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Use gpu predictor for get csr test. (#8323)

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Jiaming Yuan 2022-10-10 16:12:37 +08:00 committed by GitHub
parent a71421e825
commit e1f9f80df2
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1 changed files with 13 additions and 11 deletions
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24
tests/python-gpu/test_device_quantile_dmatrix.py
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@ -1,13 +1,14 @@
import numpy as np
import xgboost as xgb
import pytest
import sys import sys
from hypothesis import given, strategies, settings
from scipy import sparse import numpy as np
import pytest
from hypothesis import given, settings, strategies
import xgboost as xgb
sys.path.append("tests/python") sys.path.append("tests/python")
import testing as tm
import test_quantile_dmatrix as tqd import test_quantile_dmatrix as tqd
import testing as tm
class TestDeviceQuantileDMatrix: class TestDeviceQuantileDMatrix:
@ -107,9 +108,8 @@ class TestDeviceQuantileDMatrix:
@settings(print_blob=True, deadline=None) @settings(print_blob=True, deadline=None)
def test_to_csr(self, n_samples, n_features, sparsity) -> None: def test_to_csr(self, n_samples, n_features, sparsity) -> None:
import cupy as cp import cupy as cp
X, y = tm.make_sparse_regression(
n_samples, n_features, sparsity, False X, y = tm.make_sparse_regression(n_samples, n_features, sparsity, False)
)
h_X = X.astype(np.float32) h_X = X.astype(np.float32)
csr = h_X csr = h_X
@ -130,10 +130,12 @@ class TestDeviceQuantileDMatrix:
np.testing.assert_equal(h_ret.indptr, d_ret.indptr) np.testing.assert_equal(h_ret.indptr, d_ret.indptr)
np.testing.assert_equal(h_ret.indices, d_ret.indices) np.testing.assert_equal(h_ret.indices, d_ret.indices)
booster = xgb.train({"tree_method": "gpu_hist"}, dtrain=d_m) booster = xgb.train(
{"tree_method": "gpu_hist", "predictor": "gpu_predictor"}, dtrain=d_m
)
np.testing.assert_allclose( np.testing.assert_allclose(
booster.predict(d_m), booster.predict(d_m),
booster.predict(xgb.DMatrix(d_m.get_data())), booster.predict(xgb.DMatrix(d_m.get_data())),
atol=1e-6 atol=1e-6,
) )