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Test QDM with sparse data on CPU. (#9316)

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Jiaming Yuan 2023-06-19 21:27:03 +08:00 committed by GitHub
parent ee6809e642
commit 6d22ea793c
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1 changed files with 6 additions and 3 deletions
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tests/python/test_quantile_dmatrix.py
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@ -253,9 +253,12 @@ class TestQuantileDMatrix:
self.run_ref_dmatrix(rng, "hist", True) self.run_ref_dmatrix(rng, "hist", True)
self.run_ref_dmatrix(rng, "hist", False) self.run_ref_dmatrix(rng, "hist", False)
def test_predict(self) -> None: @pytest.mark.parametrize("sparsity", [0.0, 0.5])
n_samples, n_features = 16, 2 def test_predict(self, sparsity: float) -> None:
X, y = make_categorical(n_samples, n_features, n_categories=13, onehot=False) n_samples, n_features = 256, 4
X, y = make_categorical(
n_samples, n_features, n_categories=13, onehot=False, sparsity=sparsity
)
Xy = xgb.DMatrix(X, y, enable_categorical=True) Xy = xgb.DMatrix(X, y, enable_categorical=True)
booster = xgb.train({"tree_method": "hist"}, Xy) booster = xgb.train({"tree_method": "hist"}, Xy)