53 lines
1.3 KiB
C++
53 lines
1.3 KiB
C++
/**
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* Copyright 2019-2024, XGBoost Contributors
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*/
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#include <gtest/gtest.h>
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#include <xgboost/feature_map.h> // for FeatureMap
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#include <memory>
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#include "../helpers.h"
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#include "xgboost/context.h"
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#include "xgboost/gbm.h"
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#include "xgboost/json.h"
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#include "xgboost/learner.h"
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namespace xgboost::gbm {
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TEST(GBLinear, JsonIO) {
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size_t constexpr kRows = 16, kCols = 16;
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Context ctx;
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LearnerModelParam mparam{MakeMP(kCols, .5, 1)};
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std::unique_ptr<GradientBooster> gbm{
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CreateTrainedGBM("gblinear", Args{}, kRows, kCols, &mparam, &ctx)};
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Json model { Object() };
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gbm->SaveModel(&model);
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ASSERT_TRUE(IsA<Object>(model));
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std::string model_str;
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Json::Dump(model, &model_str);
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model = Json::Load(StringView{model_str.c_str(), model_str.size()});
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ASSERT_TRUE(IsA<Object>(model));
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{
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model = model["model"];
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auto weights = get<Array>(model["weights"]);
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ASSERT_EQ(weights.size(), 17);
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}
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}
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TEST(GBLinear, Dump) {
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Context ctx;
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size_t constexpr kRows = 16, kCols = 16;
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LearnerModelParam mparam{MakeMP(kCols, .5, 1)};
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std::unique_ptr<GradientBooster> gbm{
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CreateTrainedGBM("gblinear", Args{}, kRows, kCols, &mparam, &ctx)};
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FeatureMap fmap;
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ASSERT_THAT([&] { [[maybe_unused]] auto vec = gbm->DumpModel(fmap, true, "dot"); },
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GMockThrow(R"(`dot` is not supported)"));
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}
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} // namespace xgboost::gbm
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