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Remove single_precision_histogram for gpu_hist (#7828)

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This commit is contained in:
Rory Mitchell
2022-05-03 14:53:19 +02:00
committed by GitHub
parent 50d854e02e
commit 90cce38236
17 changed files with 97 additions and 155 deletions
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15
tests/cpp/tree/test_gpu_hist.cu
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@@ -277,8 +277,10 @@ void TestHistogramIndexImpl() {
int constexpr kNRows = 1000, kNCols = 10;
// Build 2 matrices and build a histogram maker with that
tree::GPUHistMakerSpecialised<GradientPairPrecise> hist_maker{ObjInfo{ObjInfo::kRegression}},
hist_maker_ext{ObjInfo{ObjInfo::kRegression}};
GenericParameter generic_param(CreateEmptyGenericParam(0));
tree::GPUHistMaker hist_maker{&generic_param,ObjInfo{ObjInfo::kRegression}},
hist_maker_ext{&generic_param,ObjInfo{ObjInfo::kRegression}};
std::unique_ptr<DMatrix> hist_maker_dmat(
CreateSparsePageDMatrixWithRC(kNRows, kNCols, 0, true));
@@ -291,10 +293,9 @@ void TestHistogramIndexImpl() {
{"max_leaves", "0"}
};
GenericParameter generic_param(CreateEmptyGenericParam(0));
hist_maker.Configure(training_params, &generic_param);
hist_maker.Configure(training_params);
hist_maker.InitDataOnce(hist_maker_dmat.get());
hist_maker_ext.Configure(training_params, &generic_param);
hist_maker_ext.Configure(training_params);
hist_maker_ext.InitDataOnce(hist_maker_ext_dmat.get());
// Extract the device maker from the histogram makers and from that its compressed
@@ -346,9 +347,9 @@ void UpdateTree(HostDeviceVector<GradientPair>* gpair, DMatrix* dmat,
{"sampling_method", sampling_method},
};
tree::GPUHistMakerSpecialised<GradientPairPrecise> hist_maker{ObjInfo{ObjInfo::kRegression}};
GenericParameter generic_param(CreateEmptyGenericParam(0));
hist_maker.Configure(args, &generic_param);
tree::GPUHistMaker hist_maker{&generic_param,ObjInfo{ObjInfo::kRegression}};
hist_maker.Configure(args);
std::vector<HostDeviceVector<bst_node_t>> position(1);
hist_maker.Update(gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position}, {tree});

4
tests/python-gpu/test_gpu_basic_models.py
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@@ -16,11 +16,11 @@ class TestGPUBasicModels:
cpu_test_bm = test_bm.TestModels()
def run_cls(self, X, y):
cls = xgb.XGBClassifier(tree_method='gpu_hist', single_precision_histogram=True)
cls = xgb.XGBClassifier(tree_method='gpu_hist')
cls.fit(X, y)
cls.get_booster().save_model('test_deterministic_gpu_hist-0.json')
cls = xgb.XGBClassifier(tree_method='gpu_hist', single_precision_histogram=True)
cls = xgb.XGBClassifier(tree_method='gpu_hist')
cls.fit(X, y)
cls.get_booster().save_model('test_deterministic_gpu_hist-1.json')

1
tests/python-gpu/test_gpu_updaters.py
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@@ -15,7 +15,6 @@ parameter_strategy = strategies.fixed_dictionaries({
'max_leaves': strategies.integers(0, 256),
'max_bin': strategies.integers(2, 1024),
'grow_policy': strategies.sampled_from(['lossguide', 'depthwise']),
'single_precision_histogram': strategies.booleans(),
'min_child_weight': strategies.floats(0.5, 2.0),
'seed': strategies.integers(0, 10),
# We cannot enable subsampling as the training loss can increase