// 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/reduce_mean_grad_kernel.h" #include "paddle/phi/backends/gpu/gpu_context.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/reduce_function.h" #include "paddle/phi/kernels/gpu/reduce_grad.h" namespace phi { template void ReduceMeanGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& out_grad, const IntArray& dims, bool keep_dim, bool reduce_all, DenseTensor* x_grad) { int dim_size = x.dims().size(); std::vector reduce_dims = funcs::details::GetReduceDim(dims.GetData(), dim_size, reduce_all); int reduce_num = 1; for (auto i : reduce_dims) { reduce_num *= (x.dims())[i]; } using MPType = typename kps::details::MPTypeTrait::Type; ReduceGradKernel>( dev_ctx, x, out_grad, dims.GetData(), keep_dim, reduce_all, x_grad, kps::DivideFunctor(reduce_num)); } } // namespace phi PD_REGISTER_KERNEL(mean_grad, GPU, ALL_LAYOUT, phi::ReduceMeanGradKernel, bool, float, double, phi::dtype::float16) {}