def flip_attributes()

in src/model.py [0:0]

• 22 lines of code
• 4 McCabe index (conditional complexity)

def flip_attributes(attributes, params, attribute_id, new_value=None):
    """
    Randomly flip a set of attributes.
    """
    assert attributes.size(1) == params.n_attr
    mappings = get_mappings(params)
    attributes = attributes.data.clone().cpu()

    def flip_attribute(attribute_id, new_value=None):
        bs = attributes.size(0)
        i, j = mappings[attribute_id]
        attributes[:, i:j].zero_()
        if new_value is None:
            y = torch.LongTensor(bs).random_(j - i)
        else:
            assert new_value in range(j - i)
            y = torch.LongTensor(bs).fill_(new_value)
        attributes[:, i:j].scatter_(1, y.unsqueeze(1), 1)

    if attribute_id == 'all':
        assert new_value is None
        for attribute_id in range(len(params.attr)):
            flip_attribute(attribute_id)
    else:
        assert type(new_value) is int
        flip_attribute(attribute_id, new_value)

    return Variable(attributes.cuda())