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[MPS] Add bicubic2d_aa
#149378
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[MPS] Add bicubic2d_aa
#149378
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/149378
Note: Links to docs will display an error until the docs builds have been completed. ⏳ 19 Pending, 1 Unrelated FailureAs of commit 7b6c5bf with merge base acf42b0 ( UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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Attention! native_functions.yaml was changedIf you are adding a new function or defaulted argument to native_functions.yaml, you cannot use it from pre-existing Python frontend code until our FC window passes (two weeks). Split your PR into two PRs, one which adds the new C++ functionality, and one that makes use of it from Python, and land them two weeks apart. See https://github.com/pytorch/pytorch/wiki/PyTorch's-Python-Frontend-Backward-and-Forward-Compatibility-Policy#forwards-compatibility-fc for more info. Caused by: |
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LG if CI is happy
@pytorchbot merge -f "Human TD: Lint + MPS are green" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Which is currently the most frequently requested op in pytorch/pytorch#141287 Small TODO: refactor two AA functions into one ghstack-source-id: 87ca392 Pull Request resolved: pytorch/pytorch#149378
Stack from ghstack (oldest at bottom):
bicubic2d_aa
#149378Which is currently the most frequently requested op in #141287
Mostly done by refactoring
upsample_bilinear2d_aa
to accept Functor as one of the template arguments, which closely ideas from https://github.com/python-pillow/Pillow/blob/eec43cfbc0c9962af2b728677d1d011b311584db/src/libImaging/Resample.c as well aspytorch/aten/src/ATen/native/cuda/UpSampleBilinear2d.cu
Lines 472 to 478 in bb42e4d
Populate unit tests by copying upsample_bilinear_2d_aa and reusing it as upsample_bicubic2d_aa
At that point, only difference between upsample_bilinear2d_aa and upsample_bicubic2d_aa are convolution kernel function and size: for bilinear it's 3x3, for bicubic it's 5x5