Hi @582990,
Every operator of a convolutional networks is implemented through one or more strategies (strategy=compute+schedule). Every strategy needs to be tuned and represents a "task". If a strategy defines no knobs, the tuning of that strategy will be a nop. To reduce the number of tasks, you can simply look at `tvm/relay/op/strategy/cuda.py` and see if any of the operators you are using is "trying" multiple strategies. If this is the case, you can select a single strategy so reducing the amount of tasks. However, if all your operators are using a single strategy, things get more complicated, as you should try to force the compiler to select (only for some layers) an "untuned" operator (it would still appear as a task, but without any knobs to tune). Hope this helps, Giuseppe --- [Visit Topic](https://discuss.tvm.apache.org/t/tvm-auto-tune-reducing-the-number-of-tasks/8503/2) 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/d0f912a15b3f7db0ee69ab90a74cff0f6dae92ef45877c6090c5c1264b06c3ee).
