Adjust output NJT ragged_idx for reductions and select() #141506
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/141506
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit bf290f5 with merge base efec302 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This was referenced Nov 25, 2024
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jbschlosser
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topic: bug fixes
cpuhrsch
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Nov 26, 2024
soulitzer
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Nov 26, 2024
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cyyever
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) This fixes some bugs when performing reductions / select() on dims before the ragged dim. In this case, the output NJT has a smaller number of dims, and its ragged_idx should reflect that correctly. Pull Request resolved: pytorch#141506 Approved by: https://github.com/cpuhrsch, https://github.com/soulitzer ghstack dependencies: pytorch#141500, pytorch#140736, pytorch#140161, pytorch#141392
pytorchmergebot
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…141604) Old logic was completely wrong, returning `chunk_size` chunks instead of the intended number. The original test didn't catch this because `chunk_size == num_chunks` :p New OpInfo-based testing covers it though. Pull Request resolved: #141604 Approved by: https://github.com/soulitzer ghstack dependencies: #141500, #140736, #140161, #141392, #141506
pobin6
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Dec 5, 2024
) This fixes some bugs when performing reductions / select() on dims before the ragged dim. In this case, the output NJT has a smaller number of dims, and its ragged_idx should reflect that correctly. Pull Request resolved: pytorch#141506 Approved by: https://github.com/cpuhrsch, https://github.com/soulitzer ghstack dependencies: pytorch#141500, pytorch#140736, pytorch#140161, pytorch#141392
pobin6
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Dec 5, 2024
…ytorch#141604) Old logic was completely wrong, returning `chunk_size` chunks instead of the intended number. The original test didn't catch this because `chunk_size == num_chunks` :p New OpInfo-based testing covers it though. Pull Request resolved: pytorch#141604 Approved by: https://github.com/soulitzer ghstack dependencies: pytorch#141500, pytorch#140736, pytorch#140161, pytorch#141392, pytorch#141506
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This fixes some bugs when performing reductions / select() on dims before the ragged dim. In this case, the output NJT has a smaller number of dims, and its ragged_idx should reflect that correctly.