71b0528a2f
* Add interval accuracy * De-virtualize AFT functions * Lint * Refactor AFT metric using GPU-CPU reducer * Fix R build * Fix build on Windows * Fix copyright header * Clang-tidy * Fix crashing demo * Fix typos in comment; explain GPU ID * Remove unnecessary #include * Add C++ test for interval accuracy * Fix a bug in accuracy metric: use log pred * Refactor AFT objective using GPU-CPU Transform * Lint * Fix lint * Use Ninja to speed up build * Use time, not /usr/bin/time * Add cpu_build worker class, with concurrency = 1 * Use concurrency = 1 only for CUDA build * concurrency = 1 for clang-tidy * Address reviewer's feedback * Update link to AFT paper
82 lines
3.2 KiB
Plaintext
82 lines
3.2 KiB
Plaintext
/*!
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* Copyright (c) by Contributors 2020
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*/
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#include <gtest/gtest.h>
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#include <cmath>
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#include "xgboost/metric.h"
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#include "../helpers.h"
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#include "../../../src/common/survival_util.h"
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/** Tests for Survival metrics that should run both on CPU and GPU **/
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namespace xgboost {
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namespace common {
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TEST(Metric, DeclareUnifiedTest(AFTNegLogLik)) {
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auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
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/**
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* Test aggregate output from the AFT metric over a small test data set.
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* This is unlike AFTLoss.* tests, which verify metric values over individual data points.
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**/
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MetaInfo info;
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info.num_row_ = 4;
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info.labels_lower_bound_.HostVector()
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= { 100.0f, 0.0f, 60.0f, 16.0f };
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info.labels_upper_bound_.HostVector()
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= { 100.0f, 20.0f, std::numeric_limits<bst_float>::infinity(), 200.0f };
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info.weights_.HostVector() = std::vector<bst_float>();
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HostDeviceVector<bst_float> preds(4, std::log(64));
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struct TestCase {
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std::string dist_type;
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bst_float reference_value;
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};
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for (const auto& test_case : std::vector<TestCase>{ {"normal", 2.1508f}, {"logistic", 2.1804f},
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{"extreme", 2.0706f} }) {
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std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &lparam));
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metric->Configure({ {"aft_loss_distribution", test_case.dist_type},
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{"aft_loss_distribution_scale", "1.0"} });
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EXPECT_NEAR(metric->Eval(preds, info, false), test_case.reference_value, 1e-4);
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}
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}
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TEST(Metric, DeclareUnifiedTest(IntervalRegressionAccuracy)) {
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auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
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MetaInfo info;
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info.num_row_ = 4;
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info.labels_lower_bound_.HostVector() = { 20.0f, 0.0f, 60.0f, 16.0f };
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info.labels_upper_bound_.HostVector() = { 80.0f, 20.0f, 80.0f, 200.0f };
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info.weights_.HostVector() = std::vector<bst_float>();
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HostDeviceVector<bst_float> preds(4, std::log(60.0f));
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std::unique_ptr<Metric> metric(Metric::Create("interval-regression-accuracy", &lparam));
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EXPECT_FLOAT_EQ(metric->Eval(preds, info, false), 0.75f);
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info.labels_lower_bound_.HostVector()[2] = 70.0f;
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EXPECT_FLOAT_EQ(metric->Eval(preds, info, false), 0.50f);
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info.labels_upper_bound_.HostVector()[2] = std::numeric_limits<bst_float>::infinity();
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EXPECT_FLOAT_EQ(metric->Eval(preds, info, false), 0.50f);
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info.labels_upper_bound_.HostVector()[3] = std::numeric_limits<bst_float>::infinity();
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EXPECT_FLOAT_EQ(metric->Eval(preds, info, false), 0.50f);
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info.labels_lower_bound_.HostVector()[0] = 70.0f;
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EXPECT_FLOAT_EQ(metric->Eval(preds, info, false), 0.25f);
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}
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// Test configuration of AFT metric
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TEST(AFTNegLogLikMetric, DeclareUnifiedTest(Configuration)) {
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auto lparam = xgboost::CreateEmptyGenericParam(GPUIDX);
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std::unique_ptr<Metric> metric(Metric::Create("aft-nloglik", &lparam));
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metric->Configure({{"aft_loss_distribution", "normal"}, {"aft_loss_distribution_scale", "10"}});
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// Configuration round-trip test
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Json j_obj{ Object() };
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metric->SaveConfig(&j_obj);
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auto aft_param_json = j_obj["aft_loss_param"];
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EXPECT_EQ(get<String>(aft_param_json["aft_loss_distribution"]), "normal");
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EXPECT_EQ(get<String>(aft_param_json["aft_loss_distribution_scale"]), "10");
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}
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} // namespace common
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} // namespace xgboost
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