      U.vprint(&#34;maxlen is %s&#34; % (maxlen), verbose=verbose)
    else:  # classification
        # set number of classes and multilabel flag
        num_classes = U.nclasses_from_data(train_data)

        # determine multilabel
        if multilabel is None:
            multilabel = U.is_multilabel(train_data)
        if multilabel and name in [NBSVM, LOGREG]:
            warnings.warn(
                &#34;switching to fasttext model, as data suggests &#34;
                &#34;multilabel classificat