// 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/activation_grad_compute.h" #include "lite/backends/arm/math/funcs.h" namespace paddle { namespace lite { namespace kernels { namespace arm { void SquareGradCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->template As(); auto out_grad_dims = param.Out_grad->dims(); auto out_grad_data = param.Out_grad->data(); auto x_data = param.X->data(); auto x_grad_data = param.X_grad->mutable_data(); lite::arm::math::act_square_grad(x_data, out_grad_data, x_grad_data, out_grad_dims.production(), ctx.threads()); } } // namespace arm } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL(square_grad, kARM, kFloat, kNCHW, paddle::lite::kernels::arm::SquareGradCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kARM))}) .BindInput("Out@GRAD", {LiteType::GetTensorTy(TARGET(kARM))}) .BindOutput("X@GRAD", {LiteType::GetTensorTy(TARGET(kARM))}) .Finalize();