Inheritance diagram for xgboost::predictor::CPUPredictor:

Public Member Functions
	CPUPredictor (Context const *ctx)

void	PredictBatch (DMatrix dmat, PredictionCacheEntry predts, const gbm::GBTreeModel &model, uint32_t tree_begin, uint32_t tree_end=0) const override
	Generate batch predictions for a given feature matrix.

template<typename Adapter , size_t kBlockSize>
void	DispatchedInplacePredict (std::any const &x, std::shared_ptr< DMatrix > p_m, const gbm::GBTreeModel &model, float missing, PredictionCacheEntry *out_preds, uint32_t tree_begin, uint32_t tree_end) const

bool	InplacePredict (std::shared_ptr< DMatrix > p_m, const gbm::GBTreeModel &model, float missing, PredictionCacheEntry *out_preds, uint32_t tree_begin, unsigned tree_end) const override

void	PredictInstance (const SparsePage::Inst &inst, std::vector< bst_float > *out_preds, const gbm::GBTreeModel &model, unsigned ntree_limit, bool is_column_split) const override
	online prediction function, predict score for one instance at a time NOTE: use the batch prediction interface if possible, batch prediction is usually more efficient than online prediction This function is NOT threadsafe, make sure you only call from one thread.

void	PredictLeaf (DMatrix p_fmat, HostDeviceVector< bst_float > out_preds, const gbm::GBTreeModel &model, unsigned ntree_limit) const override
	predict the leaf index of each tree, the output will be nsample * ntree vector this is only valid in gbtree predictor.

void	PredictContribution (DMatrix p_fmat, HostDeviceVector< float > out_contribs, const gbm::GBTreeModel &model, uint32_t ntree_limit, std::vector< bst_float > const *tree_weights, bool approximate, int condition, unsigned condition_feature) const override

void	PredictInteractionContributions (DMatrix p_fmat, HostDeviceVector< bst_float > out_contribs, const gbm::GBTreeModel &model, unsigned ntree_limit, std::vector< bst_float > const *tree_weights, bool approximate) const override

Public Member Functions inherited from xgboost::Predictor
	Predictor (Context const *ctx)

virtual void	Configure (Args const &)
	Configure and register input matrices in prediction cache.

void	InitOutPredictions (const MetaInfo &info, HostDeviceVector< bst_float > *out_predt, const gbm::GBTreeModel &model) const
	Initialize output prediction.

virtual bool	InplacePredict (std::shared_ptr< DMatrix > p_fmat, const gbm::GBTreeModel &model, float missing, PredictionCacheEntry *out_preds, uint32_t tree_begin=0, uint32_t tree_end=0) const =0
	Inplace prediction.

virtual void	PredictContribution (DMatrix dmat, HostDeviceVector< bst_float > out_contribs, const gbm::GBTreeModel &model, unsigned tree_end=0, std::vector< bst_float > const *tree_weights=nullptr, bool approximate=false, int condition=0, unsigned condition_feature=0) const =0
	feature contributions to individual predictions; the output will be a vector of length (nfeats + 1) * num_output_group * nsample, arranged in that order.

Protected Member Functions
void	PredictDMatrix (DMatrix p_fmat, std::vector< bst_float > out_preds, gbm::GBTreeModel const &model, int32_t tree_begin, int32_t tree_end) const

Additional Inherited Members
Static Public Member Functions inherited from xgboost::Predictor
static Predictor *	Create (std::string const &name, Context const *ctx)
	Creates a new Predictor*.

Protected Attributes inherited from xgboost::Predictor
Context const *	ctx_

Member Function Documentation

◆ PredictBatch()

void xgboost::predictor::CPUPredictor::PredictBatch	(	DMatrix *	dmat,
		PredictionCacheEntry *	out_preds,
		const gbm::GBTreeModel &	model,
		uint32_t	tree_begin,
		uint32_t	tree_end = `0`
	)		const

inlineoverridevirtual

Generate batch predictions for a given feature matrix.

May use cached predictions if available instead of calculating from scratch.

Parameters

[in,out]	dmat	Feature matrix.
[in,out]	out_preds	The output preds.
	model	The model to predict from.
	tree_begin	The tree begin index.
	tree_end	The tree end index.

Implements xgboost::Predictor.

◆ PredictInstance()

void xgboost::predictor::CPUPredictor::PredictInstance	(	const SparsePage::Inst &	inst,
		std::vector< bst_float > *	out_preds,
		const gbm::GBTreeModel &	model,
		unsigned	tree_end,
		bool	is_column_split
	)		const

inlineoverridevirtual

online prediction function, predict score for one instance at a time NOTE: use the batch prediction interface if possible, batch prediction is usually more efficient than online prediction This function is NOT threadsafe, make sure you only call from one thread.

Parameters

	inst	The instance to predict.
[in,out]	out_preds	The output preds.
	model	The model to predict from
	tree_end	(Optional) The tree end index.
	is_column_split	(Optional) If the data is split column-wise.

Implements xgboost::Predictor.

◆ PredictInteractionContributions()

void xgboost::predictor::CPUPredictor::PredictInteractionContributions	(	DMatrix *	p_fmat,
		HostDeviceVector< bst_float > *	out_contribs,
		const gbm::GBTreeModel &	model,
		unsigned	ntree_limit,
		std::vector< bst_float > const *	tree_weights,
		bool	approximate
	)		const

inlineoverridevirtual

Implements xgboost::Predictor.

◆ PredictLeaf()

void xgboost::predictor::CPUPredictor::PredictLeaf	(	DMatrix *	dmat,
		HostDeviceVector< bst_float > *	out_preds,
		const gbm::GBTreeModel &	model,
		unsigned	tree_end
	)		const

inlineoverridevirtual

predict the leaf index of each tree, the output will be nsample * ntree vector this is only valid in gbtree predictor.

Parameters

[in,out]	dmat	The input feature matrix.
[in,out]	out_preds	The output preds.
	model	Model to make predictions from.
	tree_end	(Optional) The tree end index.

Implements xgboost::Predictor.

The documentation for this class was generated from the following file:

External/xgboost/src/predictor/cpu_predictor.cc

Public Member Functions

Protected Member Functions

Additional Inherited Members

Member Function Documentation

◆ PredictBatch()

◆ PredictInstance()

◆ PredictInteractionContributions()

◆ PredictLeaf()