[Enhancement]Replace numpy ascontiguousarray with torch contiguous to speed-up #2604
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Merge MMSegmentation 1.x development branch dev-1.x to main branch 1.x for v1.0.0rc2
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Codecov ReportBase: 83.25% // Head: 83.35% // Increases project coverage by
Additional details and impacted files@@ Coverage Diff @@
## dev-1.x #2604 +/- ##
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+ Coverage 83.25% 83.35% +0.09%
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Files 145 145
Lines 8505 8508 +3
Branches 1273 1274 +1
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+ Hits 7081 7092 +11
+ Misses 1213 1202 -11
- Partials 211 214 +3
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MeowZheng
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MeowZheng
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Apr 5, 2024
… speed-up (open-mmlab#2604) ## Motivation Original motivation was after [MMDetection PR #9533](open-mmlab/mmdetection#9533) With several experiments I found out that if a ndarray is contiguous, numpy.transpose + torch.contiguous perform better, while if not, then use numpy.ascontiguousarray + numpy.transpose ## Modification Replace numpy.ascontiguousarray with torch.contiguous in [PackSegInputs](https://github.com/open-mmlab/mmsegmentation/blob/1.x/mmseg/datasets/transforms/formatting.py) Co-authored-by: MeowZheng <[email protected]>
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Motivation
Original motivation was after MMDetection PR #9533
With several experiments I found out that if a ndarray is contiguous, numpy.transpose + torch.contiguous perform better, while if not, then use numpy.ascontiguousarray + numpy.transpose
Modification
Replace numpy.ascontiguousarray with torch.contiguous in PackSegInputs