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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 acorr_lpc(x, axis=-1):
 """Compute autocorrelation of x along the given axis. This compute the biased autocorrelation estimator (divided by the size of input signal) Notes ----- The reason why we do not use acorr directly is for speed issue."""

    if not np.isrealobj(x):
        raise ValueError("Complex input not supported yet")

    maxlag = x.shape[axis]
    nfft = int(2 ** nextpow2(2 * maxlag - 1))

    if axis != -1:
        x = np.swapaxes(x, -1, axis)
    a = _acorr_last_axis(x, nfft, maxlag)
    if axis != -1:
        a = np.swapaxes(a, -1, axis)
    return a