ekalda commented on code in PR #14483:
URL: https://github.com/apache/tvm/pull/14483#discussion_r1158615483
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python/tvm/topi/arm_cpu/conv2d_spatial_pack.py:
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@@ -316,12 +317,23 @@ def _tile_size(axis, candidates):
return candidate
return 1
- # Tile size 8 results in efficient vectorization for these schedules.
- # If the axis is not divisible by 8, try 4
+ # For data tensors with unity height and width we can leave it to the
+ # backend to vectorize the inner loop. This has been observed to be
more
+ # performant on SVE targets with a vector width > 128bits.
+ target = Target.current(allow_none=False)
+ if target.features.has_sve and OW == OH and OW == 1:
Review Comment:
Is there no required minimum length for the output channels for this to be
beneficial?
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