NJT unsqueeze() fixes #141392
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NJT unsqueeze() fixes #141392
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/141392
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 5d7f369 with merge base efec302 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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topic: bug fixes
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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@cyyever This stack caused regressions in the past, and re-landing it caused it again, see #140736 (comment) |
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This reverts commit 48409a5. Reverted #141392 on behalf of https://github.com/malfet due to Sorry for reverting your change but its tests are failing in trunk ([comment](#140736 (comment)))
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@jbschlosser your PR has been successfully reverted. |
This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after #137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. [ghstack-poisoned]
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This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after #137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. [ghstack-poisoned]
Merge failedReason: New commits were pushed while merging. Please rerun the merge command. Details for Dev Infra teamRaised by workflow job |
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Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 mandatory check(s) failed. The first few are: Dig deeper by viewing the failures on hud |
This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after #137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. [ghstack-poisoned]
This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after #137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. [ghstack-poisoned]
This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after #137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. [ghstack-poisoned]
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@pytorchbot merge |
Merge startedYour change will be merged once all checks pass (ETA 0-4 Hours). Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
cyyever
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Nov 27, 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
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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
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This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after pytorch#137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. Pull Request resolved: pytorch#141392 Approved by: https://github.com/cpuhrsch ghstack dependencies: pytorch#140736, pytorch#140161
pobin6
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Dec 5, 2024
This reverts commit 48409a5. Reverted pytorch#141392 on behalf of https://github.com/malfet due to Sorry for reverting your change but its tests are failing in trunk ([comment](pytorch#140736 (comment)))
pobin6
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Dec 5, 2024
This PR contains three `unsqueeze()`-related fixes for NJT: 1. Adjusts the output's `_ragged_idx` when `unsqueeze()` inserts a dim before the ragged dim 2. Corrects the unbind reference for `unsqueeze()` after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrt `inp.dim() + 1` to account for `dim=-1` properly 3. Adds ragged dim support to `unsqueeze()`, allowing for e.g. `(B, j1, D) -> (B, 1, j1, D)`. This is okay now after pytorch#137125 Note that `unsqueeze()` still doesn't support batch dim operation, and arguably should never support this. Pull Request resolved: pytorch#141392 Approved by: https://github.com/cpuhrsch ghstack dependencies: pytorch#141500, pytorch#140736, pytorch#140161
pobin6
pushed a commit
to pobin6/pytorch
that referenced
this pull request
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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Stack from ghstack (oldest at bottom):
This PR contains three
unsqueeze()-related fixes for NJT:_ragged_idxwhenunsqueeze()inserts a dim before the ragged dimunsqueeze()after the last input dim. For this case, the dim kwarg canonicalization logic needs to be applied wrtinp.dim() + 1to account fordim=-1properlyunsqueeze(), allowing for e.g.(B, j1, D) -> (B, 1, j1, D). This is okay now after Allow any single non-batch dim to be ragged for NJT #137125Note that
unsqueeze()still doesn't support batch dim operation, and arguably should never support this.