def load_fashion_mnist_dataset(shape=(-<NUM_LIT:1>, <NUM_LIT>), path='<STR_LIT:data>'):
return _load_mnist_dataset(<EOL>shape, path, name='<STR_LIT>', url='<STR_LIT>'<EOL>)<EOL>
Load the fashion mnist.

    Automatically download fashion-MNIST dataset and return the training, validation and test set with 50000, 10000 and 10000 fashion images respectively, `examples <http://marubon-ds.blogspot.co.uk/2017/09/fashion-mnist-exploring.html>`__.

    Parameters
    ----------
    shape : tuple
        The shape of digit images (the default is (-1, 784), alternatively (-1, 28, 28, 1)).
    path : str
        The path that the data is downloaded to.

    Returns
    -------
    X_train, y_train, X_val, y_val, X_test, y_test: tuple
        Return splitted training/validation/test set respectively.

    Examples
    --------
    >>> X_train, y_train, X_val, y_val, X_test, y_test = tl.files.load_fashion_mnist_dataset(shape=(-1,784), path='datasets')
    >>> X_train, y_train, X_val, y_val, X_test, y_test = tl.files.load_fashion_mnist_dataset(shape=(-1, 28, 28, 1))