b52c4e13b0
Empty partition is different from empty dataset. For the former case, each worker has non-empty dask collections, but each collection might contain empty partition.
104 lines
3.2 KiB
C++
104 lines
3.2 KiB
C++
/*!
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* Copyright 2017-2021 by Contributors
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*/
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#include <dmlc/registry.h>
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#include <mutex>
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#include "xgboost/predictor.h"
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#include "xgboost/data.h"
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#include "xgboost/generic_parameters.h"
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#include "../gbm/gbtree.h"
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namespace dmlc {
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DMLC_REGISTRY_ENABLE(::xgboost::PredictorReg);
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} // namespace dmlc
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namespace xgboost {
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void PredictionContainer::ClearExpiredEntries() {
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std::vector<DMatrix*> expired;
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for (auto& kv : container_) {
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if (kv.second.ref.expired()) {
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expired.emplace_back(kv.first);
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}
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}
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for (auto const& ptr : expired) {
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container_.erase(ptr);
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}
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}
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PredictionCacheEntry &PredictionContainer::Cache(std::shared_ptr<DMatrix> m, int32_t device) {
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this->ClearExpiredEntries();
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container_[m.get()].ref = m;
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if (device != GenericParameter::kCpuId) {
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container_[m.get()].predictions.SetDevice(device);
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}
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return container_[m.get()];
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}
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PredictionCacheEntry &PredictionContainer::Entry(DMatrix *m) {
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CHECK(container_.find(m) != container_.cend());
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CHECK(container_.at(m).ref.lock())
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<< "[Internal error]: DMatrix: " << m << " has expired.";
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return container_.at(m);
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}
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decltype(PredictionContainer::container_) const& PredictionContainer::Container() {
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this->ClearExpiredEntries();
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return container_;
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}
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void Predictor::Configure(
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const std::vector<std::pair<std::string, std::string>>&) {
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}
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Predictor* Predictor::Create(
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std::string const& name, GenericParameter const* generic_param) {
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auto* e = ::dmlc::Registry<PredictorReg>::Get()->Find(name);
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if (e == nullptr) {
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LOG(FATAL) << "Unknown predictor type " << name;
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}
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auto p_predictor = (e->body)(generic_param);
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return p_predictor;
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}
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template <int32_t D>
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void ValidateBaseMarginShape(linalg::Tensor<float, D> const& margin, bst_row_t n_samples,
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bst_group_t n_groups) {
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// FIXME: Bindings other than Python doesn't have shape.
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std::string expected{"Invalid shape of base_margin. Expected: (" + std::to_string(n_samples) +
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", " + std::to_string(n_groups) + ")"};
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CHECK_EQ(margin.Shape(0), n_samples) << expected;
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CHECK_EQ(margin.Shape(1), n_groups) << expected;
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}
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void Predictor::InitOutPredictions(const MetaInfo& info, HostDeviceVector<bst_float>* out_preds,
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const gbm::GBTreeModel& model) const {
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CHECK_NE(model.learner_model_param->num_output_group, 0);
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size_t n_classes = model.learner_model_param->num_output_group;
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size_t n = n_classes * info.num_row_;
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const HostDeviceVector<bst_float>* base_margin = info.base_margin_.Data();
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if (ctx_->gpu_id >= 0) {
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out_preds->SetDevice(ctx_->gpu_id);
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}
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if (base_margin->Size() != 0) {
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out_preds->Resize(n);
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ValidateBaseMarginShape(info.base_margin_, info.num_row_, n_classes);
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out_preds->Copy(*base_margin);
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} else {
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out_preds->Resize(n);
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// cannot rely on the Resize to fill as it might skip if the size is already correct.
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out_preds->Fill(model.learner_model_param->base_score);
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}
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}
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} // namespace xgboost
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namespace xgboost {
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namespace predictor {
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// List of files that will be force linked in static links.
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#ifdef XGBOOST_USE_CUDA
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DMLC_REGISTRY_LINK_TAG(gpu_predictor);
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#endif // XGBOOST_USE_CUDA
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DMLC_REGISTRY_LINK_TAG(cpu_predictor);
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} // namespace predictor
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} // namespace xgboost
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