/* Copyright (c) 2019 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/fluid/operators/elementwise/elementwise_mod_op.h" namespace ops = paddle::operators; namespace plat = paddle::platform; namespace paddle { namespace operators { template struct CudaModFunctor { inline HOSTDEVICE T operator()(const T* args) const { T res = args[0] % args[1]; // Accoding to #PR26732: in dividen % divsor // remainder shall have the same sign as divsor. if ((res != 0) && ((args[1] ^ res) < 0)) res += args[1]; return res; } }; template struct CudaModFunctor< T, typename std::enable_if_t::value>> { inline HOSTDEVICE T operator()(const T* args) const { T res = fmod(args[0], args[1]); // Accoding to #PR26732: in dividen % divsor // remainder shall have the same sign as divsor. if ((res != 0) && ((res < 0) != (args[1] < 0))) res += args[1]; return res; } }; template class ElementwiseModKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { std::vector ins; std::vector outs; const auto& cuda_ctx = ctx.template device_context(); int axis = PackTensorsIntoVector(ctx, &ins, &outs); LaunchElementwiseCudaKernel( cuda_ctx, ins, &outs, axis, CudaModFunctor()); } }; } // namespace operators } // namespace paddle REGISTER_OP_CUDA_KERNEL( elementwise_mod, ops::ElementwiseModKernel, ops::ElementwiseModKernel, ops::ElementwiseModKernel, ops::ElementwiseModKernel);