simple way is fc(torch.cat((input1,input2,input3),-1)), memory efficient way is emulating nn.Linear layer: input1.mm(weight1.t()) + input2.mm(weight2.t()) + … + bias, where weights may be slices of nn.Parameter(output_size, total_input_size) in second dimension