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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 _interp_kernel_ft(norm_freqs, interp):
 """Scaled FT of a one-dimensional interpolation kernel. For normalized frequencies ``-1/2 <= xi <= 1/2``, this function returns:: sinc(pi * xi)**k / sqrt(2 * pi) where ``k=1`` for 'nearest' and ``k=2`` for 'linear' interpolation. Parameters norm_freqs : `numpy.ndarray` Normalized frequencies between -1/2 and 1/2 interp : {'nearest', 'linear'} Type of interpolation kernel Returns ------- ker_ft : `numpy.ndarray` Values of the kernel FT at the given frequencies """

    # Numpy's sinc(x) is equal to the 'math' sinc(pi * x)
    ker_ft = np.sinc(norm_freqs)
    interp_ = str(interp).lower()
    if interp_ == 'nearest':
        pass
    elif interp_ == 'linear':
        ker_ft *= ker_ft
    else:
        raise ValueError("`interp` '{}' not understood".format(interp))

    ker_ft /= np.sqrt(2 * np.pi)
    return ker_ft