How to use the ergo.dataset.Dataset function in ergo

def __init__(self, path):
        # base info
        self.path  = os.path.abspath(path)
        self.logic = Logic(self.path)
        # model related data
        self.model          = None
        self.accu           = None
        self.model_path     = os.path.join(self.path, 'model.yml')
        self.weights_path   = os.path.join(self.path, 'model.h5')
        self.fdeep_path     = os.path.join(self.path, 'model.fdeep')
        # training related data
        self.dataset         = Dataset(self.path)
        self.txt_stats_path  = os.path.join(self.path, 'stats.txt')
        self.json_stats_path = os.path.join(self.path, 'stats.json')
        self.history_path    = os.path.join(self.path, 'history.json')
        self.classes_path    = os.path.join(self.path, 'classes.json')
        self.history         = None
        self.classes         = None
        self.what            = {
            'train' : "Training --------------------------------------------\n",
            'val'   : "Validation ------------------------------------------\n",
            'test'  : "Test ------------------------------------------------\n"
        }

def _set_xys(self, for_training = True):
        if for_training:
            self.X_train, self.Y_train = Dataset.split_row(self.train, self.n_labels, self.is_flat)
            self.X_test,  self.Y_test  = Dataset.split_row(self.test, self.n_labels, self.is_flat)
            self.X_val,   self.Y_val   = Dataset.split_row(self.validation, self.n_labels, self.is_flat)
        else:
            self.X, self.Y = Dataset.split_row(self.train, self.n_labels, self.is_flat)