5fc5ec539d
* Robust regularization of AFT gradient and hessian * Fix AFT doc; expose it to tutorial TOC * Apply robust regularization to uncensored case too * Revise unit test slightly * Fix lint * Update test_survival.py * Use GradientPairPrecise * Remove unused variables
45 lines
2.0 KiB
C++
45 lines
2.0 KiB
C++
/*!
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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 "../../../src/common/survival_util.h"
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namespace xgboost {
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namespace common {
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inline static void RobustTestSuite(ProbabilityDistributionType dist_type,
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double y_lower, double y_upper, double sigma) {
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AFTLoss loss(dist_type);
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for (int i = 50; i >= -50; --i) {
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const double y_pred = std::pow(10.0, static_cast<double>(i));
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const double z = (std::log(y_lower) - std::log(y_pred)) / sigma;
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const double gradient = loss.Gradient(y_lower, y_upper, std::log(y_pred), sigma);
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const double hessian = loss.Hessian(y_lower, y_upper, std::log(y_pred), sigma);
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ASSERT_FALSE(std::isnan(gradient)) << "z = " << z << ", y \\in ["
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<< y_lower << ", " << y_upper << "], y_pred = " << y_pred
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<< ", dist = " << static_cast<int>(dist_type);
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ASSERT_FALSE(std::isinf(gradient)) << "z = " << z << ", y \\in ["
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<< y_lower << ", " << y_upper << "], y_pred = " << y_pred
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<< ", dist = " << static_cast<int>(dist_type);
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ASSERT_FALSE(std::isnan(hessian)) << "z = " << z << ", y \\in ["
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<< y_lower << ", " << y_upper << "], y_pred = " << y_pred
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<< ", dist = " << static_cast<int>(dist_type);
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ASSERT_FALSE(std::isinf(hessian)) << "z = " << z << ", y \\in ["
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<< y_lower << ", " << y_upper << "], y_pred = " << y_pred
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<< ", dist = " << static_cast<int>(dist_type);
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}
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}
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TEST(AFTLoss, RobustGradientPair) { // Ensure that INF and NAN don't show up in gradient pair
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RobustTestSuite(ProbabilityDistributionType::kNormal, 16.0, 200.0, 2.0);
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RobustTestSuite(ProbabilityDistributionType::kLogistic, 16.0, 200.0, 2.0);
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RobustTestSuite(ProbabilityDistributionType::kExtreme, 16.0, 200.0, 2.0);
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RobustTestSuite(ProbabilityDistributionType::kNormal, 100.0, 100.0, 2.0);
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RobustTestSuite(ProbabilityDistributionType::kLogistic, 100.0, 100.0, 2.0);
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RobustTestSuite(ProbabilityDistributionType::kExtreme, 100.0, 100.0, 2.0);
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}
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} // namespace common
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} // namespace xgboost
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