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Porting elementwise metrics to GPU. (#3952)

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* Port elementwise metrics to GPU.

* All elementwise metrics are converted to static polymorphic.
* Create a reducer for metrics reduction.
* Remove const of Metric::Eval to accommodate CubMemory.
This commit is contained in:
Jiaming Yuan
2018-12-01 18:46:45 +13:00
committed by GitHub
parent a9d684db18
commit 48dddfd635
14 changed files with 605 additions and 279 deletions
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13
src/learner.cc
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@@ -310,6 +310,10 @@ class LearnerImpl : public Learner {
if (obj_ != nullptr) {
obj_->Configure(cfg_.begin(), cfg_.end());
}
for (auto& p_metric : metrics_) {
p_metric->Configure(cfg_.begin(), cfg_.end());
}
}
void InitModel() override { this->LazyInitModel(); }
@@ -407,6 +411,10 @@ class LearnerImpl : public Learner {
cfg_["num_class"] = common::ToString(mparam_.num_class);
cfg_["num_feature"] = common::ToString(mparam_.num_feature);
obj_->Configure(cfg_.begin(), cfg_.end());
for (auto& p_metric : metrics_) {
p_metric->Configure(cfg_.begin(), cfg_.end());
}
}
// rabit save model to rabit checkpoint
@@ -503,13 +511,14 @@ class LearnerImpl : public Learner {
os << '[' << iter << ']' << std::setiosflags(std::ios::fixed);
if (metrics_.size() == 0 && tparam_.disable_default_eval_metric <= 0) {
metrics_.emplace_back(Metric::Create(obj_->DefaultEvalMetric()));
metrics_.back()->Configure(cfg_.begin(), cfg_.end());
}
for (size_t i = 0; i < data_sets.size(); ++i) {
this->PredictRaw(data_sets[i], &preds_);
obj_->EvalTransform(&preds_);
for (auto& ev : metrics_) {
os << '\t' << data_names[i] << '-' << ev->Name() << ':'
<< ev->Eval(preds_.ConstHostVector(), data_sets[i]->Info(),
<< ev->Eval(preds_, data_sets[i]->Info(),
tparam_.dsplit == DataSplitMode::kRow);
}
}
@@ -553,7 +562,7 @@ class LearnerImpl : public Learner {
this->PredictRaw(data, &preds_);
obj_->EvalTransform(&preds_);
return std::make_pair(metric,
ev->Eval(preds_.ConstHostVector(), data->Info(),
ev->Eval(preds_, data->Info(),
tparam_.dsplit == DataSplitMode::kRow));
}