// 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. #pragma once namespace phi { namespace funcs { //////// Frobenius Norm Functor /////// struct FrobeniusNormFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = ((x->square()).sum(dim)).sqrt(); } }; struct FrobeniusNormGradFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy, const Dim& dim, int size) { dx->device(place) = y->broadcast(dim); dx->device(place) = *dx + dx->constant(1e-12f); dx->device(place) = (*x / *dx) * (dy->broadcast(dim)); } }; //////// Max Functor /////// struct MaxFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->maximum(dim); } }; //////// Mean Functor /////// struct MeanFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->mean(dim); } }; //////// Prod Functor /////// struct ProdFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->prod(dim); } }; //////// Sum Functor /////// struct SumFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->sum(dim); } }; //////// Min Functor /////// struct MinFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->minimum(dim); } }; //////// All Functor /////// struct AllFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->all(dim); } }; //////// Any Functor /////// struct AnyFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, const Dim& dim) { y->device(place) = x->any(dim); } }; struct MeanGradFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy, const Dim& dim, int size) { dx->device(place) = dy->broadcast(dim) / dx->constant(size); } }; struct SumGradFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy, const Dim& dim, int size) { dx->device(place) = dy->broadcast(dim); } }; struct ProdGradFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy, const Dim& dim, int size) { dx->device(place) = dy->broadcast(dim) * y->broadcast(dim) * x->inverse(); } }; struct MaxOrMinGradFunctor { template void operator()(const DeviceContext& place, X* x, Y* y, DX* dx, DY* dy, const Dim& dim, int size) { auto equals = (*x) == y->broadcast(dim); auto ones = dx->constant(1); auto zeros = dx->constant(0); // If there are multiple minimum or maximum elements, the subgradient of // each is the set [0, 1], and we pass gradient to all of them here. dx->device(place) = dy->broadcast(dim) * equals.select(ones, zeros); } }; } // namespace funcs } // namespace phi