load_dataset#

load_dataset(train: bool = True, with_predictions: bool = True, batch_size: Optional[int] = None, shuffle: bool = False, n_samples: Optional[int] = None, object_type='VisionData') VisionData[source]#

Return MNIST VisionData, containing prediction produced by a simple fully connected model.

Model and data are taken from https://www.tensorflow.org/tutorials/quickstart/beginner.

Parameters
trainbool, defaultTrue

Train or Test dataset

with_predictionsbool, defaultTrue

Whether the returned VisonData should contain predictions

batch_size: int, optional

how many samples per batch to load

shufflebool , defaultFalse

To reshuffled data at every epoch or not.

n_samplesint, optional

Number of samples to load. Return the first n_samples if shuffle is False otherwise selects n_samples at random. If None, returns all samples.

object_typestr, default‘VisionData’

Kept for compatibility with torch datasets. Not used.

Returns
——-
:obj:`deepchecks.vision.VisionData`