human
Complete the below
def forward(data, impulse_response=None, filter_params={}, predefined_filter=None):

    ''''Apply the given filter to data.
    Parameters
    data : (M,N) ndarray
    Input data.
    impulse_response : callable `f(r, c, **filter_params)`
    Impulse response of the filter.  See LPIFilter2D.__init__.
    filter_params : dict
    Additional keyword parameters to the impulse_response function.
    Other Parameters
    predefined_filter : LPIFilter2D
    If you need to apply the same filter multiple times over different
    images, construct the LPIFilter2D and specify it here.
    Examples
    Gaussian filter:
    >>> def filt_func(r, c):
    ...     return np.exp(-np.hypot(r, c)/1)
    >>> from skimage import data
    >>> filtered = forward(data.coins(), filt_func)'
    '''

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Write me a the Python program you requested?
assistant
#Here is the Python program you requested.
    assert_nD(data, 2, 'data')
    if (predefined_filter is None):
        predefined_filter = LPIFilter2D(impulse_response, **filter_params)
    return predefined_filter(data)