activation_grad_kernel.cu 20.7 KB
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/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

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#include "paddle/phi/kernels/activation_grad_kernel.h"

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#include "paddle/fluid/platform/device/gpu/gpu_device_function.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/common/bfloat16.h"
#include "paddle/phi/common/float16.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/elementwise_base.h"
#include "paddle/phi/kernels/impl/activation_grad_impl.h"

namespace phi {

template <typename T, typename Context, typename Functor>
void ActivationGradGPUImpl(const Context& dev_ctx,
                           const DenseTensor* x,
                           const DenseTensor* out,
                           const DenseTensor* d_out,
                           DenseTensor* d_x,
                           const Functor& functor) {
  if (static_cast<int>(Functor::FwdDeps()) &
      static_cast<int>(funcs::ActBwdOpFwdDeps::kDepOut)) {
    PADDLE_ENFORCE_NOT_NULL(
        out, errors::NotFound("The input DenseTensor Out can not be nullptr"));
  }
  PADDLE_ENFORCE_NOT_NULL(
      d_out, errors::NotFound("The input DenseTensor dOut can not be nullptr"));
  PADDLE_ENFORCE_NOT_NULL(
      d_x, errors::NotFound("The output DenseTensor dX can not be nullptr"));
  if (!out) {
    out = d_out;  // fake out
  }
  if (static_cast<int>(Functor::FwdDeps()) &
      static_cast<int>(funcs::ActBwdOpFwdDeps::kDepX)) {
    PADDLE_ENFORCE_NOT_NULL(
        x, errors::NotFound("The input DenseTensor X can not be nullptr"));
  } else {
    VLOG(10) << "Inplace activation of Op Functor: " << typeid(Functor).name();
    x = d_x;
  }

  dev_ctx.template Alloc<T>(d_x);

  std::vector<const DenseTensor*> ins = {d_out};
  std::vector<DenseTensor*> outs = {d_x};

  if (static_cast<int>(Functor::FwdDeps()) ==
      static_cast<int>(funcs::ActBwdOpFwdDeps::kDepOut)) {
    // Only need forward output Out
    ins.push_back(out);
    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
  } else if (static_cast<int>(Functor::FwdDeps()) ==
             static_cast<int>(funcs::ActBwdOpFwdDeps::kDepX)) {
    // Only need forward input X
    ins.push_back(x);
    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
  } else {
    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
  }
}

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#define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(name, functor_class) \
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  template <typename T, typename Context>                           \
  void name##GradKernel(const Context& dev_ctx,                     \
                        const DenseTensor& x,                       \
                        const DenseTensor& dout,                    \
                        DenseTensor* dx) {                          \
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    funcs::functor_class<T> functor;                                \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>(     \
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        dev_ctx, &x, nullptr, &dout, dx, functor);                  \
  }

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#define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(         \
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    name, functor_class, attr)                                  \
  template <typename T, typename Context>                       \
  void name##GradKernel(const Context& dev_ctx,                 \
                        const DenseTensor& x,                   \
                        const DenseTensor& dout,                \
                        float attr,                             \
                        DenseTensor* dx) {                      \
    funcs::functor_class<T> functor;                            \
    auto attrs = functor.GetAttrs();                            \
    *(attrs[0].second) = attr;                                  \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>( \
        dev_ctx, &x, nullptr, &dout, dx, functor);              \
  }

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#define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(         \
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    name, functor_class, attr1, attr2)                          \
  template <typename T, typename Context>                       \
  void name##GradKernel(const Context& dev_ctx,                 \
                        const DenseTensor& x,                   \
                        const DenseTensor& dout,                \
                        float attr1,                            \
                        float attr2,                            \
                        DenseTensor* dx) {                      \
    funcs::functor_class<T> functor;                            \
    auto attrs = functor.GetAttrs();                            \
    *(attrs[0].second) = attr1;                                 \
    *(attrs[1].second) = attr2;                                 \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>( \
        dev_ctx, &x, nullptr, &dout, dx, functor);              \
  }

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#define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(name, functor_class) \
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  template <typename T, typename Context>                             \
  void name##GradKernel(const Context& dev_ctx,                       \
                        const DenseTensor& out,                       \
                        const DenseTensor& dout,                      \
                        DenseTensor* dx) {                            \
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    funcs::functor_class<T> functor;                                  \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>(       \
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        dev_ctx, nullptr, &out, &dout, dx, functor);                  \
  }

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#define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT(       \
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    name, functor_class, attr)                                  \
  template <typename T, typename Context>                       \
  void name##GradKernel(const Context& dev_ctx,                 \
                        const DenseTensor& out,                 \
                        const DenseTensor& dout,                \
                        float attr,                             \
                        DenseTensor* dx) {                      \
    funcs::functor_class<T> functor;                            \
    auto attrs = functor.GetAttrs();                            \
    *(attrs[0].second) = attr;                                  \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>( \
        dev_ctx, nullptr, &out, &dout, dx, functor);            \
  }

