// 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 #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_lite.h" #include "paddle/fluid/lite/core/op_registry.h" #include "paddle/fluid/lite/core/type_system.h" #include "paddle/fluid/lite/operators/relu_op.h" namespace paddle { namespace lite { namespace kernels { namespace x86 { template void scale_compute(const T* x, T* out, int size, float scale, float bias, bool bias_before) { if (bias_before) bias *= scale; for (int i = 0; i < size; i++) { out[i] = x[i] * scale + bias; } } template class ScaleCompute : public KernelLite { public: using param_t = operators::ScaleParam; void Run() override { auto& param = *param_.get_mutable(); scale_compute(param.x->data(), param.output->mutable_data(), param.x->dims().production(), param.scale, param.bias, param.bias_after_scale); } virtual ~ScaleCompute() = default; }; } // namespace x86 } // namespace kernels } // namespace lite } // namespace paddle REGISTER_LITE_KERNEL(scale, kX86, kFloat, kNCHW, paddle::lite::kernels::x86::ScaleCompute, def) .BindInput("X", {LiteType::GetTensorTy(TARGET(kX86))}) .BindOutput("Out", {LiteType::GetTensorTy(TARGET(kX86))}) .Finalize();