Yes! From the perspective of back-prop, I’m unclear what’s the difference between having the pre-emphasis happen outside of the network versus inside of the network as in the example below.
class Network(nn.Module):
    def __init__(self, c, ch):
        super(Network, self).__init__():
        self.pre_processing = PreEmphasis(c)
        self.convs = nn.Sequenial([nn.Conv1d(ch[0], ch[1]), nn.Conv1d(ch[1], ch[2])])

    def forward(self, input)
        x = self.pre_processing(input)
        x = self.convs(x)
        return x

class PreEmphasis(nn.Module):
    def __init__(self, coef):
        super(PreEmphasis, self).__init__()
        self.coef = coef

    def forward(self, x)
        return self.pre_emph(x, self.coef)

    def pre_emph(self, x, coef)
        # pre_emphasis fn on x with coef