sc2_datasets.lightning.datamodules.sc2_datamodule

Classes

SC2DataModuleSingleJSON

SC2DataModule

Defines a LightningDataModule abstraction for some StarCraft II DataModule.

Module Contents

class SC2DataModuleSingleJSON(dataset_name: str, unpack_dir: pathlib.Path, download: bool = True, download_dir: pathlib.Path | str | None = None, dataset_url: str = '', transform: Callable | None = None, validator: Callable | None = None)

Bases: pytorch_lightning.LightningDataModule

dataset_name
unpack_dir
download = True
download_dir = None
dataset_url = ''
transform = None
validator = None
prepare_data() → None
setup(stage: str | None = None) → None
train_dataloader() → torch.utils.data.dataloader.DataLoader
val_dataloader() → torch.utils.data.dataloader.DataLoader
test_dataloader() → torch.utils.data.dataloader.DataLoader
teardown(stage)
class SC2DataModule(replaypacks: list[sc2_datasets.available_replaypacks.DatasetProperties], download_dir: pathlib.Path | str = Path('./data/download').resolve(), unpack_dir: pathlib.Path | str = Path('./data/unpack').resolve(), download: bool = True, transform: Callable = None, batch_size: int = 256, num_workers: int = 0, unpack_n_workers: int = 16, validator: Callable | None = None)

Bases: pytorch_lightning.LightningDataModule

Defines a LightningDataModule abstraction for some StarCraft II DataModule.

Parameters:

  • replaypacks (list[DatasetProperties]) – Specifies a list of properties of replaypacks that will be used for downloading.

  • download_dir (Path | str, optional) – Specifies the path where the dataset will be downloaded, by default “./data/download”

  • unpack_dir (Path | str, optional) – Specifies the path where the dataset will be unpacked into a custom directory structure, by default “./data/unpack”

  • download (bool, optional) – If the underlying dataset should be downloaded, by default True

  • transform (Callable, optional) – Specifies the PyTorch transforms to be used on the replaypack (dataset), Deprecated since version v1.5: Will be removed in v1.7.0, by default None

  • batch_size (int, optional) – The size of collating individual fetched data samples, by default 256

  • num_workers (int, optional) – How many sub-processes to use for data loading, by default 0

  • unpack_n_workers (int, optional) – The number of workers that will be used for unpacking the archive, by default 16

  • validator (Callable | None, optional) – Specifies the validation option for fetched data, this can also act as a filtering function that will be applied for the entirety of the dataset, by default None

transform = None
batch_size = 256
num_workers = 0
download_dir
unpack_dir
download = True
unpack_n_workers = 16
validator = None
replaypacks
prepare_data() → None
setup(stage: str | None = None) → None
train_dataloader() → torch.utils.data.dataloader.DataLoader
val_dataloader() → torch.utils.data.dataloader.DataLoader
test_dataloader() → torch.utils.data.dataloader.DataLoader
teardown(stage: str | None = None) → None