[docs]classMadNorm(Layer):"""A function similar to the MAD normalization layer presented in quantizeml. (Note that the normalization is only available over the last dimension) Instead of using the standard deviation (std) during the normalization division, the sum of absolute values is used. The normalization is performed in this way: MadNorm(x) = x * gamma / sum(abs(x)) + beta Args: output_bits (int, optional): output bitwidth. Defaults to 8 buffer_bits (int, optional): buffer bitwidth. Defaults to 32. name (str, optional): name of the layer. Defaults to empty string. """def__init__(self,output_bits=8,buffer_bits=32,name=""):try:params=LayerParams(LayerType.MadNorm,{"output_bits":output_bits,"buffer_bits":buffer_bits,})# Call parent constructor to initialize C++ bindings# Note that we invoke directly __init__ instead of using super, as# specified in pybind documentationLayer.__init__(self,params,name)exceptBaseException:self=Noneraise