Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

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

Browse Source
This commit is contained in:
Jiaming Yuan 2022-10-10 16:12:37 +08:00 committed by GitHub
parent a71421e825
commit e1f9f80df2
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 13 additions and 11 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

24
tests/python-gpu/test_device_quantile_dmatrix.py
View File

@ -1,13 +1,14 @@
import numpy as np
import xgboost as xgb
import pytest
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")
import testing as tm
import test_quantile_dmatrix as tqd
import testing as tm
class TestDeviceQuantileDMatrix:
@ -107,9 +108,8 @@ class TestDeviceQuantileDMatrix:
@settings(print_blob=True, deadline=None)
def test_to_csr(self, n_samples, n_features, sparsity) -> None:
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)
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.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(
booster.predict(d_m),
booster.predict(xgb.DMatrix(d_m.get_data())),
atol=1e-6
atol=1e-6,
)