Yeah that is a good point. I do think that if we are going with Executor to
describe the runtime, we should rename the existing `tvm.relay.Executor`
interface to something e.g. `ExecutorWrapper`. We could also contemplate the
future of `relay.create_executor`, but should probably do that in a
Ah, I saw your latest comment from the TVM archiver to dev@ list. Maybe I
accidentally delete the previous emails. I think we are still good. Thanks,
Chris
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It looks like the forum is being archived. I don't know why that particular
topic was missed.
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https://github.com/apache/tvm-rfcs/pull/2#issuecomment-810619601
Are we not sending the copy of topics from discuss.tvm.apache.org to dev@
mailing list anymore?
I could not find the email copy for the TVM discuss that linked with this PR:
https://discuss.tvm.apache.org/t/rfc-update-rfc-process/9033
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The RFC repository has been seeded with a template, and I've sent up a pull
request that attempts to capture the process discussed here. Please take a look
and review, and we can formally begin the RFC process once that is complete.
https://github.com/apache/tvm-rfcs/pull/2
Thank!
Chris
You can view, comment on, or merge this pull request online at:
https://github.com/apache/tvm-rfcs/pull/2
-- Commit Summary --
* RFC Process Update
-- File Changes --
M README.md (60)
-- Patch Links --
https://github.com/apache/tvm-rfcs/pull/2.patch
https://github.com/apache/tvm-rfc
Thanks, the batched inputs thing makes sense, I misunderstood! I also didn't
mean to imply that batch size itself is unnecessary- I do think it's a fairly
universal concept for data loading (except for perhaps dynamic models where the
input shape changes for each instance, but in this case you
perhaps we should rename the existing GraphExecutor?
https://github.com/apache/tvm/blob/main/python/tvm/relay/build_module.py#L366
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