// 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. #include "paddle/phi/kernels/elementwise_grad_kernel.h" #include "paddle/phi/backends/cpu/cpu_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/copy_kernel.h" #include "paddle/phi/kernels/cpu/elementwise_grad.h" #include "paddle/phi/kernels/funcs/elementwise_functor.h" #include "paddle/phi/kernels/impl/elementwise_grad_kernel_impl.h" namespace phi { template void AddGradFunc(const CPUContext& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& out, const DenseTensor& dout, DenseTensor* dx, DenseTensor* dy, int axis = -1) { if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) { ElementwiseAddGrad(dev_ctx, x, y, out, dout, dx, dy); } else { ElemwiseExplicitGradCompute, IdentityGrad>( dev_ctx, x, y, out, dout, axis, dx, dy, IdentityGrad(), IdentityGrad()); } } template void AddGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { phi::AddGradImpl(dev_ctx, x, y, dout, axis, dx, dy, AddGradFunc); } template void AddDoubleGradKernel(const Context& dev_ctx, const DenseTensor& y, paddle::optional ddx, paddle::optional ddy, const DenseTensor& dout, int axis, DenseTensor* ddout) { phi::AddDoubleGradImpl(dev_ctx, y, ddx, ddy, dout, axis, ddout); } template void AddTripleGradKernel(const Context& dev_ctx, const DenseTensor& ddx, const DenseTensor& ddy, const DenseTensor& d_ddout, int axis, DenseTensor* d_ddx, DenseTensor* d_ddy) { phi::AddGradImpl( dev_ctx, ddx, ddy, d_ddout, axis, d_ddx, d_ddy, AddGradFunc); } template void SubtractGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { // skip out auto* out = &dout; ElementwiseSubGrad(dev_ctx, x, y, *out, dout, dx, dy, axis); } template void SubtractDoubleGradKernel(const Context& dev_ctx, const DenseTensor& y, paddle::optional ddx, paddle::optional ddy, const DenseTensor& dout, int axis, DenseTensor* ddout) { phi::SubtractDoubleGradImpl(dev_ctx, y, ddx, ddy, dout, axis, ddout); } template void DivideGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& out, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { funcs::ElementwiseGradPreProcess(dout, dx); phi::funcs::ElemwiseGradCompute, DivGradDY>( dev_ctx, x, y, out, dout, axis, dx, dy, DivGradDX(), DivGradDY()); } template void MultiplyGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { funcs::ElementwiseGradPreProcess(dout, dx); auto* out = &dout; // out is not necessary phi::funcs::ElemwiseGradCompute, MulGradDY>( dev_ctx, x, y, *out, dout, axis, dx, dy, MulGradDX(), MulGradDY()); } template void MaximumGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { funcs::ElementwiseGradPreProcess(dout, dx); phi::funcs::ElemwiseGradCompute, MaxGradDy>( dev_ctx, x, y, dout, dout, axis, dx, dy, MaxGradDx(), MaxGradDy()); } template void MinimumGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { funcs::ElementwiseGradPreProcess(dout, dx); phi::funcs::ElemwiseGradCompute, MinGradDy>( dev_ctx, x, y, dout, dout, axis, dx, dy, MinGradDx(), MinGradDy()); } } // namespace phi PD_REGISTER_KERNEL(add_grad, CPU, ALL_LAYOUT, phi::AddGradKernel, float, double, int16_t, int, int64_t, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(add_double_grad, CPU, ALL_LAYOUT, phi::AddDoubleGradKernel, float, double, int16_t, int, int64_t, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(add_triple_grad, CPU, ALL_LAYOUT, phi::AddTripleGradKernel, float, double, int16_t, int, int64_t, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(subtract_grad, CPU, ALL_LAYOUT, phi::SubtractGradKernel, float, double, int16_t, int, int64_t, phi::dtype::bfloat16, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(subtract_double_grad, CPU, ALL_LAYOUT, phi::SubtractDoubleGradKernel, float, double, int16_t, int, int64_t, phi::dtype::bfloat16, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(divide_grad, CPU, ALL_LAYOUT, phi::DivideGradKernel, float, double, int, int64_t, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(divide_double_grad, CPU, ALL_LAYOUT, phi::DivideDoubleGradKernel, float, double, int, int64_t, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(multiply_grad, CPU, ALL_LAYOUT, phi::MultiplyGradKernel, float, double, int, int64_t, bool, phi::dtype::bfloat16, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(multiply_double_grad, CPU, ALL_LAYOUT, phi::MultiplyDoubleGradKernel, float, double, int, int64_t, bool, phi::dtype::bfloat16, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(multiply_triple_grad, CPU, ALL_LAYOUT, phi::MultiplyTripleGradKernel, float, double, int, int64_t, bool, phi::dtype::bfloat16, phi::dtype::complex, phi::dtype::complex) {} PD_REGISTER_KERNEL(fmax_grad, CPU, ALL_LAYOUT, phi::ElementwiseFMaxGradKernel, float, double, int, int64_t) {} PD_REGISTER_KERNEL(fmin_grad, CPU, ALL_LAYOUT, phi::ElementwiseFMinGradKernel, float, double, int, int64_t) {} PD_REGISTER_KERNEL(maximum_grad, CPU, ALL_LAYOUT, phi::MaximumGradKernel, float, double, int, int64_t, phi::dtype::bfloat16) {} PD_REGISTER_KERNEL(minimum_grad, CPU, ALL_LAYOUT, phi::MinimumGradKernel, float, double, int, int64_t, phi::dtype::bfloat16) {}