Your model works fine with an input of [batch_size, 3, 128, 128]:
model = AutoEncoder()
x = torch.randn(2, 3, 128, 128)
out = model(x)
print(out.shape)
> torch.Size([2, 3, 130, 130])

so I guess the shape of your model output doesn’t match the target shape.
If that’s the case, you would have to change the layer setups and make sure that both these tensors have an equal spatial size.