[Precision Depth Alignment] paddle.tanh reverse gradient calculation and Torch accuracy alignment. #75454
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zhengshengning
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Sep 23, 2025
| if constexpr (std::is_same<T, phi::float16>::value) { | ||
| __half out_half = __float2half_rn(static_cast<float>(out)); | ||
| __half tmp_half = __hmul(out_half, out_half); | ||
| return dout * (one - static_cast<T>(__half2float(tmp_half))); |
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进了这个if， T应该就是float16了，为什么还要cast to float然后static cast回来，接着做减法？
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因为没找到float16可以直接转_half的，所以先转成float
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* CallScalarFunction uses the dtype of 'self' as the type of 'other' when opotype is 'div'(#75237) * LinspaceKernel uses the dtype of 'self' as the type of 'step' when tensor is floating (#75238) * align LinspaceKernel * update meta * update gpu kernel * fix LinspaceKernelInner * improve kernel * fix CudaSigmoidGradFunctor and CudaSiluGradFunctor (#75341) * Softplus accuracy and torch alignment 1 (#75363) * [Precision Depth Alignment] paddle.tan reverse calculation: dx = dout *(1 + tan(x)^2) (#75335) * Tan reverse calculation: dx = dout *(1 + tan(x)^2) * [Precision Depth Alignment] Add support for CUDNN to paddle.nn.functional.grid_sample to align with torch accuracy. (#75355) * accuracy_stable_grid_sample * fix * correlation supports big tensor (#75383) * fix * fix test * fix * paddle.tanh Grad and torch alignment (float16) (#75454) * [Precision Depth Alignment] paddle.sin and paddle.cos aligns with torch precision. (#75503) * accuracy_stable_sin * accuracy_stable_cos * [深度对齐]Divide (#75379) * fix * fix * fix * fix * fix * [Precision Depth Alignment] fix precision for float16 of paddle.tan backward (#75525) * fix precision for float16 of paddle.tan backward * fix else branch of CudaTanGradFunctor * [Precision Depth Alignment] fix precision for paddle.expm1 (#75549) * accuracy_stable_expm1 * fix * Bigtensor排查修复[Paddle/paddle/phi/kernels/funcs] (#75523) * fix * fix * [Precision Depth Alignment] fix beta and threshold of paddle.nn.functional.softplus to double (#75426) * fix beta and threshold of Softplus to double * fix test_softplus_activation_fuse_pass v1 * fix test_activation_zero * fix flaot of SoftplusDoubleGradKernel to double * add op_patches for softplus * add yaml for ops/yaml/legacy * fix infershape/operator for FLOAT64 * fix * add SoftPlusOpTranscriber * fix * fix * fix1 * fix2 * fix coverage * fix coverage2 * fix (#75605) * [深度对齐] dot (#75717) * fix * fix * fix dcu * [Precision Depth Alignment] paddle.log aligns with torch precision (#75799) * accuracy_stable_log * accuracy_stable_log * fix * fix * fix * fix * fix5 * [Precision Depth Alignment] fix eps of paddle.logit from float to double (#75816) * accuracy_stable_logit * add LogitOpTranscriber * fix coverage * fix 0yaml * [Precision Depth Alignment] paddle.log_sigmoid (#75898) * accuracy_stable_log_sigmoid * fix test_activation_stride_op.py * [Precision Depth Alignment] Modify the negative_slope parameter of the paddle.nn.functional.leaky_relu API to double (#75547) * [big tensor] Paddle/paddle/phi/kernels/funcs gpuBigtensor (#75856) * fix funcs * gpu * fix * fix * 修改PADDLE_ENFORCE信息 * fix cpu error * fix dcu * fix dcu * fix * [Fix] log sigmoid complex (#75953) * feature: Add specialized LogSigmoidFunctor and CudaLogSigmoidFunctor for complex numbers This commit introduces specialized implementations of LogSigmoidFunctor and CudaLogSigmoidFunctor to handle complex number inputs. The new implementations utilize direct formulas for improved accuracy and stability in calculations involving complex types. * refactor: Optimize LogSigmoidFunctor and CudaLogSigmoidFunctor for complex types by caching exp(-x) to reduce redundant computations. This change enhances performance while maintaining accuracy in calculations. * refactor: modified the formula in LogSigmoidFunctor to make it numerical stable --------- Co-authored-by: Zhan Rongrui <46243324+zrr1999@users.noreply.github.com> Co-authored-by: 正在学习 <62892980+cszdrg@users.noreply.github.com> Co-authored-by: Bvicii <98971614+scyyh11@users.noreply.github.com>
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PR Category
Operator Mechanism
PR Types
Bug fixes
Description
主要修改点如下：
测试结果：
pcard-67164