Refactor configuration [Part II]. (#4577)
* 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
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@@ -7,7 +7,7 @@
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#include "../helpers.h"
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TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassObjGPair)) {
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xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
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xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
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std::vector<std::pair<std::string, std::string>> args {{"num_class", "3"}};
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xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax", &lparam);
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@@ -47,7 +47,7 @@ TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
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}
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TEST(Objective, DeclareUnifiedTest(SoftprobMultiClassBasic)) {
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xgboost::LearnerTrainParam lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
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xgboost::GenericParameter lparam = xgboost::CreateEmptyGenericParam(0, NGPUS);
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std::vector<std::pair<std::string, std::string>> args {
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std::pair<std::string, std::string>("num_class", "3")};
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