IterableTorchMnistDataset#

class IterableTorchMnistDataset[source]#

Iterable MNIST <http://yann.lecun.com/exdb/mnist/>`_ Dataset.

Parameters

batch_size: int, default=64: Batch size to use
train: bool, default: true: If True, creates dataset from training.pt, otherwise from test.pt.
transform: t.Optional[t.Callable], default: None: A function/transform that takes in an PIL image and returns a transformed version. E.g, transforms.RandomCrop
n_samples: int, default: None: Number of samples to use. If None, use all samples.

__init__(batch_size: int = 64, train: bool = True, transform: Optional[Callable] = None, n_samples: Optional[int] = None) → None[source]#

static __new__(cls, *args, **kwds)#

Attributes

`IterableTorchMnistDataset.mirrors`
`IterableTorchMnistDataset.raw_folder`	Return the path to the raw data folder.
`IterableTorchMnistDataset.resources`

Methods

IterableTorchMnistDataset.download()

Download the MNIST data if it doesn't exist already.

previous

TorchMnistDataset.extra_repr

next

IterableTorchMnistDataset.mirrors