def load_data():

   """Loads the Fashion-MNIST dataset.

   # Returns

       Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`.

   """

   dirname = os.path.join('datasets', 'fashion-mnist')

   base = 'http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/'

   files = ['train-labels-idx1-ubyte.gz', 'train-images-idx3-ubyte.gz',

            't10k-labels-idx1-ubyte.gz', 't10k-images-idx3-ubyte.gz']

   paths = []

   for fname in files:

       paths.append(get_file(fname,

                             origin=base + fname,

                             cache_subdir=dirname))

   with gzip.open(paths[0], 'rb') as lbpath:

       y_train = np.frombuffer(lbpath.read(), np.uint8, offset=8)

   with gzip.open(paths[1], 'rb') as imgpath:

       x_train = np.frombuffer(imgpath.read(), np.uint8,

                               offset=16).reshape(len(y_train), 28, 28)

   with gzip.open(paths[2], 'rb') as lbpath:

       y_test = np.frombuffer(lbpath.read(), np.uint8, offset=8)

   with gzip.open(paths[3], 'rb') as imgpath:

       x_test = np.frombuffer(imgpath.read(), np.uint8,

                              offset=16).reshape(len(y_test), 28, 28)

   return (x_train, y_train), (x_test, y_test)