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 fromtest.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]#
- __new__(*args, **kwargs)#
Attributes
Return the path to the raw data folder. |
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Methods
Download the MNIST data if it doesn't exist already. |
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Reinforce the type for DataPipe instance. |
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