How to use the kipoiseq.dataloaders.sequence.StringSeqIntervalDl function in kipoiseq

def test_fasta_based_dataset(intervals_file, fasta_file):
    # just test the functionality
    dl = StringSeqIntervalDl(intervals_file, fasta_file)
    ret_val = dl[0]
    assert isinstance(ret_val["inputs"], np.ndarray)
    assert ret_val["inputs"].shape == ()
    # # test with set wrong seqlen:
    # dl = StringSeqIntervalDl(intervals_file, fasta_file, required_seq_len=3)
    # with pytest.raises(Exception):
    #     dl[0]

    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="str")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.str_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="int")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.int_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="bool")
    ret_val = dl[0]

dl = StringSeqIntervalDl(intervals_file, fasta_file)
    ret_val = dl[0]
    assert isinstance(ret_val["inputs"], np.ndarray)
    assert ret_val["inputs"].shape == ()
    # # test with set wrong seqlen:
    # dl = StringSeqIntervalDl(intervals_file, fasta_file, required_seq_len=3)
    # with pytest.raises(Exception):
    #     dl[0]

    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="str")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.str_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="int")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.int_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="bool")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.bool_)
    vals = dl.load_all()
    assert vals['inputs'][0] == 'GT'

def test_fasta_based_dataset(intervals_file, fasta_file):
    # just test the functionality
    dl = StringSeqIntervalDl(intervals_file, fasta_file)
    ret_val = dl[0]
    assert isinstance(ret_val["inputs"], np.ndarray)
    assert ret_val["inputs"].shape == ()
    # # test with set wrong seqlen:
    # dl = StringSeqIntervalDl(intervals_file, fasta_file, required_seq_len=3)
    # with pytest.raises(Exception):
    #     dl[0]

    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="str")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.str_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="int")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.int_)
    dl = StringSeqIntervalDl(intervals_file, fasta_file, label_dtype="bool")
    ret_val = dl[0]
    assert isinstance(ret_val['targets'][0], np.bool_)
    vals = dl.load_all()
    assert vals['inputs'][0] == 'GT'

def __init__(self,
                 intervals_file,
                 fasta_file,
                 num_chr_fasta=False,
                 label_dtype=None,
                 auto_resize_len=None,
                 # max_seq_len=None,
                 # use_strand=False,
                 alphabet_axis=1,
                 dummy_axis=None,
                 alphabet="ACGT",
                 ignore_targets=False,
                 dtype=None):
        # core dataset, not using the one-hot encoding params
        self.seq_dl = StringSeqIntervalDl(intervals_file, fasta_file, num_chr_fasta=num_chr_fasta,
                                          label_dtype=label_dtype, auto_resize_len=auto_resize_len,
                                          # use_strand=use_strand,
                                          ignore_targets=ignore_targets)

        self.input_transform = ReorderedOneHot(alphabet=alphabet,
                                               dtype=dtype,
                                               alphabet_axis=alphabet_axis,
                                               dummy_axis=dummy_axis)