// Copyright (c) 2020 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 "lite/kernels/arm/mean_grad_compute.h" #include "lite/backends/arm/math/reduce_mean.h" namespace paddle { namespace lite { namespace kernels { namespace arm { void MeanGradCompute::Run() { auto& param = this->Param(); const auto* input = param.X; const auto* out_grad = param.Out_grad; auto* input_grad = param.X_grad; auto out_grad_data = out_grad->data(); auto input_data = input->data(); auto input_grad_data = input_grad->mutable_data(); int input_grad_size = input_grad->dims().production(); lite::arm::math::mean_grad(out_grad_data, input_grad_data, input_grad_size); } } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL(mean_grad, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::MeanGradCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM))}) .BindInput("Out@GRAD", {LiteType::GetTensorTy(TARGET(kARM))}) .BindOutput("X@GRAD", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize();