// 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 "lite/kernels/xpu/activation_compute.h" #include "lite/backends/xpu/xpu_header_sitter.h" #include "lite/core/op_registry.h" namespace paddle { namespace lite { namespace kernels { namespace xpu { void ReluCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); int r = xdnn::activation_forward( ctx.GetRawContext(), /* context */ xdnn::Activation_t::RELU, /* type */ param.X->numel(), /* len */ param.X->data(), /* x */ param.Out->mutable_data(TARGET(kXPU)) /* y */); CHECK_EQ(r, 0); } void TanhCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); int r = xdnn::activation_forward( ctx.GetRawContext(), /* context */ xdnn::Activation_t::TANH, /* type */ param.X->numel(), /* len */ param.X->data(), /* x */ param.Out->mutable_data(TARGET(kXPU)) /* y */); CHECK_EQ(r, 0); } void SigmoidCompute::Run() { auto& param = this->Param(); auto& ctx = this->ctx_->As(); int r = xdnn::activation_forward( ctx.GetRawContext(), /* context */ xdnn::Activation_t::SIGMOID, /* type */ param.X->numel(), /* len */ param.X->data(), /* x */ param.Out->mutable_data(TARGET(kXPU)) /* y */); CHECK_EQ(r, 0); } } // namespace xpu } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL( relu, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::ReluCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize(); REGISTER_LITE_KERNEL( tanh, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::TanhCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize(); REGISTER_LITE_KERNEL(sigmoid, kXPU, kFloat, kNCHW, paddle::lite::kernels::xpu::SigmoidCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kXPU))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kXPU))}) .Finalize();