import tensorflow as tf

                  .FullyConnected('fc2', out_dim=128, nl=tf.nn.relu)
                  .FullyConnected('fct', out_dim=19, nl=tf.identity)())
        tf.nn.softmax(logits, name='prob')

        cost = tf.nn.sparse_softmax_cross_entropy_with_logits(logits=logits, labels=label)
        cost = tf.reduce_mean(cost, name='cross_entropy_loss')

        wrong = tf.to_float(tf.logical_not(tf.nn.in_top_k(logits, label, 1)), name='incorrect_vector')
