@matt-arm For each BYOC backend such as DNNL, we could define a transform sequence so that we can have `mod = transform.partition("dnnl")(mod)`. However, there are some issues should be further discussed. For example, where should we put those transform sequences (e.g., put them under `tvm.transform` and ask users to manually invoke, or integrate them along with the `PassContext` or `relay.build` to automatically invoke). We could file another RFC to discuss the proposals and APIs.
On the other hand, IMHO, the data calibration flow is an optional analysis pass, so it should be put under analysis passes as proposed. We could discuss how to abstract such BYOC related analysis passes with transform passes in another RFC as well. Talking back to the calibration flow, I just realized that the `calibrate_partition_gaph` is not necessary to be a BYOC specific pass. We could rename it to something like `profile_subgraph` to make it general for all Relay programs. The pass accepts a Relay program and returns complete values of every function boundary tensors. --- [Visit Topic](https://discuss.tvm.ai/t/rfc-byoc-data-calibration-flow/7099/9) to respond. You are receiving this because you enabled mailing list mode. To unsubscribe from these emails, [click here](https://discuss.tvm.ai/email/unsubscribe/a43f1a20c200035e0d0f348f5138c36fb6bb063ccc5e58e07ccfef5553b5e1ae).