mattertune.configs.data.matbench

class mattertune.configs.data.matbench.DatasetConfigBase[source]
abstract create_dataset()[source]
Return type:

Dataset[Atoms]

prepare_data()[source]

Prepare the dataset for training.

Use this to download and prepare data. Downloading and saving data with multiple processes (distributed settings) will result in corrupted data. Lightning ensures this method is called only within a single process, so you can safely add your downloading logic within this method.

classmethod ensure_dependencies()[source]

Ensure that all dependencies are installed.

This method should raise an exception if any dependencies are missing, with a message indicating which dependencies are missing and how to install them.

class mattertune.configs.data.matbench.MatbenchDatasetConfig(*, type='matbench', task=None, property_name=None, fold_idx=0)[source]

Configuration for the Matbench dataset.

Parameters:

  • type (Literal['matbench'])

  • task (str | None)

  • property_name (str | None)

  • fold_idx (Literal[0, 1, 2, 3, 4])

type: Literal['matbench']

Discriminator for the Matbench dataset.

task: str | None

The name of the self.tasks to include in the dataset.

property_name: str | None

Assign a property name for the self.task. Must match the property head in the model.

fold_idx: Literal[0, 1, 2, 3, 4]

The index of the fold to be used in the dataset.

create_dataset()[source]