

def __init__(self, input=None, target=None, train=None, valid=None, test=None, limit=None):
    super(Dataset, self).__init__()
    self._limit = limit
    self._train = Subset()
    self._valid = Subset()
    self._test = Subset()
    if ((input is not None) and (target is not None)):
        self._input = input
        self._target = target
    elif ((train is not None) and (valid is not None) and (test is not None)):
        self._input = _combine(train.input, valid.input, test.input)
        self._target = _combine(train.target, valid.target, test.target)
        if isinstance(train.input, list):
            self._train.input = [HierarData(X, limit=self._limit) for X in train.input]
            self._valid.input = [HierarData(X, limit=self._limit) for X in valid.input]
            self._test.input = [HierarData(X, limit=self._limit) for X in test.input]
        else:
            self._train.input = HierarData(train.input, limit=self._limit)
            self._valid.input = HierarData(valid.input, limit=self._limit)
            self._test.input = HierarData(test.input, limit=self._limit)
        if isinstance(train.target, list):
            self._train.target = [HierarData(X, limit=self._limit) for X in train.target]
            self._valid.target = [HierarData(X, limit=self._limit) for X in valid.target]
            self._test.target = [HierarData(X, limit=self._limit) for X in test.target]
        else:
            self._train.target = HierarData(train.target, limit=self._limit)
            self._valid.target = HierarData(valid.target, limit=self._limit)
            self._test.target = HierarData(test.target, limit=self._limit)
        n_train = _get_n(train.input)
        n_valid = _get_n(valid.input)
        n_test = _get_n(test.input)
        self._train_ind = np.arange(n_train)
        self._valid_ind = np.arange(n_train, (n_train + n_valid))
        self._test_ind = np.arange((train + n_valid), ((n_train + n_valid) + n_test))
    else:
        raise ValueError('Invalid combination of arguments')

dataset/ETHPy150Open Cysu/dlearn/dlearn/data/dataset.py Dataset.__init__/VarMisuse@535/636 `n_train`->`train`