import tensorflow as tf

    variables_averages_op = variable_averages.apply(tf.trainable_variables())

    # Group all updates to into a single train op.
    train_op = tf.group(apply_gradient_op, variables_averages_op)

    # Create a saver.
    saver = tf.train.Saver(tf.global_variables())

    # Build the summary operation from the last tower summaries.
    summary_op = tf.summary.merge(summaries)

    # Build an initialization operation to run below.
    init = tf.global_variables_initializer()

    # Start running operations on the Graph. allow_soft_placement must be set to
    # True to build towers on GPU, as some of the ops do not have GPU
    # implementations.
    sess = tf.Session(config=tf.ConfigProto(
        allow_soft_placement=True,
        log_device_placement=FLAGS.log_device_placement))
    sess.run(init)

    # Start the queue runners.
    tf.train.start_queue_runners(sess=sess)
