Ansor uses its XGBoost based cost model in an advanced manner. Each prediction is a sum of several XGBoost calls. To train the model, a "pack-sum" loss is used.
Training a cost model in this way seems interesting. Can anyone explain the mechanism in detail? The only thing I got is the source code (https://github.com/apache/tvm/blob/main/python/tvm/auto_scheduler/cost_model/xgb_model.py) --- [Visit Topic](https://discuss.tvm.apache.org/t/question-about-the-pack-sum-loss-of-xgboost-in-ansor/10651/1) 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/0183b7f105fe2c872f64b7183231f13e348c39f6320b23af5ccd299b1432faa2).
