Hi,
Actually, a batch of images is like this (batch, channel, height, width), so you are passing your images wrongly.
And I do not understand why you are using unsqueeze(0) over there, it adds another dimension and it will cause error in first self.convB1_BW.
after removing unsqueeze(0), I tried below code, I have got another error coresponds to dimenstion mismatch in another layer.
x = torch.randn(1, 3,1024, 1024)
net = fuseNet()
x = net(x, x)

and the error:
# stage 1
--> 146         z = self.convB1_FS(torch.cat((y_1, x_1), dim=1))
    147         temp_t = torch.add(x_1, y_1)
    148         z = torch.add(z, temp_t)


invalid argument 0: Sizes of tensors must match except in dimension 1. Got 256 and 512 in dimension 2 at /pytorch/aten/src/TH/generic/THTensor.cpp:711