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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def init_tf_ops(sess):
 """Initialize TensorFlow operations. This function initialize the following tensorflow ops: * init variables ops * summary ops * create model saver Parameters sess : object Tensorflow `Session` object Returns ------- tuple : (summary_merged, summary_writer) * tf merged summaries object * tf summary writer object * tf saver object """

    summary_merged = tf.summary.merge_all()
    init_op = tf.global_variables_initializer()
    saver = tf.train.Saver()

    sess.run(init_op)

    # Retrieve run identifier
    run_id = 0
    for e in os.listdir(Config().logs_dir):
        if e[:3] == 'run':
            r = int(e[3:])
            if r > run_id:
                run_id = r
    run_id += 1
    run_dir = os.path.join(Config().logs_dir, 'run' + str(run_id))
    print('Tensorboard logs dir for this run is %s' % (run_dir))

    summary_writer = tf.summary.FileWriter(run_dir, sess.graph)

    return (summary_merged, summary_writer, saver)