// Copyright (c) 2018 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. #pragma once #include #include #include #include #include #include "paddle/fluid/inference/analysis/analysis_pass.h" #include "paddle/pten/backends/dynload/port.h" namespace paddle { namespace framework { namespace ir { class Graph; } // namespace ir } // namespace framework } // namespace paddle namespace paddle { namespace inference { namespace analysis { /* Memory optimization. * We will perform the following operation: * 1. Collect all var's lifetime. * 2. Make reuse plan: the vars can be reused if there is no overlap(on lifetime) * between * them. * The final plan is a mapping table in which the key represents the original * name of var and the value in the table represents the current name of var. * 3. Perform reuse plan: Replace all var's name in the model according to the * mapping table. */ class MemoryOptimizePass : public AnalysisPass { public: using space_table_t = std::unordered_map; using lifecycle_t = std::pair; virtual ~MemoryOptimizePass() = default; protected: void RunImpl(Argument *argument) override; private: void CollectLifeCycle( framework::ir::Graph *graph, std::unordered_map *lifecycles, int sort_kind) const; void CollectVarMemorySize(framework::ir::Graph *graph, space_table_t *space_table) const; public: std::string repr() const override; }; } // namespace analysis } // namespace inference } // namespace paddle