import tensorflow as tf

    with tf.Session(config=config) as sess:
        t6 = time.time()
        sv3 = sess.run(approx_scskconv)
        t5 = time.time()
        for i in range(0, num_trials):
            sess.run(approx_scskconv)
        t6 = time.time()
        ts =  abs(t6 - t5) / max(num_trials,1)
        print("time approx sparse: ", ts)
    tf.reset_default_graph()
    
    time.sleep(1)
    
    if dense:
        td = 0
        with tf.device("/gpu:0"):
            conv = nn_ops.conv3d(d1, d2, strides, padding)
        with tf.Session(config=config) as sess:
            t22 = time.time()
            expected = sess.run(conv)
            t11 = time.time()
            for i in range(0, num_trials):
                sess.run(conv)
            t22 = time.time()
            td = abs(t22 - t11) / max(num_trials,1)
            print("time dense gpu: ", td)
        tf.reset_default_graph()

        print("time ratio: ", ts / td)
        return [expected, sv3, ts, td]
