According to TLCBench, on CNNs like resnet50 and mobilenet, models tuned by auto-scheduler tend to be faster than AutoTVM. With the same setting, I've tested tuning Yolo v3 on Tesla T4 and the result is as follows.
| | AutoTVM | Auto-Scheduler (nchw) | Auto-Scheduler (nhwc) | |---- | ---- | ---- | ---- | |fp32 | 17.23 ms | 21.24 ms | 18.67 ms | |int8 | 8.54 ms | 15.85 ms | 15.92ms | Is there any possible reason or any missing important setting for int8 with auto-scheduler? Comparing debug_runtime results shows that for almost all layers conv2d AutoTVM is superior.  ### Experiment setting - Common - model: from darknet (input: 416x416) - opt_level: 3 - batch_size: 1 - AutoTVM - n_trial: 2000 - layout: nchw - tuner: xgb - early_stopping: 600 - number=20 - repeat=3 - timeout=4 - min_repeat_ms=150 - AutoScheduler - n_trial: 30000 (28 tasks) - layout: nhwc - repeat: 1 - min_repeat_ms: 200 - time_out: 20 - early_stopping: 2000 --- [Visit Topic](https://discuss.tvm.apache.org/t/auto-scheduler-seems-slower-on-int8/9585/1) 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/0498a6a4bf753d3da765036ae25a77ca0b9aace6880335ffe7820b7476ff19b4).
