. Splitting happens after shuffling with seed 0. Paper: https://arxiv.org/abs/1906.04015 Split: https://github.com/risilab/cormorant/blob/master/src/cormorant/data/prepare/qm9.py

• Auto-cached (documentation): Yes (test, validation), Only when shuffle_files=False (train)

• Splits:

• Examples (tfds.as_dataframe):

qm9/dimenet

• Config description: Dataset split used by DimeNet. 110,000 train, 10,000 validation, and 10,831 test samples. Splitting happens after shuffling with seed 42. Paper: https://arxiv.org/abs/2003.03123 Split: https://github.com/gasteigerjo/dimenet/blob/master/dimenet/training/data_provider.py

• Auto-cached (documentation): Yes (test, validation), Only when shuffle_files=False (train)

• Splits:

• Examples (tfds.as_dataframe):