* Only define `gpu_id` and `n_gpus` in `LearnerTrainParam` * Pass LearnerTrainParam through XGBoost vid factory method. * Disable all GPU usage when GPU related parameters are not specified (fixes XGBoost choosing GPU over aggressively). * Test learner train param io. * Fix gpu pickling.
68 lines
2.3 KiB
C++
68 lines
2.3 KiB
C++
/*!
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* Copyright 2018-2019 XGBoost contributors
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*/
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#include <xgboost/objective.h>
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#include <xgboost/generic_parameters.h>
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#include "../../src/common/common.h"
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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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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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obj->Configure(args);
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CheckObjFunction(obj,
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{1.0f, 0.0f, 2.0f, 2.0f, 0.0f, 1.0f}, // preds
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{1.0f, 0.0f}, // labels
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{1.0f, 1.0f}, // weights
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{0.24f, -0.91f, 0.66f, -0.33f, 0.09f, 0.24f}, // grad
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{0.36f, 0.16f, 0.44f, 0.45f, 0.16f, 0.37f}); // hess
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ASSERT_NO_THROW(obj->DefaultEvalMetric());
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delete obj;
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}
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TEST(Objective, DeclareUnifiedTest(SoftmaxMultiClassBasic)) {
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auto 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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xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softmax", &lparam);
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obj->Configure(args);
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xgboost::HostDeviceVector<xgboost::bst_float> io_preds = {2.0f, 0.0f, 1.0f,
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1.0f, 0.0f, 2.0f};
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std::vector<xgboost::bst_float> out_preds = {0.0f, 2.0f};
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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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delete obj;
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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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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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xgboost::ObjFunction * obj = xgboost::ObjFunction::Create("multi:softprob", &lparam);
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obj->Configure(args);
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xgboost::HostDeviceVector<xgboost::bst_float> io_preds = {2.0f, 0.0f, 1.0f};
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std::vector<xgboost::bst_float> out_preds = {0.66524096f, 0.09003057f, 0.24472847f};
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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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delete obj;
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}
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