f0064c07ab
* Refactor configuration [Part II].
* General changes:
** Remove `Init` methods to avoid ambiguity.
** Remove `Configure(std::map<>)` to avoid redundant copying and prepare for
parameter validation. (`std::vector` is returned from `InitAllowUnknown`).
** Add name to tree updaters for easier debugging.
* Learner changes:
** Make `LearnerImpl` the only source of configuration.
All configurations are stored and carried out by `LearnerImpl::Configure()`.
** Remove booster in C API.
Originally kept for "compatibility reason", but did not state why. So here
we just remove it.
** Add a `metric_names_` field in `LearnerImpl`.
** Remove `LazyInit`. Configuration will always be lazy.
** Run `Configure` before every iteration.
* Predictor changes:
** Allocate both cpu and gpu predictor.
** Remove cpu_predictor from gpu_predictor.
`GBTree` is now used to dispatch the predictor.
** Remove some GPU Predictor tests.
* IO
No IO changes. The binary model format stability is tested by comparing
hashing value of save models between two commits
103 lines
3.5 KiB
C++
103 lines
3.5 KiB
C++
/*!
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* Copyright 2018 by Contributors
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* \file split_evaluator.h
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* \brief Used for implementing a loss term specific to decision trees. Useful for custom regularisation.
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* \author Henry Gouk
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*/
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#ifndef XGBOOST_TREE_SPLIT_EVALUATOR_H_
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#define XGBOOST_TREE_SPLIT_EVALUATOR_H_
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#include <dmlc/registry.h>
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#include <xgboost/base.h>
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#include <functional>
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#include <memory>
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#include <string>
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#include <utility>
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#include <vector>
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#define ROOT_PARENT_ID (-1 & ((1U << 31) - 1))
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namespace xgboost {
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namespace tree {
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// Should GradStats be in this header, rather than param.h?
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struct GradStats;
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class SplitEvaluator {
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public:
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// Factory method for constructing new SplitEvaluators
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static SplitEvaluator* Create(const std::string& name);
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virtual ~SplitEvaluator() = default;
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// Used to initialise any regularisation hyperparameters provided by the user
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virtual void Init(const Args& args);
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// Resets the SplitEvaluator to the state it was in after the Init was called
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virtual void Reset();
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// This will create a clone of the SplitEvaluator in host memory
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virtual SplitEvaluator* GetHostClone() const = 0;
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// Computes the score (negative loss) resulting from performing this split
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virtual bst_float ComputeSplitScore(bst_uint nodeid,
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bst_uint featureid,
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const GradStats& left_stats,
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const GradStats& right_stats,
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bst_float left_weight,
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bst_float right_weight) const = 0;
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virtual bst_float ComputeSplitScore(bst_uint nodeid,
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bst_uint featureid,
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const GradStats& left_stats,
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const GradStats& right_stats) const;
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// Compute the Score for a node with the given stats
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virtual bst_float ComputeScore(bst_uint parentid,
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const GradStats &stats,
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bst_float weight) const = 0;
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// Compute the weight for a node with the given stats
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virtual bst_float ComputeWeight(bst_uint parentid, const GradStats& stats)
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const = 0;
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virtual void AddSplit(bst_uint nodeid,
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bst_uint leftid,
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bst_uint rightid,
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bst_uint featureid,
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bst_float leftweight,
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bst_float rightweight);
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// Check whether a given feature is feasible for a given node.
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// Use this function to narrow the search space for split candidates
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virtual bool CheckFeatureConstraint(bst_uint nodeid,
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bst_uint featureid) const = 0;
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};
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struct SplitEvaluatorReg
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: public dmlc::FunctionRegEntryBase<SplitEvaluatorReg,
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std::function<SplitEvaluator* (std::unique_ptr<SplitEvaluator>)> > {};
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/*!
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* \brief Macro to register tree split evaluator.
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*
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* \code
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* // example of registering a split evaluator
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* XGBOOST_REGISTER_SPLIT_EVALUATOR(SplitEval, "splitEval")
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* .describe("Some split evaluator")
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* .set_body([]() {
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* return new SplitEval();
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* });
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* \endcode
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*/
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#define XGBOOST_REGISTER_SPLIT_EVALUATOR(UniqueID, Name) \
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static DMLC_ATTRIBUTE_UNUSED ::xgboost::tree::SplitEvaluatorReg& \
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__make_ ## SplitEvaluatorReg ## _ ## UniqueID ## __ = \
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::dmlc::Registry< ::xgboost::tree::SplitEvaluatorReg>::Get()->__REGISTER__(Name) //NOLINT
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} // namespace tree
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} // namespace xgboost
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#endif // XGBOOST_TREE_SPLIT_EVALUATOR_H_
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