code: def bisine_wahwah_wave(frequency):
    
    #
    # This is clearly intended to build on the bisine wave defined above,
    # so we can start by generating that.
    waves_a = bisine_wave(frequency)
    #
    # Then, by reversing axis 2, we swap the stereo channels. By mixing
    # this with `waves_a`, we'll be able to create the desired effect.
    waves_b = tf.reverse(waves_a, axis=[2])
    #
    # Let's have the balance oscillate from left to right four times.
    iterations = 4
    #
    # Now, we compute the balance for each sample: `ts` has values
    # in [0, 1] that indicate how much we should use `waves_a`.
    xs = tf.reshape(tf.range(_samples(), dtype=tf.float32), [1, _samples(), 1])
    thetas = xs / _samples() * iterations
    ts = (tf.sin(math.pi * 2 * thetas) + 1) / 2
    #
    # Finally, we can mix the two together, and we're done.
    wave = ts * waves_a + (1.0 - ts) * waves_b
    #
    # Alternately, we can make the effect more pronounced by exaggerating
    # the sample data. Let's emit both variations.
    exaggerated_wave = wave ** 3.0
    return tf.concat([wave, exaggerated_wave], axis=0)
docs: Emit two sine waves with balance oscillating left and right.