

def __init__(self, one_hot=False, **kwargs):
    dir = '/Volumes/Storage/Unilever_Challenge/dataset'
    with open((dir + '/train.npy')) as Xin:
        data = np.load(Xin)
    (X, y) = self.make_Xy(data)
    if one_hot:
        y = make_one_hot(y, 8)
    else:
        y = y.reshape((y.shape[0], 1))
    super(Unilever, X).__init__(X=X, y=y, **kwargs)

dataset/ETHPy150Open hycis/Pynet/pynet/datasets/unilever.py Unilever.__init__/VarMisuse@100/133 `self`->`X`