gbm.h

转到此文件的文档。

#ifndef XGBOOST_GBM_H_
#define XGBOOST_GBM_H_

#include <dmlc/registry.h>
#include <xgboost/base.h>
#include <xgboost/data.h>
#include <xgboost/host_device_vector.h>
#include <xgboost/model.h>

#include <vector>
#include <string>
#include <functional>
#include <memory>

namespace xgboost {

class Json;
class FeatureMap;
class ObjFunction;

struct Context;
struct LearnerModelParam;
struct PredictionCacheEntry;

class GradientBooster : public Model, public Configurable {
 protected
 Context const* ctx_;
 explicit GradientBooster(Context const* ctx) : ctx_{ctx} {}

 public
 ~GradientBooster() override = default;
 virtual void Configure(Args const& cfg) = 0;
 virtual void Load(dmlc::Stream* fi) = 0;
 virtual void Save(dmlc::Stream* fo) const = 0;
 virtual void Slice(bst_layer_t /*begin*/, bst_layer_t /*end*/, bst_layer_t /*step*/,
 GradientBooster* /*out*/, bool* /*out_of_bound*/) const {
 LOG(FATAL) << "Slice is not supported by the current booster.";
 }
 [[nodiscard]] virtual std::int32_t BoostedRounds() const = 0;
 [[nodiscard]] virtual bool ModelFitted() const = 0;
 virtual void DoBoost(DMatrix* p_fmat, linalg::Matrix<GradientPair>* in_gpair,
 PredictionCacheEntry*, ObjFunction const* obj) = 0;

 virtual void PredictBatch(DMatrix* dmat, PredictionCacheEntry* out_preds, bool training,
 bst_layer_t begin, bst_layer_t end) = 0;

 virtual void InplacePredict(std::shared_ptr<DMatrix>, float, PredictionCacheEntry*, bst_layer_t,
 bst_layer_t) const {
 LOG(FATAL) << "Inplace predict is not supported by the current booster.";
 }
 virtual void PredictLeaf(DMatrix *dmat,
 HostDeviceVector<bst_float> *out_preds,
 unsigned layer_begin, unsigned layer_end) = 0;

 virtual void PredictContribution(DMatrix* dmat, HostDeviceVector<float>* out_contribs,
 bst_layer_t layer_begin, bst_layer_t layer_end,
 bool approximate = false) = 0;

 virtual void PredictInteractionContributions(DMatrix* dmat, HostDeviceVector<float>* out_contribs,
 bst_layer_t layer_begin, bst_layer_t layer_end,
 bool approximate) = 0;

 [[nodiscard]] virtual std::vector<std::string> DumpModel(const FeatureMap& fmap, bool with_stats,
 std::string format) const = 0;

 virtual void FeatureScore(std::string const& importance_type,
 common::Span<int32_t const> trees,
 std::vector<bst_feature_t>* features,
 std::vector<float>* scores) const = 0;
 [[nodiscard]] virtual bool UseGPU() const = 0;
 static GradientBooster* Create(const std::string& name, Context const* ctx,
 LearnerModelParam const* learner_model_param);
};

struct GradientBoosterReg
 : public dmlc::FunctionRegEntryBase<
 GradientBoosterReg,
 std::function<GradientBooster*(LearnerModelParam const* learner_model_param,
 Context const* ctx)> > {};

#define XGBOOST_REGISTER_GBM(UniqueId, Name) \
 static DMLC_ATTRIBUTE_UNUSED ::xgboost::GradientBoosterReg & \
 __make_ ## GradientBoosterReg ## _ ## UniqueId ## __ = \
 ::dmlc::Registry< ::xgboost::GradientBoosterReg>::Get()->__REGISTER__(Name)

} // namespace xgboost
#endif // XGBOOST_GBM_H_