* fix interp scale factor sampling and pnnx recomputed sizes
Use the original scale factor for linear and cubic interpolation instead
of deriving coordinates from the truncated output size. Preserve explicit
sizes, reference sizes, and size expressions across CPU and Vulkan paths.
Keep same-axis linear behavior, resample non-unit same-size bicubic input,
and clamp interpolation taps for short axes without out-of-bounds reads.
Lower recompute_scale_factor to runtime size expressions, retain the flag
when importing nn.Upsample, and avoid deleting non-unit same-size resizes.
Add independent ncnn reference checks and pnnx static/dynamic round-trip
tests covering fractional up/downscales, recomputed sizes, short axes,
align_corners, and nn.Upsample.
Validated CPU interpolation tests, ASan/UBSan, Vulkan llvmpipe, and pnnx
TorchScript interpolation tests against PyTorch 2.10.0 CPU. The original
bilinear/bicubic reproductions fail on the base and pass with this fix.
Refs: Tencent/ncnn#6836, Tencent/ncnn#6837, Tencent/ncnn#6844
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Co-authored-by: Acture <acturea@gmail.com>
Co-authored-by: xy200303 <3483421977@qq.com>
Co-authored-by: nihui <171016+nihui@users.noreply.github.com>
nihui