lane_scanning_evaluator.h

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/******************************************************************************
 * Copyright 2018 The Apollo 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 <string>
#include <vector>
 
#include "torch/script.h"
#include "torch/torch.h"
 
#include "modules/prediction/container/obstacles/obstacles_container.h"
#include "modules/prediction/evaluator/evaluator.h"
 
namespace apollo {
namespace prediction {
 
class LaneScanningEvaluator : public Evaluator {
 public:
  LaneScanningEvaluator();
 
  virtual ~LaneScanningEvaluator() = default;
 
  bool Evaluate(Obstacle* obstacle_ptr,
                ObstaclesContainer* obstacles_container) override;
 
  bool Evaluate(Obstacle* obstacle_ptr, ObstaclesContainer* obstacles_container,
                std::vector<Obstacle*> dynamic_env) override;
 
  bool ExtractFeatures(const Obstacle* obstacle_ptr,
                       const LaneGraph* lane_graph_ptr,
                       std::vector<double>* feature_values);
 
  bool ExtractStringFeatures(
      const LaneGraph& lane_graph,
      std::vector<std::string>* const string_feature_values);
 
  std::string GetName() override { return "LANE_SCANNING_EVALUATOR"; }
 
 private:
  void LoadModel();
 
  bool ExtractObstacleFeatures(const Obstacle* obstacle_ptr,
                               std::vector<double>* feature_values);
 
  bool ExtractStaticEnvFeatures(const Obstacle* obstacle_ptr,
                                const LaneGraph* lane_graph_ptr,
                                std::vector<double>* feature_values,
                                std::vector<int>* lane_sequence_idx_to_remove);
 
  void ModelInference(const std::vector<torch::jit::IValue>& torch_inputs,
                      torch::jit::script::Module torch_model,
                      Feature* feature_ptr);
 
 private:
  static const size_t OBSTACLE_FEATURE_SIZE = 20 * (9 + 40);
  static const size_t INTERACTION_FEATURE_SIZE = 8;
  static const size_t SINGLE_LANE_FEATURE_SIZE = 4;
  static const size_t LANE_POINTS_SIZE = 100;          // 50m
  static const size_t BACKWARD_LANE_POINTS_SIZE = 50;  // 25m
  static const size_t MAX_NUM_LANE = 10;
  static const size_t SHORT_TERM_TRAJECTORY_SIZE = 10;
 
  torch::jit::script::Module torch_lane_scanning_model_;
  torch::Device device_;
};
 
}  // namespace prediction
}  // namespace apollo