Method RenewTreeOutput

src/treelearner/serial_tree_learner.cpp:855–893

void SerialTreeLearner::RenewTreeOutput(Tree* tree, const ObjectiveFunction* obj, std::function<double(const label_t*, int)> residual_getter,
                                        data_size_t total_num_data, const data_size_t* bag_indices, data_size_t bag_cnt) const {
  if (obj != nullptr && obj->IsRenewTreeOutput()) {
    CHECK(tree->num_leaves() <= data_partition_->num_leaves());
    const data_size_t* bag_mapper = nullptr;
    if (total_num_data != num_data_) {
      CHECK(bag_cnt == num_data_);
      bag_mapper = bag_indices;
    }
    std::vector<int> n_nozeroworker_perleaf(tree->num_leaves(), 1);
    int num_machines = Network::num_machines();
    #pragma omp parallel for schedule(static)
    for (int i = 0; i < tree->num_leaves(); ++i) {
      const double output = static_cast<double>(tree->LeafOutput(i));
      data_size_t cnt_leaf_data = 0;
      auto index_mapper = data_partition_->GetIndexOnLeaf(i, &cnt_leaf_data);
      if (cnt_leaf_data > 0) {
        // bag_mapper[index_mapper[i]]
        const double new_output = obj->RenewTreeOutput(output, residual_getter, index_mapper, bag_mapper, cnt_leaf_data);
        tree->SetLeafOutput(i, new_output);
      } else {
        CHECK(num_machines > 1);
        tree->SetLeafOutput(i, 0.0);
        n_nozeroworker_perleaf[i] = 0;
      }
    }
    if (num_machines > 1) {
      std::vector<double> outputs(tree->num_leaves());
      for (int i = 0; i < tree->num_leaves(); ++i) {
        outputs[i] = static_cast<double>(tree->LeafOutput(i));
      }
      outputs = Network::GlobalSum(&outputs);
      n_nozeroworker_perleaf = Network::GlobalSum(&n_nozeroworker_perleaf);
      for (int i = 0; i < tree->num_leaves(); ++i) {
        tree->SetLeafOutput(i, outputs[i] / n_nozeroworker_perleaf[i]);
      }
    }
  }
}

}  // namespace LightGBM