126 lines
5.0 KiB
C++
126 lines
5.0 KiB
C++
/**
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* Copyright 2017-2023 by XGBoost contributors
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*/
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#include <gtest/gtest.h>
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#include <xgboost/context.h>
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#include <xgboost/json.h>
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#include <xgboost/objective.h>
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#include "../../../src/common/linalg_op.h" // for begin, end
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#include "../../../src/objective/adaptive.h"
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#include "../../../src/tree/param.h" // for TrainParam
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#include "../helpers.h"
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#include "xgboost/base.h"
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#include "xgboost/data.h"
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#include "xgboost/linalg.h"
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#include "test_regression_obj.h"
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namespace xgboost {
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void TestLinearRegressionGPair(const Context* ctx) {
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std::string obj_name = "reg:squarederror";
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std::vector<std::pair<std::string, std::string>> args;
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std::unique_ptr<ObjFunction> obj{ObjFunction::Create(obj_name, ctx)};
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obj->Configure(args);
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CheckObjFunction(obj,
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{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
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{0, 0, 0, 0, 1, 1, 1, 1},
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{1, 1, 1, 1, 1, 1, 1, 1},
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{0, 0.1f, 0.9f, 1.0f, -1.0f, -0.9f, -0.1f, 0},
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{1, 1, 1, 1, 1, 1, 1, 1});
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CheckObjFunction(obj,
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{0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
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{0, 0, 0, 0, 1, 1, 1, 1},
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{}, // empty weight
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{0, 0.1f, 0.9f, 1.0f, -1.0f, -0.9f, -0.1f, 0},
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{1, 1, 1, 1, 1, 1, 1, 1});
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ASSERT_NO_THROW(obj->DefaultEvalMetric());
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}
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void TestSquaredLog(const Context* ctx) {
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std::string obj_name = "reg:squaredlogerror";
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std::vector<std::pair<std::string, std::string>> args;
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std::unique_ptr<ObjFunction> obj{ObjFunction::Create(obj_name, ctx)};
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obj->Configure(args);
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CheckConfigReload(obj, obj_name);
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CheckObjFunction(obj,
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{0.1f, 0.2f, 0.4f, 0.8f, 1.6f}, // pred
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{1.0f, 1.0f, 1.0f, 1.0f, 1.0f}, // labels
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{1.0f, 1.0f, 1.0f, 1.0f, 1.0f}, // weights
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{-0.5435f, -0.4257f, -0.25475f, -0.05855f, 0.1009f},
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{ 1.3205f, 1.0492f, 0.69215f, 0.34115f, 0.1091f});
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CheckObjFunction(obj,
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{0.1f, 0.2f, 0.4f, 0.8f, 1.6f}, // pred
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{1.0f, 1.0f, 1.0f, 1.0f, 1.0f}, // labels
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{}, // empty weights
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{-0.5435f, -0.4257f, -0.25475f, -0.05855f, 0.1009f},
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{ 1.3205f, 1.0492f, 0.69215f, 0.34115f, 0.1091f});
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ASSERT_EQ(obj->DefaultEvalMetric(), std::string{"rmsle"});
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}
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void TestLogisticRegressionGPair(const Context* ctx) {
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std::string obj_name = "reg:logistic";
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std::vector<std::pair<std::string, std::string>> args;
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std::unique_ptr<ObjFunction> obj{ObjFunction::Create(obj_name, ctx)};
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obj->Configure(args);
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CheckConfigReload(obj, obj_name);
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CheckObjFunction(obj,
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{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1}, // preds
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{ 0, 0, 0, 0, 1, 1, 1, 1}, // labels
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{ 1, 1, 1, 1, 1, 1, 1, 1}, // weights
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{ 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f}, // out_grad
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{0.25f, 0.24f, 0.20f, 0.19f, 0.25f, 0.24f, 0.20f, 0.19f}); // out_hess
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}
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void TestLogisticRegressionBasic(const Context* ctx) {
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std::string obj_name = "reg:logistic";
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std::vector<std::pair<std::string, std::string>> args;
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std::unique_ptr<ObjFunction> obj{ObjFunction::Create(obj_name, ctx)};
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obj->Configure(args);
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CheckConfigReload(obj, obj_name);
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// test label validation
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EXPECT_ANY_THROW(CheckObjFunction(obj, {0}, {10}, {1}, {0}, {0}))
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<< "Expected error when label not in range [0,1f] for LogisticRegression";
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// test ProbToMargin
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EXPECT_NEAR(obj->ProbToMargin(0.1f), -2.197f, 0.01f);
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EXPECT_NEAR(obj->ProbToMargin(0.5f), 0, 0.01f);
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EXPECT_NEAR(obj->ProbToMargin(0.9f), 2.197f, 0.01f);
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EXPECT_ANY_THROW((void)obj->ProbToMargin(10))
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<< "Expected error when base_score not in range [0,1f] for LogisticRegression";
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// test PredTransform
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HostDeviceVector<bst_float> io_preds = {0, 0.1f, 0.5f, 0.9f, 1};
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std::vector<bst_float> out_preds = {0.5f, 0.524f, 0.622f, 0.710f, 0.731f};
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obj->PredTransform(&io_preds);
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auto& preds = io_preds.HostVector();
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for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
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EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
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}
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}
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void TestsLogisticRawGPair(const Context* ctx) {
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std::string obj_name = "binary:logitraw";
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std::vector<std::pair<std::string, std::string>> args;
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std::unique_ptr<ObjFunction> obj {ObjFunction::Create(obj_name, ctx)};
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obj->Configure(args);
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CheckObjFunction(obj,
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{ 0, 0.1f, 0.9f, 1, 0, 0.1f, 0.9f, 1},
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{ 0, 0, 0, 0, 1, 1, 1, 1},
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{ 1, 1, 1, 1, 1, 1, 1, 1},
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{ 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
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{0.25f, 0.24f, 0.20f, 0.19f, 0.25f, 0.24f, 0.20f, 0.19f});
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}
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} // namespace xgboost
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