// 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/pten/kernels/elementwise_grad_kernel.h" #include "paddle/pten/backends/gpu/gpu_context.h" #include "paddle/pten/core/kernel_registry.h" #include "paddle/pten/kernels/copy_kernel.h" #include "paddle/pten/kernels/funcs/elementwise_functor.h" #include "paddle/pten/kernels/gpu/elementwise.h" #include "paddle/pten/kernels/impl/elementwise_grad_kernel_impl.h" namespace pten { template void AddGradFunc(const GPUContext& 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())) { elementwise_add_grad(dev_ctx, x, y, out, dout, dx, dy); } else { default_elementwise_add_grad(dev_ctx, x, y, out, dout, dx, dy, axis); } } template void AddGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& y, const DenseTensor& dout, int axis, DenseTensor* dx, DenseTensor* dy) { pten::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) { pten::AddDoubleGradImpl( dev_ctx, y, ddx, ddy, dout, axis, ddout, ElementwiseCompute, T>, ElementwiseCompute, T>); } 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) { pten::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; if (dx != nullptr && dy != nullptr && (dx->dims() == dy->dims())) { elementwise_sub_grad(dev_ctx, x, y, *out, dout, dx, dy); } else { default_elementwise_sub_grad(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) { pten::SubtractDoubleGradImpl( dev_ctx, y, ddx, ddy, dout, axis, ddout, ElementwiseCompute, T>); } } // namespace pten PT_REGISTER_KERNEL(add_grad, GPU, ALL_LAYOUT, pten::AddGradKernel, float, double, int, int64_t, paddle::platform::float16, paddle::platform::complex, paddle::platform::complex) {} PT_REGISTER_KERNEL(add_double_grad, GPU, ALL_LAYOUT, pten::AddDoubleGradKernel, float, double, int, int64_t, paddle::platform::float16, paddle::platform::complex, paddle::platform::complex) {} PT_REGISTER_KERNEL(add_triple_grad, GPU, ALL_LAYOUT, pten::AddTripleGradKernel, float, double, int, int64_t, paddle::platform::float16, paddle::platform::complex, paddle::platform::complex) {} PT_REGISTER_KERNEL(subtract_grad, GPU, ALL_LAYOUT, pten::SubtractGradKernel, float, double, int, int64_t, paddle::platform::float16, paddle::platform::complex, paddle::platform::complex) {} PT_REGISTER_KERNEL(subtract_double_grad, GPU, ALL_LAYOUT, pten::SubtractDoubleGradKernel, float, double, int, int64_t, paddle::platform::float16, paddle::platform::complex, paddle::platform::complex) {}