// 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/mean_all_kernel.h" #include "paddle/phi/core/kernel_registry.h" #include "paddle/phi/kernels/funcs/reduce_function.h" #include "paddle/phi/kernels/primitive/functor_primitives.h" #include "paddle/fluid/memory/memcpy.h" namespace phi { template void MeanAllKernel(const Context& dev_ctx, const DenseTensor& x, DenseTensor* out) { const T* in_data = x.data(); T* out_data = dev_ctx.template Alloc(out); auto numel = x.numel(); auto rank = x.dims().size(); auto place = dev_ctx.GetPlace(); auto stream = dev_ctx.stream(); if (rank == 0) { // scalar paddle::memory::Copy( place, out_data, place, in_data, numel * sizeof(T), stream); return; } std::vector reduce_dims; reduce_dims.reserve(rank); for (decltype(rank) i = 0; i < rank; ++i) { reduce_dims.push_back(i); } funcs::ReduceKernel>( dev_ctx, x, out, kps::IdentityFunctor(), reduce_dims, /*is_mean=*/true); } } // namespace phi PD_REGISTER_KERNEL(mean_all, GPU, ALL_LAYOUT, phi::MeanAllKernel, float, double, phi::dtype::float16, phi::dtype::complex, phi::dtype::complex) {}