'Find the model and build the graph.'

def build_model(self, model, reader):

    label_loss_fn = find_class_by_name(FLAGS.label_loss, [losses])()
    optimizer_class = find_class_by_name(FLAGS.optimizer, [tf.train])
    build_graph(reader=reader, model=model, optimizer_class=optimizer_class, clip_gradient_norm=FLAGS.clip_gradient_norm, train_data_pattern=FLAGS.train_data_pattern, label_loss_fn=label_loss_fn, base_learning_rate=FLAGS.base_learning_rate, learning_rate_decay=FLAGS.learning_rate_decay, learning_rate_decay_examples=FLAGS.learning_rate_decay_examples, regularization_penalty=FLAGS.regularization_penalty, num_readers=FLAGS.num_readers, batch_size=FLAGS.batch_size, num_epochs=FLAGS.num_epochs)
    return tf.train.Saver(max_to_keep=0, keep_checkpoint_every_n_hours=0.25)
