no-op binary removal #1764
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no-op binary removal #1764
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Still running tests locally. Would wait on that before merging. |
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Tests passed, I'm merging this~ |
shmsong
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Jul 24, 2022
Syncing nvfuser devel branch to upstream master. https://github.com/csarofeen/pytorch/ Code changes includes: - TransformPropagator refactor: switched to Dijkstra instead of exhaustive enumeration on all possible paths to reduce compilation time on transform propagation; - Indexing refactor: remove reference tensor creation in all tensor indexing logic (csarofeen#1690) - (more) generic grouped grid reduction kernel; - Minor parser/fuser patches: 1. zero-dim tensor reduction support 3. no-op binary removal within fused graph 4. expand supported in fusion Squashed commits to WAR github API Commits that's actually in this PR from the devel branch: ``` a054b3e Refactor TransormPropagator to allow specifying a position and propagating to part of the DAG (csarofeen#1775) d67e1cd Indexing refactor stage 1: remove reference tensor creation in all tensor indexing logic (csarofeen#1690) 1b65299 Issue 1770 (csarofeen#1774) 35b0427 Avoid compilation errors like below: (csarofeen#1773) 452c773 Ignore reductions of zero-dim tensors per PyTorch conventions (csarofeen#1771) 31d6c56 TransformPropagator refactor (csarofeen#1769) 570c5a8 Merge pull request csarofeen#1767 from csarofeen/upstream_merge_0621 9d6c3d8 merging upstream 61305cd 0ed815f New TransformPropagator algorithm (csarofeen#1763) 6c19520 no-op binary removal (csarofeen#1764) ec7fa41 Proper propagation of IterType (csarofeen#1762) b263562 Fix dimensionality check (csarofeen#1759) 2d6343f More generic grouped grid reduction kernel (csarofeen#1740) 64e2b56 [nvfuser] prevent spamming warning message (pytorch#77777) (csarofeen#1758) 0c43162 [nvFuser] Improving bitwise ops support (pytorch#77158) (csarofeen#1757) b93a147 Parser expand (csarofeen#1754) ``` RUN_TORCHBENCH: nvfuser Pull Request resolved: pytorch#80355 Approved by: https://github.com/davidberard98
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Removes no-op binary op inside fusion. We can ignore aliasing in this pass since we are in fusion section.
e.g. add(tensor, /other/ 0, /alpha/ 1) or mul(tensor, /other/ 1)