How to use the kipoiseq.transforms.functional.one_hot_dna function in kipoiseq

def test_seq_dataset(intervals_file, fasta_file):
    dl = SeqIntervalDl(intervals_file, fasta_file)
    ret_val = dl[0]

    assert np.all(ret_val['inputs'] == one_hot_dna("GT"))
    assert isinstance(ret_val["inputs"], np.ndarray)
    assert ret_val["inputs"].shape == (2, 4)

def test_one_hot():

    seq = "ACGTTTATNT"
    assert len(seq) == 10

    assert one_hot_dna(seq).shape == (10, 4)
    assert one_hot(seq).shape == (10, 4)

    assert np.all(one_hot_dna(seq) == one_hot(seq))

    assert one_hot(pad(seq, 20)).shape == (20, 4)

    assert one_hot(fixed_len(seq, 20)).shape == (20, 4)
    assert one_hot(fixed_len(seq, 5)).shape == (5, 4)
    assert trim(seq, 5) == 'TTTAT'
    assert trim(seq, 5, 'start') == 'ACGTT'
    assert trim(seq, 5, 'end') == 'TATNT'
    with pytest.raises(Exception):
        assert pad(seq, 5, 'end') == 'TATNT'

    assert np.all(one_hot(seq)[0] == np.array([1, 0, 0, 0]))
    assert np.all(one_hot(seq)[1] == np.array([0, 1, 0, 0]))
    assert np.all(one_hot(seq)[2] == np.array([0, 0, 1, 0]))
    assert np.all(one_hot(seq)[3] == np.array([0, 0, 0, 1]))
    assert np.all(one_hot(seq)[4] == np.array([0, 0, 0, 1]))

def test_one_hot():

    seq = "ACGTTTATNT"
    assert len(seq) == 10

    assert one_hot_dna(seq).shape == (10, 4)
    assert one_hot(seq).shape == (10, 4)

    assert np.all(one_hot_dna(seq) == one_hot(seq))

    assert one_hot(pad(seq, 20)).shape == (20, 4)

    assert one_hot(fixed_len(seq, 20)).shape == (20, 4)
    assert one_hot(fixed_len(seq, 5)).shape == (5, 4)
    assert trim(seq, 5) == 'TTTAT'
    assert trim(seq, 5, 'start') == 'ACGTT'
    assert trim(seq, 5, 'end') == 'TATNT'
    with pytest.raises(Exception):
        assert pad(seq, 5, 'end') == 'TATNT'

    assert np.all(one_hot(seq)[0] == np.array([1, 0, 0, 0]))
    assert np.all(one_hot(seq)[1] == np.array([0, 1, 0, 0]))

with pytest.raises(Exception):
        assert pad(seq, 5, 'end') == 'TATNT'

    assert np.all(one_hot(seq)[0] == np.array([1, 0, 0, 0]))
    assert np.all(one_hot(seq)[1] == np.array([0, 1, 0, 0]))
    assert np.all(one_hot(seq)[2] == np.array([0, 0, 1, 0]))
    assert np.all(one_hot(seq)[3] == np.array([0, 0, 0, 1]))
    assert np.all(one_hot(seq)[4] == np.array([0, 0, 0, 1]))
    assert np.all(one_hot(seq)[-1] == np.array([0, 0, 0, 1]))
    assert np.all(one_hot(seq)[-2] == np.array([0.25, 0.25, 0.25, 0.25]))

    with pytest.raises(ValueError):
        one_hot(['A', 'C'])

    with pytest.raises(ValueError):
        one_hot_dna(['A', 'C'])

def __call__(self, seq):
        if self.alphabet == DNA and self.neutral_alphabet == ['N'] and self.neutral_value == 0.25:
            return F.one_hot_dna(seq, self.dtype)
        else:
            return F.one_hot(seq,
                             alphabet=self.alphabet,
                             neutral_alphabet=self.neutral_alphabet,
                             neutral_value=self.neutral_value,
                             dtype=self.dtype)