1.Basically i am replicating the software in hardware(verilog coding),so to code Bnorm in hardware its very complicated
2.So i have fused(learnable parametrs) the Bnorm of my first layer with Conv (Conv->Bnorm)
3. For FC I have Bnorm  in 3rd FC layer, I want to avoid these in my model, so it will be useful to code in hardware
4. So thought of fusing Bnorm with  near by layers
5.My FC2 and FC3 layers looks like (Linear->Relu->Bnorm->dropout->Linear)
6.I tried to fuse (Linear->Relu->Bnorm->dropout->Linear) it didn’t worked out due to its shape
7. So I tried to fuse (Linear->Relu->Bnorm->dropout->Linear), I fused it but  prediction are not correct by taking fused weights and bias
8.So I want to try to fuse(learnable parameter) (Linear->Relu) and then fused result again to fuse with Bnorm
9.Is that possible to do ?
Your help will be appreciated