Hi there.
The error you get has nothing to do with your nn.Sequential code but is strictly Python based. Your code line output = model_4ch({0:input2, 1:input2}) sends one dict as an input to the forward function whilst you’ve defined two (both x1 and x2) inputs to the Python function.
Change your lineoutput = model_4ch({0:input2, 1:input2}) into output = model_4ch(input2, input2) (or maybe input1 input2?)
I’m pretty sure that your model can only handle one input so you’d have to combine your x1 & x2 before feeding that input to the model or feed the inputs separately. This could be done by the following code

def forward(self, x1, x2):
        inputs = torch.cat((x1, x2))
        return self.block(inputs)

or
def forward(self, x1, x2):
        output1 = self.block(x1)
        output2 = self.block(x2)
        return output1, output2

If this is not what you’re looking for, give us some more backbone to what you want to do. Gl