Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add max_cat_threshold to GPU and handle missing cat values. (#8212)

Browse Source
This commit is contained in:
Jiaming Yuan
2022-09-07 00:57:51 +08:00
committed by GitHub
parent 441ffc017a
commit b5eb36f1af
10 changed files with 546 additions and 122 deletions
Download Patch File Download Diff File Expand all files Collapse all files

56
tests/cpp/tree/test_evaluate_splits.h
View File

@@ -43,7 +43,7 @@ class TestPartitionBasedSplit : public ::testing::Test {
auto &h_vals = cuts_.cut_values_.HostVector();
h_vals.resize(n_bins_);
std::iota(h_vals.begin(), h_vals.end(), 0.0);
cuts_.min_vals_.Resize(1);
hist_.Init(cuts_.TotalBins());
@@ -97,5 +97,59 @@ class TestPartitionBasedSplit : public ::testing::Test {
} while (std::next_permutation(sorted_idx_.begin(), sorted_idx_.end()));
}
};
inline auto MakeCutsForTest(std::vector<float> values, std::vector<uint32_t> ptrs,
std::vector<float> min_values, int32_t device) {
common::HistogramCuts cuts;
cuts.cut_values_.HostVector() = values;
cuts.cut_ptrs_.HostVector() = ptrs;
cuts.min_vals_.HostVector() = min_values;
if (device >= 0) {
cuts.cut_ptrs_.SetDevice(device);
cuts.cut_values_.SetDevice(device);
cuts.min_vals_.SetDevice(device);
}
return cuts;
}
class TestCategoricalSplitWithMissing : public testing::Test {
protected:
common::HistogramCuts cuts_;
// Setup gradients and parent sum with missing values.
GradientPairPrecise parent_sum_{1.0, 6.0};
std::vector<GradientPairPrecise> feature_histogram_{
{0.5, 0.5}, {0.5, 0.5}, {1.0, 1.0}, {1.0, 1.0}};
TrainParam param_;
void SetUp() override {
cuts_ = MakeCutsForTest({0.0, 1.0, 2.0, 3.0}, {0, 4}, {0.0}, -1);
auto max_cat = *std::max_element(cuts_.cut_values_.HostVector().begin(),
cuts_.cut_values_.HostVector().end());
cuts_.SetCategorical(true, max_cat);
param_.UpdateAllowUnknown(
Args{{"min_child_weight", "0"}, {"reg_lambda", "0"}, {"max_cat_to_onehot", "1"}});
}
void CheckResult(float loss_chg, bst_feature_t split_ind, float fvalue, bool is_cat,
bool dft_left, GradientPairPrecise left_sum, GradientPairPrecise right_sum) {
// forward
// it: 0, gain: 0.545455
// it: 1, gain: 1.000000
// it: 2, gain: 2.250000
// backward
// it: 3, gain: 1.000000
// it: 2, gain: 2.250000
// it: 1, gain: 3.142857
ASSERT_NEAR(loss_chg, 2.97619, kRtEps);
ASSERT_TRUE(is_cat);
ASSERT_TRUE(std::isnan(fvalue));
ASSERT_EQ(split_ind, 0);
ASSERT_FALSE(dft_left);
ASSERT_EQ(left_sum.GetHess(), 2.5);
ASSERT_EQ(right_sum.GetHess(), parent_sum_.GetHess() - left_sum.GetHess());
}
};
} // namespace tree
} // namespace xgboost