ae536756ae
* Apply Configurable to objective functions. * Apply Model to Learner and Regtree, gbm. * Add Load/SaveConfig to objs. * Refactor obj tests to use smart pointer. * Dummy methods for Save/Load Model.
61 lines
1.8 KiB
C++
61 lines
1.8 KiB
C++
// Copyright by Contributors
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#include <xgboost/objective.h>
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#include <xgboost/generic_parameters.h>
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#include "../helpers.h"
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#include <xgboost/json.h>
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namespace xgboost {
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TEST(Objective, PairwiseRankingGPair) {
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xgboost::GenericParameter tparam;
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std::vector<std::pair<std::string, std::string>> args;
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tparam.InitAllowUnknown(args);
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std::unique_ptr<xgboost::ObjFunction> obj {
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xgboost::ObjFunction::Create("rank:pairwise", &tparam)
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};
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obj->Configure(args);
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CheckConfigReload(obj, "rank:pairwise");
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// Test with setting sample weight to second query group
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CheckRankingObjFunction(obj,
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{0, 0.1f, 0, 0.1f},
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{0, 1, 0, 1},
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{2.0f, 0.0f},
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{0, 2, 4},
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{1.9f, -1.9f, 0.0f, 0.0f},
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{1.995f, 1.995f, 0.0f, 0.0f});
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CheckRankingObjFunction(obj,
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{0, 0.1f, 0, 0.1f},
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{0, 1, 0, 1},
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{1.0f, 1.0f},
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{0, 2, 4},
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{0.95f, -0.95f, 0.95f, -0.95f},
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{0.9975f, 0.9975f, 0.9975f, 0.9975f});
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ASSERT_NO_THROW(obj->DefaultEvalMetric());
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}
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TEST(Objective, NDCG_Json_IO) {
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xgboost::GenericParameter tparam;
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tparam.InitAllowUnknown(Args{});
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std::unique_ptr<xgboost::ObjFunction> obj {
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xgboost::ObjFunction::Create("rank:ndcg", &tparam)
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};
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obj->Configure(Args{});
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Json j_obj {Object()};
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obj->SaveConfig(&j_obj);
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ASSERT_EQ(get<String>(j_obj["name"]), "rank:ndcg");;
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auto const& j_param = j_obj["lambda_rank_param"];
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ASSERT_EQ(get<String>(j_param["num_pairsample"]), "1");
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ASSERT_EQ(get<String>(j_param["fix_list_weight"]), "0");
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}
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} // namespace xgboost
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