Hi @masahi , I am not quite clear regarding this bias_add and add op folding that you mentioned.
So, what I intend to achieve and what I assume you are also implying above is as follows: case 1: >**before:** conv2d -> bias_add -> add (shift from batchnorm) is transformed to: > > **after transform:** conv2d -> bias_add ( bias values are changed by add op > folding into bias_add op) case 2: > **before:** conv2d -> add (shift from batchnorm) is transformed to: > >**after transform:** conv2d -> biad_add (add op expressed as bias _add op) Can you please confirm once if this is what you also meant above. Thanks for the catch.. yeah I tried now with SimplifyExpr but not seeing the desired changes in the relay graph. I shall see if I can find some helpful TVM transformation passes sequence in the cases 1 & 2. --- [Visit Topic](https://discuss.tvm.apache.org/t/batchnorm-op-fusion-in-tvm/12391/9) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.apache.org/email/unsubscribe/de1e4a219480588be301ae94a9bf240b8aaa85d7b3b4971f20198dd5d2512070).
