Why the count of parameters and flops differ from that shown in the paper?

[Casey-bit]

Here are my codes.

model = Change_detection() input1 = torch.rand((1, 3, 256, 256)) input2 = torch.rand((1, 3, 256, 256)) from fvcore.nn import FlopCountAnalysis, flop_count_table model.eval() flops = FlopCountAnalysis(model, (input1, input2)) print(flop_count_table(flops))

Thank you for help.