Hi,
You can pass multiple inputs to the forward call of the network, that is not a problem, just pass a Variable and you will be fine.
About merging the fc layers, you can do any operation you want, for example concatenating the outputs (via torch.cat([res1, res2],1)), summing them, etc.
Here is a simplified example
class SimpleConv(nn.Module):
    def __init__(self):
        super(SimpleConv, self).__init__()
        self.features = nn.Sequential(
            nn.Conv2d(1, 1, kernel_size=3, stride=1, padding=1),
            nn.ReLU(inplace=True),
        )

    def forward(self, x, y):
        x1 = self.features(x)
        x2 = self.features(y)
        x = torch.cat((x1, x2), 1)
        return x