CBL.py

class CBL(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride, padding):
        super(CBL, self).__init__()

        conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding, bias=False)
        bn = nn.BatchNorm2d(out_channels, eps=1e-3, momentum=0.03)

        self.cbl = nn.Sequential(
            conv,
            bn,
            # https://pytorch.org/docs/stable/generated/torch.nn.SiLU.html
            nn.SiLU(inplace=True)
        )

    def forward(self, x):
        return self.cbl(x)