// 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. /* * This file implements a light-weight API which can run on mobile. We limit the * dependencies and the runtime computation complexity. */ #pragma once #include #include #include #include #include #include "lite/api/paddle_api.h" #include "lite/core/context.h" #include "lite/core/program.h" #include "lite/core/tensor.h" #include "lite/core/types.h" #include "lite/model_parser/model_parser.h" namespace paddle { namespace lite { /* * The light weight predictor, mainly for mobile. It loads an optimized model, * and will not depend on the MIR or perform latter optimization. */ class LITE_API LightPredictor { public: LightPredictor( const std::string& model_dir, const std::string& model_buffer = "", const std::string& param_buffer = "", bool model_from_memory = false, lite_api::LiteModelType model_type = lite_api::LiteModelType::kProtobuf) { scope_ = std::make_shared(); Build(model_dir, model_buffer, param_buffer, model_type, model_from_memory); } void Run() { program_->Run(); } // Get offset-th col of feed inputs. Tensor* GetInput(size_t offset); // get input by name. Tensor* GetInputByName(const std::string& name); // Get offset-th col of fetch outputs. const Tensor* GetOutput(size_t offset); const lite::Tensor* GetTensor(const std::string& name) const { auto* var = program_->exec_scope()->FindVar(name); return &var->Get(); } // get inputnames and get outputnames. std::vector GetInputNames(); std::vector GetOutputNames(); void PrepareFeedFetch(); private: void Build( const std::string& model_dir, const std::string& model_buffer, const std::string& param_buffer, lite_api::LiteModelType model_type = lite_api::LiteModelType::kProtobuf, bool model_from_memory = false); void BuildRuntimeProgram(const cpp::ProgramDesc& prog); private: std::shared_ptr scope_; std::unique_ptr program_; cpp::ProgramDesc cpp_program_desc_; std::map input_names_; std::map idx2feeds_; std::map output_names_; }; } // namespace lite } // namespace paddle