// 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_sum_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 ReduceSumGradKernel(const Context& dev_ctx, const DenseTensor& x, const DenseTensor& out_grad, const IntArray& dims, bool keep_dim, bool reduce_all, DenseTensor* x_grad) { // get reduce_dim for reduce_mean_grad int dim_size = x.dims().size(); if (dims.size() == 0) { reduce_all = true; } std::vector reduce_dims = funcs::details::GetReduceDim(dims.GetData(), dim_size, reduce_all); auto update_dims = vectorize(x.dims()); for (auto i : reduce_dims) { update_dims[i] = 1; } // make new tensor DenseTensor new_out_grad(out_grad.dtype()); new_out_grad.ShareDataWith(out_grad); new_out_grad.Resize(phi::make_ddim(update_dims)); // call ReduceGrad dev_ctx.Alloc(x_grad, x.dtype()); using MPType = typename kps::details::MPTypeTrait::Type; phi::ReduceGrad>( dev_ctx, &new_out_grad, x_grad, x.dtype(), kps::IdentityFunctor()); } } // namespace phi PD_REGISTER_KERNEL(sum_grad, GPU, ALL_LAYOUT, phi::ReduceSumGradKernel, bool, float, double, phi::dtype::float16, phi::dtype::bfloat16, int, int64_t, phi::dtype::complex, phi::dtype::complex) {}