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#define DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT(       \
    name, functor_class, attr1, attr2)                          \
  template <typename T, typename Context>                       \
  void name##GradKernel(const Context& dev_ctx,                 \
                        const DenseTensor& out,                 \
                        const DenseTensor& dout,                \
                        float attr1,                            \
                        float attr2,                            \
                        DenseTensor* dx) {                      \
    funcs::functor_class<T> functor;                            \
    auto attrs = functor.GetAttrs();                            \
    *(attrs[0].second) = attr1;                                 \
    *(attrs[1].second) = attr2;                                 \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>( \
        dev_ctx, nullptr, &out, &dout, dx, functor);            \
  }

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#define DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(name, functor_class)      \
  template <typename T, typename Context>                                 \
  void name##GradKernel(                                                  \
      const Context& dev_ctx, const DenseTensor& dout, DenseTensor* dx) { \
    funcs::functor_class<T> functor;                                      \
    ActivationGradGPUImpl<T, Context, funcs::functor_class<T>>(           \
        dev_ctx, nullptr, nullptr, &dout, dx, functor);                   \
  }

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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Relu, CudaReluGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Tanh, CudaTanhGradFunctor);
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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sigmoid, CudaSigmoidGradFunctor);

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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Round, CudaZeroGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Floor, CudaZeroGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_NODEP(Ceil, CudaZeroGradFunctor);

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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Cos, CudaCosGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Tan, CudaTanGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Acos, CudaAcosGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Sin, CudaSinGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Asin, CudaAsinGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Atan, CudaAtanGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Sinh, CudaSinhGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Cosh, CudaCoshGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Asinh, CudaAsinhGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Acosh, CudaAcoshGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Atanh, CudaAtanhGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(TanhShrink, CudaTanhShrinkGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Silu, CudaSiluGradFunctor);
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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Square, CudaSquareGradFunctor);

DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Exp, CudaExpGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Expm1, CudaExpm1GradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Reciprocal, CudaReciprocalGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Sqrt, CudaSqrtGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPOUT(Rsqrt, CudaRsqrtGradFunctor);
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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(LogSigmoid, CudaLogSigmoidGradFunctor);
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DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log, CudaLogGradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log2, CudaLog2GradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log10, CudaLog10GradFunctor);
DEFINE_GPU_ACTIVATION_GRAD_KERNEL_DEPX(Log1p, CudaLog1pGradFunctor);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(LeakyRelu,
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                                               CudaLeakyReluGradFunctor,
                                               alpha);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(ThresholdedRelu,
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                                               CudaThresholdedReluGradFunctor,
                                               threshold);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(SoftShrink,
                                               CudaSoftShrinkGradFunctor,
                                               lambda);
DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(HardShrink,
                                               CudaHardShrinkGradFunctor,
                                               threshold);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Swish,
                                               CudaSwishGradFunctor,
                                               beta);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Mish,
                                               CudaMishGradFunctor,
                                               threshold);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPX(Celu,
                                               CudaCELUGradFunctor,
                                               alpha);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_ONE_ATTRS_DEPOUT(Relu6,
                                                 CudaRelu6GradFunctor,
                                                 threshold);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(BRelu,
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                                               CudaBReluGradFunctor,
                                               t_min,
                                               t_max);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(STanh,
                                               CudaSTanhGradFunctor,
                                               scale_a,
                                               scale_b);

DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPX(Softplus,
                                               CudaSoftplusGradFunctor,
                                               beta,
                                               threshold);
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DEFINE_GPU_ACT_GRAD_KERNEL_WITH_TWO_ATTRS_DEPOUT(HardSigmoid,
                                                 CudaHardSigmoidGradFunctor,
                                                 slope,
                                                 offset);

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template <typename T, typename Context>
void EluGradKernel(const Context& dev_ctx,
                   const DenseTensor& x,
                   const DenseTensor& out,
                   const DenseTensor& dout,
                   float alpha,
                   DenseTensor* dx) {
  dev_ctx.template Alloc<T>(dx);
  std::vector<const DenseTensor*> ins = {&dout, &out};
  std::vector<DenseTensor*> outs = {dx};
  if (alpha > 0) {
    funcs::CudaELUGradFunctor<T> functor;
    functor.alpha = alpha;
    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
  } else {
    funcs::CudaELUGradNegativeAlphaFunctor<T> functor;
    functor.alpha = alpha;
    ins.push_back(&x);
    funcs::ElementwiseKernel<T>(dev_ctx, ins, &outs, functor);
  }
}

