[GitHub] [incubator-tvm] giuseros edited a comment on pull request #6711: Improve AArch64 depthwise convolution through smlal/smlal2 intrinsic

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giuseros edited a comment on pull request #6711:
URL: https://github.com/apache/incubator-tvm/pull/6711#issuecomment-716586250


   Hi @FrozenGene 
   Thanks for your reply! 
   1) Yes we can, but there is a issue. It's very hard to have the two quantized strategies (int8 + smull/sadalp vs int16 + smlal/smlal2) available to the auto-tuner at the same time (you already saw [this post](https://discuss.tvm.apache.org/t/quantized-models-and-legalization-pass/8253/3), I will reply there to your comment). In the case of depthwise, we only have the int16 strategy, so the issue does not arise. 
   2) Nice you asked, because I am trying to prototype  the idea of a "tir pass" where this  tensorization (and possibly every arm tensorization in `tensor_intrin.py`) happens. My hope is to make it work more or less like `vectorize`. One of the main reasons to have this is to enable Ansor support


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