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Use double for GPU Hist node sum. (#7507)

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This commit is contained in:
Jiaming Yuan
2021-12-22 08:41:35 +08:00
committed by GitHub
parent eabec370e4
commit 7f399eac8b
5 changed files with 85 additions and 98 deletions
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18
tests/cpp/tree/gpu_hist/test_evaluate_splits.cu
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@@ -17,7 +17,7 @@ auto ZeroParam() {
void TestEvaluateSingleSplit(bool is_categorical) {
thrust::device_vector<DeviceSplitCandidate> out_splits(1);
GradientPair parent_sum(0.0, 1.0);
GradientPairPrecise parent_sum(0.0, 1.0);
TrainParam tparam = ZeroParam();
GPUTrainingParam param{tparam};
@@ -73,7 +73,7 @@ TEST(GpuHist, EvaluateCategoricalSplit) {
TEST(GpuHist, EvaluateSingleSplitMissing) {
thrust::device_vector<DeviceSplitCandidate> out_splits(1);
GradientPair parent_sum(1.0, 1.5);
GradientPairPrecise parent_sum(1.0, 1.5);
TrainParam tparam = ZeroParam();
GPUTrainingParam param{tparam};
@@ -104,8 +104,8 @@ TEST(GpuHist, EvaluateSingleSplitMissing) {
EXPECT_EQ(result.findex, 0);
EXPECT_EQ(result.fvalue, 1.0);
EXPECT_EQ(result.dir, kRightDir);
EXPECT_EQ(result.left_sum, GradientPair(-0.5, 0.5));
EXPECT_EQ(result.right_sum, GradientPair(1.5, 1.0));
EXPECT_EQ(result.left_sum, GradientPairPrecise(-0.5, 0.5));
EXPECT_EQ(result.right_sum, GradientPairPrecise(1.5, 1.0));
}
TEST(GpuHist, EvaluateSingleSplitEmpty) {
@@ -130,7 +130,7 @@ TEST(GpuHist, EvaluateSingleSplitEmpty) {
// Feature 0 has a better split, but the algorithm must select feature 1
TEST(GpuHist, EvaluateSingleSplitFeatureSampling) {
thrust::device_vector<DeviceSplitCandidate> out_splits(1);
GradientPair parent_sum(0.0, 1.0);
GradientPairPrecise parent_sum(0.0, 1.0);
TrainParam tparam = ZeroParam();
tparam.UpdateAllowUnknown(Args{});
GPUTrainingParam param{tparam};
@@ -164,14 +164,14 @@ TEST(GpuHist, EvaluateSingleSplitFeatureSampling) {
DeviceSplitCandidate result = out_splits[0];
EXPECT_EQ(result.findex, 1);
EXPECT_EQ(result.fvalue, 11.0);
EXPECT_EQ(result.left_sum, GradientPair(-0.5, 0.5));
EXPECT_EQ(result.right_sum, GradientPair(0.5, 0.5));
EXPECT_EQ(result.left_sum, GradientPairPrecise(-0.5, 0.5));
EXPECT_EQ(result.right_sum, GradientPairPrecise(0.5, 0.5));
}
// Features 0 and 1 have identical gain, the algorithm must select 0
TEST(GpuHist, EvaluateSingleSplitBreakTies) {
thrust::device_vector<DeviceSplitCandidate> out_splits(1);
GradientPair parent_sum(0.0, 1.0);
GradientPairPrecise parent_sum(0.0, 1.0);
TrainParam tparam = ZeroParam();
tparam.UpdateAllowUnknown(Args{});
GPUTrainingParam param{tparam};
@@ -209,7 +209,7 @@ TEST(GpuHist, EvaluateSingleSplitBreakTies) {
TEST(GpuHist, EvaluateSplits) {
thrust::device_vector<DeviceSplitCandidate> out_splits(2);
GradientPair parent_sum(0.0, 1.0);
GradientPairPrecise parent_sum(0.0, 1.0);
TrainParam tparam = ZeroParam();
tparam.UpdateAllowUnknown(Args{});
GPUTrainingParam param{tparam};