mxnet.gluon.data.vision.datasets.FashionMNIST¶

class mxnet.gluon.data.vision.datasets.FashionMNIST(root='/var/lib/jenkins/.mxnet/datasets/fashion-mnist', train=True, transform=None)[source]¶

A dataset of Zalando’s article images consisting of fashion products, a drop-in replacement of the original MNIST dataset from https://github.com/zalandoresearch/fashion-mnist

Each sample is an image (in 3D NDArray) with shape (28, 28, 1).

Parameters

root (str, default $MXNET_HOME/datasets/fashion-mnist') – Path to temp folder for storing data.
train (bool, default True) – Whether to load the training or testing set.
transform (function, default None) –
A user defined callback that transforms each sample. For example:
```
transform=lambda data, label: (data.astype(np.float32)/255, label)
```

__init__(root='/var/lib/jenkins/.mxnet/datasets/fashion-mnist', train=True, transform=None)[source]¶: Initialize self. See help(type(self)) for accurate signature.

Methods

`__init__`([root, train, transform])	Initialize self.
`transform`(fn[, lazy])	Returns a new dataset with each sample transformed by the transformer function fn.
`transform_first`(fn[, lazy])	Returns a new dataset with the first element of each sample transformed by the transformer function fn.