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@3l1 3l1 commented Dec 25, 2025

Summary:
Dual LUT Strategy

Reviewed By: digantdesai

Differential Revision: D87120925

@3l1 3l1 requested a review from digantdesai as a code owner December 25, 2025 18:50
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pytorch-bot bot commented Dec 25, 2025

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/16396

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❌ 7 New Failures, 1 Cancelled Job, 1 Unrelated Failure

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@meta-cla meta-cla bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Dec 25, 2025
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meta-codesync bot commented Dec 25, 2025

@3l1 has exported this pull request. If you are a Meta employee, you can view the originating Diff in D87120925.

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Review automatically exported from Phabricator review in Meta.

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3l1 commented Dec 25, 2025

@pytorchbot label "release notes: none"

@pytorch-bot pytorch-bot bot added the release notes: none Do not include this in the release notes label Dec 25, 2025
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3l1 commented Dec 25, 2025

NOTE: I have pending changes before merging !!

Summary:


Dual LUT Strategy (from Bolt reference)
1. **Range LUT**: Covers full int16 range, LOW resolution at small values
2. **Resolution LUT**: Scaled input (x*128), HIGH resolution for codes 0-256

 Interpolation Weights
- **x <= 255**: Use resolution_lut (high accuracy for small values)
- **x >= 256**: Use range_lut (works fine for large values)
- **Transition at 255/256** to avoid interpolation artifacts

Buck Build Fixes
- Created TARGETS file in `/fb` subdirectory to enable Buck discovery
- Restructured parent TARGETS to break circular dependency (core → fb, passes → core + fb)
- Fixed Python circular import by importing directly from module files

Next Steps

- Full test suite validation
- Performance benchmarking
- Reduce number of rescale ops

Reviewed By: digantdesai

Differential Revision: D87120925
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