Thank you for your reply.
[quote="haichen, post:10, topic:6161"] The strategy to select implementations for `conv2d` op is defined at [here ](https://github.com/apache/incubator-tvm/blob/master/python/tvm/relay/op/strategy/cuda.py#L91-L198) [/quote] Which function in AutoTVM will use this strategy? [quote="puddingfjz, post:9, topic:6161"] Also, are there any examples or tutorials on how to use these templates? [/quote] I want to ask how to use one template which is implemented by TVM to autotune an operator, and someone already helped me on this, but I [still have a question](https://discuss.tvm.ai/t/how-to-use-autotvm-with-manually-created-topi-computations/4895/12?u=puddingfjz), and maybe you can help. [quote="puddingfjz, post:9, topic:6161"] are there templates with more kinds of knobs? [/quote] By reading the documents and some code, I find that there are four functions which can define the ```config_space```: ```define_split, define_reorder, define_annotate, define_knob```. I also find that ```define_split, define_knob``` are the most used. Is it because ```loop tiling``` and ```loop unrolling``` is the most important or comman techniques to automatically optimize an operator? Thank you in advance. --- [Visit Topic](https://discuss.tvm.ai/t/topi-winograd-convolution-performance-is-too-slow/6161/11) 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/6ba5dd9ab417e09fc7837f247c659c135b9a55101039f68abfa4632839fcd40c).
