Fix: preserve creator edges in deps_viewer reduced and omitted modes#1377
Fix: preserve creator edges in deps_viewer reduced and omitted modes#1377indigo1973 wants to merge 1 commit into
Conversation
|
Important Review skippedAuto incremental reviews are disabled on this repository. Please check the settings in the CodeRabbit UI or the ⚙️ Run configurationConfiguration used: Organization UI Review profile: CHILL Plan: Pro Run ID: You can disable this status message by setting the Use the checkbox below for a quick retry:
📝 WalkthroughWalkthrough
ChangesLifetime-aware dependency reduction
Estimated code review effort: 2 (Simple) | ~10 minutes Poem
🚥 Pre-merge checks | ✅ 5✅ Passed checks (5 passed)
Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out. Comment |
There was a problem hiding this comment.
Code Review
This pull request updates the transitive reduction logic in deps_viewer.py to preserve tensor-lifetime edges (where source=creator) while continuing to reduce redundant scheduling edges. It also updates the CLI help, documentation, and adds unit tests to verify this behavior. The review feedback suggests adding a defensive type check when parsing annotations to prevent potential AttributeError exceptions from malformed data.
Important
The consumer version of Gemini Code Assist on GitHub is being sunset. Starting June 18, 2026, new organization installations will be blocked, and all code review activity will officially cease on July 17, 2026.
For more details on the timeline and next steps, please review the Help Documentation.
- Keep creator references out of v1 structural reduction - Add reduced_v2 and omitted_v2 with conservative byte-range INOUT dataflow proof - Preserve OUTPUT_EXISTING reuse boundaries and document the new modes - Cover middle-output reduction, cross-round retention, and CLI selection
Preserve source=creator edges during transitive reduction because they
encode tensor lifetime retention rather than redundant scheduling
dependencies. Continue reducing transitively covered explicit and
tensormap edges.
Pass edge annotations into the reduction logic, add regression coverage
based on the vector_example dependency pattern, and update the
deps_viewer documentation.