load_dataset

load_dataset(day_index: int = 0, batch_size: int = 32, num_workers: int = 0, pin_memory: bool = True, shuffle: bool = False, object_type: Literal['VisionData', 'DataLoader'] = 'DataLoader') → Union[DataLoader, VisionData]

Get the mask dataset and return a dataloader.

Parameters

day_indexint, default: 0

Select the index of the day that should be loaded. 0 is the training set, and each subsequent number is a subsequent day in the production dataset. Last day index is 59.

batch_sizeint, default: 32

Batch size for the dataloader.

num_workersint, default: 0

Number of workers for the dataloader.

shufflebool, default: False

Whether to shuffle the dataset.

pin_memorybool, default: True

If True, the data loader will copy Tensors into CUDA pinned memory before returning them.

object_typeLiteral[‘Dataset’, ‘DataLoader’], default: ‘DataLoader’

type of the return value. If ‘Dataset’, deepchecks.vision.VisionData will be returned, otherwise torch.utils.data.DataLoader

Returns

Union[DataLoader, VisionDataset]

A DataLoader or VisionDataset instance representing mask dataset

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