Add test for eta and mitigate float error. (#7446)
* Add eta test. * Don't skip test.
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@@ -149,6 +149,7 @@ void TestLearnerSerialization(Args args, FeatureMap const& fmap, std::shared_ptr
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Json m_0 = Json::Load(StringView{continued_model.c_str(), continued_model.size()});
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Json m_1 = Json::Load(StringView{model_at_2kiter.c_str(), model_at_2kiter.size()});
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CompareJSON(m_0, m_1);
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}
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@@ -610,7 +611,6 @@ TEST_F(MultiClassesSerializationTest, CPUCoordDescent) {
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#if defined(XGBOOST_USE_CUDA)
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TEST_F(MultiClassesSerializationTest, GpuHist) {
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GTEST_SKIP() << "This test is broken for CUDA 11.0 + Windows combination, skipping";
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TestLearnerSerialization({{"booster", "gbtree"},
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{"num_class", std::to_string(kClasses)},
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{"seed", "0"},
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@@ -620,6 +620,9 @@ TEST_F(MultiClassesSerializationTest, GpuHist) {
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// different result (1e-7) with CPU predictor for some
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// entries.
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{"predictor", "gpu_predictor"},
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// Mitigate the difference caused by hardware fused multiply
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// add to tree weight during update prediction cache.
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{"learning_rate", "1.0"},
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{"tree_method", "gpu_hist"}},
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fmap_, p_dmat_);
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@@ -630,7 +633,8 @@ TEST_F(MultiClassesSerializationTest, GpuHist) {
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{"max_depth", std::to_string(kClasses)},
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// GPU_Hist has higher floating point error. 1e-6 doesn't work
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// after num_parallel_tree goes to 4
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{"num_parallel_tree", "3"},
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{"num_parallel_tree", "4"},
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{"learning_rate", "1.0"},
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{"tree_method", "gpu_hist"}},
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fmap_, p_dmat_);
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@@ -638,6 +642,7 @@ TEST_F(MultiClassesSerializationTest, GpuHist) {
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{"num_class", std::to_string(kClasses)},
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{"seed", "0"},
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{"nthread", "1"},
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{"learning_rate", "1.0"},
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{"max_depth", std::to_string(kClasses)},
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{"tree_method", "gpu_hist"}},
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fmap_, p_dmat_);
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