Pytorch Residual Module for use with nn.Sequential

residual.py

class Residual(t.nn.Module):
    def __init__(self, *args: t.nn.Module):
        super().__init__()
        self.delegate = t.nn.Sequential(*args)

    def forward(self, inputs):
        return self.delegate(inputs) + inputs

usage.py

net = t.nn.Sequential(
    t.nn.Conv2d(z_size, hid, 3, padding=1),
    t.nn.ELU(),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    Residual(
        t.nn.Conv2d(hid, hid, 1),
        t.nn.ELU(),
        t.nn.Conv2d(hid, hid, 1),
    ),
    t.nn.Conv2d(hid, z_size, 1)
)