def kernal_mus(n_kernels):
    """
    get the mu for each gaussian kernel. Mu is the middle of each bin
    :param n_kernels: number of kernels (including exact match). first one is exact match
    :return: l_mu, a list of mu.
    """
    l_mu = [1]
    if n_kernels == 1:
        return l_mu

    bin_size = 2.0 / (n_kernels - 1)  # score range from [-1, 1]
    l_mu.append(1 - bin_size / 2)  # mu: middle of the bin
    for i in range(1, n_kernels - 1):
        l_mu.append(l_mu[i] - bin_size)
    return l_mu