Re: [apache/tvm-rfcs] [RFC] Relax Upstreaming (PR #89)
In Intellif, people build, maintain and extend the DL compilation stack with Relay in past years. However, we never think the upstreaming of a new module would break existing functionalities or cause confusions, but huge opportunities to solve many technical issues which prove to be not so easy to handle in Relay, which are already emphasized in the discussion thread. >From my perspective the TVM community is a very inclusive community. We do >have modules of certain overlapped functionality co-exist without so much >debates. As examples we could see different runtime implementation for Relay, >TE-schedule and TensorIR-schedule, Ansor and meta-schedule, etc. Wish it is >also not a problem on graph ast infra. -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm-rfcs/pull/89#issuecomment-1268210986 You are receiving this because you are subscribed to this thread. Message ID:
[apache/tvm] [skip ci] Added label tags links to the wiki page in issue templates to align with Issue Tracking RFC (PR #12988)
Issue Tracking RFC - https://github.com/apache/tvm/issues/12801 cc: @areusch You can view, comment on, or merge this pull request online at: https://github.com/apache/tvm/pull/12988 -- Commit Summary -- * [skip ci] Added links to label tag wiki page in issue templates to align with Issue Tracking RFC -- File Changes -- M .github/ISSUE_TEMPLATE/bug-report.md (4) M .github/ISSUE_TEMPLATE/ci-problem.md (2) M .github/ISSUE_TEMPLATE/documentation.md (2) M .github/ISSUE_TEMPLATE/feature-tracking.md (2) M .github/ISSUE_TEMPLATE/flaky-test.md (2) -- Patch Links -- https://github.com/apache/tvm/pull/12988.patch https://github.com/apache/tvm/pull/12988.diff -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm/pull/12988 You are receiving this because you are subscribed to this thread. Message ID:
Re: [apache/tvm-rfcs] [RFC] Relax Upstreaming (PR #89)
Thanks for this great job ! Based on our experience at Meituan, dynamic shape is important for our use cases, e.g. OCR and ASR models with dynamic seq_len. Now we could solve these with relax and vm runtime :) -- Reply to this email directly or view it on GitHub: https://github.com/apache/tvm-rfcs/pull/89#issuecomment-1268593073 You are receiving this because you are subscribed to this thread. Message ID:
