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[PHI] Fixed argsort big tensor bug by Enigmatisms · Pull Request #72712 · PaddlePaddle/Paddle · GitHub
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[PHI] Fixed argsort big tensor bug #72712
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你的PR提交成功,感谢你对开源项目的贡献! |
lshpku
approved these changes
May 15, 2025
wanghuancoder
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May 27, 2025
* [PHI] Fixed argsort big tensor bug * [PHI] Fixed shape mismatch problem.
wanghuancoder
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that referenced
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Jun 3, 2025
* refine forrange (#72360) * refine forrange * refine forrange * reduce support big tensor (#71970) * reduce support big tensor * [PHI] Fix gridDim limit for reduce kernel (#72507) * [API] isclose support bigtensor (#72516) * isclose support bigtensor * refine * [API] isnan isinf isfinite support bigtensor (#72517) * isnan isinf isfinite support bigtensor * refine * [PHI] Fix cum kernel for big tensor (#72562) * [PHI] Preliminary fix for elementwise broadcast int32 shape overflow (#72584) * [PHI] Align linalg.solve kernel with torch (#72608) * Update strided copy kernel (#72662) * [PHI] Fix grid sample kernel for big tensor (#72628) * [PHI] Fix argsort big tensor bug (#72712) * [PHI] Fixed argsort big tensor bug * [PHI] Fixed shape mismatch problem. * [PHI] Fix contiguous kernel for big tensor (#72705) * [PHI] Fix flatten and split kernel for big tensor (#72634) * [PHI] Fix out-of-bound issue of paddle.take_along_axis (#72757) * [PHI] fix paddle.diag with big tensor (#72638) * [API] fix paddle.cross with big tensor (#72652) * [PHI] Fix paddle.where api for big tensor (#72717) * [PHI] Fix bincount kernel for big tensor (#72706) * fix bincount kernel for big tensor * use HostAlloc to alloc memory * add cpu test case * [PHI] Fix full_like kernel for big tensor (#72831) * [API] Fix int overflow and float16 support for paddle.frac (#72815) * [PHI] Align paddle.inner with torch in matmul logic (#72843) * [PHI] Fix paddle.var & paddle.std float16 overflow (#72650) * [PHI] Fix logsumexp precision problem (#72681) * [PHI] Debug for logsumexp, bug source found * [PHI] Removed GetNumBlocks func to get correct logsumexp * [PHI] Removed redundant debug VLOG * [PHI] Elegant grid bounded solution * [Accuracy diff No.55-56、76-77] Fix accuracy diff for var&std API (#72879) * [Accuracy diff No.21] Fix accuracy diff for heaviside API (#72894) --------- Co-authored-by: Shuhao Liang <50269654+lshpku@users.noreply.github.com> Co-authored-by: Qianyue He <46109954+Enigmatisms@users.noreply.github.com> Co-authored-by: Lei Ding <69283446+Dmovic@users.noreply.github.com> Co-authored-by: ggggxm <66855582+ggggxm@users.noreply.github.com> Co-authored-by: xkkkkkk23 <xiekeke@baidu.com> Co-authored-by: Zx <zhangxiao35@baidu.com> Co-authored-by: huangjiyi <43315610+huangjiyi@users.noreply.github.com> Co-authored-by: ooo oo <106524776+ooooo-create@users.noreply.github.com>
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PR Category
Operator Mechanism
PR Types
Bug fixes
Description
修复了大 Tensor 情况下的。argsort 算子出错。argsort 算子出错原因:
cub::DeviceSegmentedRadixSort
目前不支持超过 INT_MAX 个元素的sort,所以对于大tensor,需要一个kernel call拆分机制,将一次 sort 拆分为多次。比如下面这个例子:由于 Tensor numel 为 2281701380 大于 INT_MAX,直接用
DeviceSegmentedRadixSort::SortPairs
计算 temp buffer 大小将会出现溢出。目前的解决方案:每次参与 sort 的元素不超过 2^30 个(不选择 2^31 - 1 是为了避免过大的 temp buffer,显存压力大),按照 sorting 维度计算 batch,拆分为多个 cub kernel。比如上述例子将会被拆分为三次计算:关于
cub::DeviceSegmentedRadixSort
的 API 支持范围,见:经过性能测试,此 kernel 目前平均运行时间约为 torch 的 1.25倍,部分较好的 shape 下(比如[5, 456340276] axis = -1)可达到将近50%的计算时间。
Pcard-89620