eq_len=maxlen
    )
    inputs = model.inputs[:2]
    dense = model.get_layer(&#34;NSP-Dense&#34;).output
    outputs = keras.layers.Dense(units=num_classes, activation=activation)(dense)
    model = keras.Model(inputs, outputs)
    model.compile(loss=loss_func, optimizer=U.DEFAULT_OPT, metrics=metrics)
    return model


def _build_transformer(
    num_classes,
    maxlen,
    max_features,
    features,
    loss_func=&#34;categorical_crossentropy&#34;,
    activation=&#34;softmax&#34;,
    metrics=[&#34;a