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Optimize dart inplace predict perf. (#6804)

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This commit is contained in:
Jiaming Yuan
2021-03-31 15:20:54 +08:00
committed by GitHub
parent 4aa12e10c0
commit 79b8b560d2
3 changed files with 82 additions and 32 deletions
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37
tests/python-gpu/test_gpu_prediction.py
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@@ -332,27 +332,44 @@ class TestGPUPredict:
rmse = mean_squared_error(y_true=y, y_pred=pred, squared=False)
np.testing.assert_almost_equal(rmse, eval_history['train']['rmse'][-1], decimal=5)
def test_predict_dart(self):
@pytest.mark.parametrize("n_classes", [2, 3])
def test_predict_dart(self, n_classes):
from sklearn.datasets import make_classification
import cupy as cp
rng = cp.random.RandomState(1994)
n_samples = 1000
X = rng.randn(n_samples, 10)
y = rng.randn(n_samples)
X_, y_ = make_classification(
n_samples=n_samples, n_informative=5, n_classes=n_classes
)
X, y = cp.array(X_), cp.array(y_)
Xy = xgb.DMatrix(X, y)
booster = xgb.train(
{
if n_classes == 2:
params = {
"tree_method": "gpu_hist",
"booster": "dart",
"rate_drop": 0.5,
},
Xy,
num_boost_round=32
)
"objective": "binary:logistic"
}
else:
params = {
"tree_method": "gpu_hist",
"booster": "dart",
"rate_drop": 0.5,
"objective": "multi:softprob",
"num_class": n_classes
}
booster = xgb.train(params, Xy, num_boost_round=32)
# predictor=auto
inplace = booster.inplace_predict(X)
copied = booster.predict(Xy)
cpu_inplace = booster.inplace_predict(X_)
booster.set_param({"predictor": "cpu_predictor"})
cpu_copied = booster.predict(Xy)
copied = cp.array(copied)
cp.testing.assert_allclose(cpu_inplace, copied, atol=1e-6)
cp.testing.assert_allclose(cpu_copied, copied, atol=1e-6)
cp.testing.assert_allclose(inplace, copied, atol=1e-6)
booster.set_param({"predictor": "gpu_predictor"})