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Prevent copying data to host. (#4795)

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Jiaming Yuan 2019-08-20 23:06:27 -04:00 committed by GitHub
parent 3fa2ceb193
commit fba298fecb
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 17 additions and 9 deletions
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16
src/gbm/gbtree.cc
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@ -57,6 +57,14 @@ void GBTree::Configure(const Args& cfg) {
monitor_.Init("GBTree");
if (tparam_.tree_method == TreeMethod::kGPUHist &&
std::none_of(cfg.cbegin(), cfg.cend(),
[](std::pair<std::string, std::string> const& arg) {
return arg.first == "predictor";
})) {
tparam_.predictor = "gpu_predictor";
}
configured_ = true;
}
@ -88,7 +96,7 @@ void GBTree::PerformTreeMethodHeuristic(std::map<std::string, std::string> const
// set, since only experts are expected to do so.
return;
}
// tparam_ is set before calling this function.
if (tparam_.tree_method != TreeMethod::kAuto) {
return;
}
@ -112,7 +120,6 @@ void GBTree::PerformTreeMethodHeuristic(std::map<std::string, std::string> const
tparam_.tree_method = TreeMethod::kApprox;
} else {
tparam_.tree_method = TreeMethod::kExact;
tparam_.updater_seq = "grow_colmaker,prune";
}
LOG(DEBUG) << "Using tree method: " << static_cast<int>(tparam_.tree_method);
}
@ -131,8 +138,9 @@ void GBTree::ConfigureUpdaters(const std::map<std::string, std::string>& cfg) {
/* Choose updaters according to tree_method parameters */
switch (tparam_.tree_method) {
case TreeMethod::kAuto:
// Use heuristic to choose between 'exact' and 'approx'
// This choice is deferred to PerformTreeMethodHeuristic().
// Use heuristic to choose between 'exact' and 'approx' This
// choice is carried out in PerformTreeMethodHeuristic() before
// calling this function.
break;
case TreeMethod::kApprox:
tparam_.updater_seq = "grow_histmaker,prune";

10
src/learner.cc
View File

@ -530,7 +530,7 @@ class LearnerImpl : public Learner {
void PredictRaw(DMatrix* data, HostDeviceVector<bst_float>* out_preds,
unsigned ntree_limit = 0) const {
CHECK(gbm_ != nullptr)
<< "Predict must happen after Load or InitModel";
<< "Predict must happen after Load or configuration";
this->ValidateDMatrix(data);
gbm_->PredictBatch(data, out_preds, ntree_limit);
}
@ -619,11 +619,11 @@ class LearnerImpl : public Learner {
void ValidateDMatrix(DMatrix* p_fmat) const {
MetaInfo const& info = p_fmat->Info();
auto const& weights = info.weights_.HostVector();
if (info.group_ptr_.size() != 0 && weights.size() != 0) {
CHECK(weights.size() == info.group_ptr_.size() - 1)
auto const& weights = info.weights_;
if (info.group_ptr_.size() != 0 && weights.Size() != 0) {
CHECK(weights.Size() == info.group_ptr_.size() - 1)
<< "\n"
<< "weights size: " << weights.size() << ", "
<< "weights size: " << weights.Size() << ", "
<< "groups size: " << info.group_ptr_.size() -1 << ", "
<< "num rows: " << p_fmat->Info().num_row_ << "\n"
<< "Number of weights should be equal to number of groups in ranking task.";