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Fix GPU RF #6755

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merged 3 commits into from
Mar 16, 2021
Merged

Fix GPU RF #6755

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5d18b90
Fix sampling.
trivialfis Mar 16, 2021
a7146a1
Test.
trivialfis Mar 16, 2021
e0e5201
Fix test.
trivialfis Mar 16, 2021
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9 changes: 8 additions & 1 deletion src/tree/updater_gpu_hist.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -169,6 +169,7 @@ struct GPUHistMakerDevice {
std::unique_ptr<RowPartitioner> row_partitioner;
DeviceHistogram<GradientSumT> hist{};

dh::caching_device_vector<GradientPair> d_gpair; // storage for gpair;
common::Span<GradientPair> gpair;

dh::caching_device_vector<int> monotone_constraints;
Expand Down Expand Up @@ -269,7 +270,13 @@ struct GPUHistMakerDevice {
std::fill(node_sum_gradients.begin(), node_sum_gradients.end(),
GradientPair());

auto sample = sampler->Sample(dh_gpair->DeviceSpan(), dmat);
if (d_gpair.size() != dh_gpair->Size()) {
d_gpair.resize(dh_gpair->Size());
}
thrust::copy(thrust::device, dh_gpair->ConstDevicePointer(),
dh_gpair->ConstDevicePointer() + dh_gpair->Size(),
d_gpair.begin());
auto sample = sampler->Sample(dh::ToSpan(d_gpair), dmat);
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@hcho3 hcho3 Mar 16, 2021 •
edited

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We have to make a copy here since Sample() is expected to modify the incoming gpair parameter? Mutating gpairs would be bad when we fit multiple trees in a single round, and this fix would make sense.

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modify the incoming gpair parameter?

Yes.

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Thanks guys!

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Fix confirmed. Thanks.

page = sample.page;
gpair = sample.gpair;

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5 changes: 4 additions & 1 deletion tests/cpp/tree/test_gpu_hist.cu
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Expand Up @@ -503,12 +503,15 @@ TEST(GpuHist, ExternalMemoryWithSampling) {
auto gpair = GenerateRandomGradients(kRows);

// Build a tree using the in-memory DMatrix.
auto rng = common::GlobalRandom();

RegTree tree;
HostDeviceVector<bst_float> preds(kRows, 0.0, 0);
UpdateTree(&gpair, dmat.get(), 0, &tree, &preds, kSubsample, kSamplingMethod,
kRows);

// Build another tree using multiple ELLPACK pages.
common::GlobalRandom() = rng;
RegTree tree_ext;
HostDeviceVector<bst_float> preds_ext(kRows, 0.0, 0);
UpdateTree(&gpair, dmat_ext.get(), kPageSize, &tree_ext, &preds_ext,
Expand All @@ -518,7 +521,7 @@ TEST(GpuHist, ExternalMemoryWithSampling) {
auto preds_h = preds.ConstHostVector();
auto preds_ext_h = preds_ext.ConstHostVector();
for (int i = 0; i < kRows; i++) {
EXPECT_NEAR(preds_h[i], preds_ext_h[i], 2e-3);
EXPECT_NEAR(preds_h[i], preds_ext_h[i], 1e-3);
}
}

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6 changes: 5 additions & 1 deletion tests/python-gpu/test_gpu_with_sklearn.py
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Expand Up @@ -33,4 +33,8 @@ def test_gpu_binary_classification():


def test_boost_from_prediction_gpu_hist():
cpu_test = twskl.run_boost_from_prediction('gpu_hist')
twskl.run_boost_from_prediction('gpu_hist')


def test_num_parallel_tree():
twskl.run_boston_housing_rf_regression("gpu_hist")
15 changes: 9 additions & 6 deletions tests/python/test_with_sklearn.py
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Expand Up @@ -357,23 +357,26 @@ def test_boston_housing_regression():
assert mean_squared_error(preds4, labels) < 350


def test_boston_housing_rf_regression():
def run_boston_housing_rf_regression(tree_method):
from sklearn.metrics import mean_squared_error
from sklearn.datasets import load_boston
from sklearn.model_selection import KFold

boston = load_boston()
y = boston['target']
X = boston['data']
X, y = load_boston(return_X_y=True)
kf = KFold(n_splits=2, shuffle=True, random_state=rng)
for train_index, test_index in kf.split(X, y):
xgb_model = xgb.XGBRFRegressor(random_state=42).fit(
X[train_index], y[train_index])
xgb_model = xgb.XGBRFRegressor(random_state=42, tree_method=tree_method).fit(
X[train_index], y[train_index]
)
preds = xgb_model.predict(X[test_index])
labels = y[test_index]
assert mean_squared_error(preds, labels) < 35


def test_boston_housing_rf_regression():
run_boston_housing_rf_regression("hist")


def test_parameter_tuning():
from sklearn.model_selection import GridSearchCV
from sklearn.datasets import load_boston
Expand Down