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djstefanovicTT
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Codecov Report❌ Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## main #7017 +/- ##
==========================================
+ Coverage 69.26% 69.27% +0.01%
==========================================
Files 384 384
Lines 67207 67254 +47
==========================================
+ Hits 46550 46593 +43
- Misses 20657 20661 +4 ☔ View full report in Codecov by Sentry. |
azecevicTT
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Feb 12, 2026
Comment on lines
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2625
| // Compute the slice result type. | ||
| RankedTensorType sliceResultType; | ||
| if (needPad) { | ||
| // Intermediate type: sliced shape. | ||
| SmallVector<int64_t> slicedShape; | ||
| for (size_t i = 0; i < inputShape.size(); i++) { | ||
| slicedShape.push_back(sliceEnds[i] - sliceBegins[i]); | ||
| } | ||
| sliceResultType = | ||
| RankedTensorType::get(slicedShape, inputType.getElementType()); | ||
| } else { | ||
| // Final output type when only slicing is needed. | ||
| sliceResultType = cast<RankedTensorType>(op.getType()); | ||
| } |
Contributor
There was a problem hiding this comment.
IMO you don't have to optimize the case for the case when padding is not needed, you can put the calculation of the shape in the previous loop, that way it's much more obvious what the intention is.
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Ticket
closes #6959
Problem description
PyTorch supports negative padding in pad op as cropping. TTNN padOp does not allow this and causes errors.
What's changed
Added decomposition to
ttir.slice_staticop if there is negative padding.Checklist