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template <typename T, typename Context>
void HardSwishGradKernel(const Context& dev_ctx,
                         const DenseTensor& x,
                         const DenseTensor& dout,
                         float threshold,
                         float scale,
                         float offset,
                         DenseTensor* dx) {
  funcs::CudaHardSwishGradFunctor<T> functor;
  auto attrs = functor.GetAttrs();
  *(attrs[0].second) = threshold;
  *(attrs[1].second) = scale;
  *(attrs[2].second) = offset;
  ActivationGradGPUImpl<T, Context, funcs::CudaHardSwishGradFunctor<T>>(
      dev_ctx, &x, nullptr, &dout, dx, functor);
}

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}  // namespace phi
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#ifdef PADDLE_WITH_HIP
PD_REGISTER_KERNEL(relu_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluGradKernel,
                   float,
                   double,
                   phi::dtype::float16) {}
PD_REGISTER_KERNEL(relu_double_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluDoubleGradKernel,
                   float,
                   double,
                   phi::dtype::float16) {}
#else
PD_REGISTER_KERNEL(relu_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluGradKernel,
                   float,
                   double,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
PD_REGISTER_KERNEL(relu_double_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ReluDoubleGradKernel,
                   float,
                   double,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
#endif
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#define PD_REGISTER_ACTIVATION_GRAD_KERNEL(name, func) \
  PD_REGISTER_KERNEL(name,                             \
                     GPU,                              \
                     ALL_LAYOUT,                       \
                     phi::func,                        \
                     float,                            \
                     double,                           \
                     phi::dtype::float16,              \
                     phi::dtype::bfloat16) {}

PD_REGISTER_ACTIVATION_GRAD_KERNEL(sin_grad, SinGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(cos_grad, CosGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(tan_grad, TanGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(acos_grad, AcosGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(asin_grad, AsinGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(atan_grad, AtanGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(sinh_grad, SinhGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(cosh_grad, CoshGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(asinh_grad, AsinhGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(acosh_grad, AcoshGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(atanh_grad, AtanhGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_grad, TanhGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_double_grad, TanhDoubleGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_triple_grad, TanhTripleGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(brelu_grad, BReluGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(leaky_relu_grad, LeakyReluGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(leaky_relu_double_grad,
                                   LeakyReluDoubleGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(thresholded_relu_grad,
                                   ThresholdedReluGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(relu6_grad, Relu6GradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(mish_grad, MishGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(stanh_grad, STanhGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(reciprocal_grad, ReciprocalGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(softplus_grad, SoftplusGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(sqrt_grad, SqrtGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(sqrt_double_grad, SqrtDoubleGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(rsqrt_grad, RsqrtGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(rsqrt_double_grad, RsqrtDoubleGradKernel)
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PD_REGISTER_KERNEL(exp_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::ExpGradKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16) {}

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PD_REGISTER_ACTIVATION_GRAD_KERNEL(soft_shrink_grad, SoftShrinkGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_shrink_grad, HardShrinkGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(tanh_shrink_grad, TanhShrinkGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(silu_grad, SiluGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(elu_grad, EluGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(elu_double_grad, EluDoubleGradKernel)
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PD_REGISTER_KERNEL(expm1_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::Expm1GradKernel,
                   float,
                   double,
                   phi::dtype::float16) {}

PD_REGISTER_KERNEL(logit_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::LogitGradKernel,
                   float,
                   double,
                   phi::dtype::float16) {}

PD_REGISTER_KERNEL(square_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::SquareGradKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
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PD_REGISTER_KERNEL(square_double_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::SquareDoubleGradKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16,
                   phi::dtype::bfloat16) {}
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_grad, SigmoidGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_double_grad, SigmoidDoubleGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(sigmoid_triple_grad, SigmoidTripleGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_sigmoid_grad, HardSigmoidGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(logsigmoid_grad, LogSigmoidGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(log_grad, LogGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(log2_grad, Log2GradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(log10_grad, Log10GradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(log1p_grad, Log1pGradKernel)
PD_REGISTER_KERNEL(log_double_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::LogDoubleGradKernel,
                   float,
                   double,
                   phi::dtype::float16) {}
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(hard_swish_grad, HardSwishGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(swish_grad, SwishGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(round_grad, RoundGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(floor_grad, FloorGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(ceil_grad, CeilGradKernel)
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PD_REGISTER_ACTIVATION_GRAD_KERNEL(celu_grad, CeluGradKernel)
PD_REGISTER_ACTIVATION_GRAD_KERNEL(celu_double_grad, CeluDoubleGradKernel)
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PD_REGISTER_KERNEL(pow_grad,
                   GPU,
                   ALL_LAYOUT,
                   phi::PowGradKernel,
                   float,
                   double,
                   int,
                   int64_t,
                   phi::dtype::float16) {}