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[PHI] Align paddle.inner with torch in matmul logic #72843
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* 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>
PR Category
Operator Mechanism
PR Types
Bug fixes
Description
对齐paddle.inner(x, y)与torch在matmul上的调用逻辑
原理
paddle动态图原来是先调用 y.transpose(),再调用 matmul,这会导致inner的执行变成2个kernel:transpose(y) + matmul(x, yT):
本PR将其改为直接调用 matmul(x, y, transpose_y=True),这样底层的分发逻辑就会只执行1个kernel(外加一个小reduce
kernel):
注意到,前一个cutlass的签名是
nn
,后一个是tn
参考torch
对齐情况
本PR可以做到与torch完全对齐(结果完全相等,nsys trace完全相同)
测试范围:x[M, C],y[N, C];其中 1 <= N, M <= 228,1 <= C <= 230(在显存能装下的范围内)
性能比原先的 transpose + matmul 版本提升一倍左右,因为省了transpose的成本
另外,静态图无需修改,因为静态图会自动把 matmul_v2(x, y.T) 变成 matmul(x, y, transpose_y: true)
Pcard-85711