// 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/framework/eigen.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/lite/core/kernel.h" #include "paddle/fluid/lite/core/op_registry.h" #include "paddle/fluid/operators/jit/kernels.h" namespace paddle { namespace lite { namespace kernels { namespace x86 { template class SGDCompute : public KernelLite { public: using param_t = operators::ActivationParam; void Run() override { auto &context = context_->As(); auto &sgd_param = *param_.get_mutable(); CHECK(context.x86_device_context); // param.Out->template mutable_data(); const auto *param = &sgd_param.Param->raw_tensor(); const auto *grad = &sgd_param.Grad->raw_tensor(); const auto *learning_rate = &sgd_param.LearningRate->raw_tensor(); auto *param_out = &sgd_param.ParamOut->raw_tensor(); auto sz = param_out->numel(); PADDLE_ENFORCE_EQ(param->numel(), sz); PADDLE_ENFORCE_EQ(grad->numel(), sz); paddle::operators::jit::sgd_attr_t attr(1, sz, 1, sz, 1); const T *lr = learning_rate->data(); const T *param_data = param->data(); const T *grad_data = grad->data(); int64_t rows_idx = 0; T *out_data = param_out->mutable_data(context.x86_device_context->GetPlace()); auto sgd = paddle::operators::jit::KernelFuncs, platform::CPUPlace>::Cache() .At(attr); sgd(lr, param_data, grad_data, &rows_idx, out_data, &attr); } virtual ~SGDCompute() = default; }; } // namespace x86 } // namespace kernels } // namespace lite } // namespace paddle // float REGISTER_LITE_KERNEL(sgd, kX86, kFloat, kNCHW, paddle::lite::kernels::x86::SGDCompute, def) .BindInput("Param", {LiteType::GetTensorTy(TARGET(kX86))}) .BindInput("LearningRate", {LiteType::GetTensorTy(TARGET(kX86))}) .BindInput("Grad", {LiteType::GetTensorTy(TARGET(kX86))}) .BindOutput("ParamOut", {LiteType::GetTensorTy(TARGET(kX86))}) .Finalize();