The limitation is perhaps more with TE/TIR than it is TOPI, in that currently
*all* the scheduling decisions need to happen together. The proposed changes
with TensorIR would lift that constraint, but for it to actually be useful the
FuseOps pass would have to become a TIR pass rather than a R
>From your response to TQ I feel that the current limitation is mainly from the
>TOPI implementation, which fixed the granularity of conv2d schedule. This
>limitation, however, can potentially be resolved by auto-scheduler (Ansor). In
>fact, we AWS is attempting to use Ansor to perform more a
For the pending PRs, we could have TensorRT and Xilinx Vitis-AI as v0.8
experimental features.
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[Visit Topic](https://discuss.tvm.apache.org/t/discuss-tvm-v0-8-roadmap/8139/2)
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Closed #6623.
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All the open PR's base has been updated to main
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Thanks for everyone’s effort we have successfully released v0.7. As per Apache
way of development, we want broader involvement and inputs from community
developers on what we want to push for in the v0.8 release cycle.
This is a discussion thread to get everyone's thoughts about directions we
Closed #6421.
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Closed #6638.
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Closed #6486.
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Reopened #5519.
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Closed #5519.
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As of now, the default branch has been changed to main. I have also spend some
time to update base branch of the existing PRs, but it would be great to double
check for a bit when we merge PR this week.
@apache/tvm-committers please check the information when merging a PR ([XXX]
want to merge
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