Thanks for the advice. This seems like a good start.
I've been playing around with auto-tuner module and thinking that we may utilize the performance of the default schedule during the tuning process. 2nd approach seems more relevant for my purpose. Rather than defining a default configuration by myself as the 1st approach, I want to measure the performance of the current default configuration in the tuner model. Is *fallback_with_reference_log* the one I can use? I'm not sure since it does not return any configuration. (Seems like it applies directly to the kernel?) As far as I know, I need a set of optimization configurations (*config* in the following code) for the default setting to trigger the measurement inside the tuner. https://github.com/apache/incubator-tvm/blob/master/python/tvm/autotvm/tuner/tuner.py#L122 Thank you so much for the great advices! --- [Visit Topic](https://discuss.tvm.ai/t/autotvm-find-the-default-optimization-configuration-of-the-kernel/6090/6) 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/b72609ed1008689a0653c51573b3339f0372edf8e5c615733e2e9036b547a86c).
