import tensorflow as tf

    infer_graph = tf.Graph()
    with train_graph.as_default():
        initializer = tf.random_uniform_initializer(-config.init_scale,
                                                    config.init_scale)

        with tf.name_scope('Train'):
            train_input = DataInput(config=config, data=train_data, name='TrainInput')
            with tf.variable_scope('Model', reuse=None, initializer=initializer):
                m = Model(is_training=True, config=config, input_=train_input, graph=train_graph)
            tf.summary.scalar('Training Loss', m.cost)
