Thanks for the good summarization. One concern that I have for this case is mainly about the coupling of the quantization part with the customized code generator.
While the application scenario is certainly understandable. We will need to resolve two questions, as an overall goal of the project. - P0: The relation with the existing quantization and which one to advocate for. - P1: The coupling of the customized code generator flow with the quantization. In the case of P0, I think it is best to focus on QNN and AutoQ, so that most of the quantized optimization are optimized in a transparent way. It is certainly important to produce hardware target aware quantization along the lines of AutoQ, so that we can generate better graphs that can be mapped to the low-level hw. We can certainly see some value in introducing this feature. However, given that the application scenario is somewhat limited, it would be useful to de-couple it from the existing set of features. In particular, the name BOYCQ suggests some level of coupling with the customized codegen target, which is not desirable. If the new feature is an optional pass that would not disrupt the existing flow, then it would be easier bring it in. It would be great if we can think about a way to plugin the opaque graph quantizer as a component of AutoQ. So that it is possible to directly feed data in and out to produce such transformed graph, before running the final code generation. The main motivation for such discussion is that, while it is possible to always introduce new features, every feature also brings technical debts, so it is important to think about ways to minimize the potential debts for future usecases. Finally i do think that opaque quantizer seems to be a bad idea in the long run, and is harder to get right than the opaque code generator, if there are ways to do things in a more transparent fashion(e.g. plugging things back to AutoQ and return back part of quantized graph) it is better to do things in that way --- [Visit Topic](https://discuss.tvm.ai/t/rfc-byoc-data-calibration-flow/7099/13) 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/8e98f9d6a8737b6935c90ff91142e42cecc3f2a77c5fb5a94167683da8514c2d).
