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Fix test_gpu_coordinate. (#3974)

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* Fix test_gpu_coordinate.

* Use `gpu_coord_descent` in test.
* Reduce number of running rounds.

* Remove nthread.

* Use githubusercontent for r-appveyor.

* Use githubusercontent in travis r tests.
This commit is contained in:
Jiaming Yuan
2019-02-20 06:09:10 +08:00
committed by Philip Hyunsu Cho
parent c8c472f39a
commit cecbe0cf71
4 changed files with 31 additions and 21 deletions
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46
tests/python-gpu/test_gpu_linear.py
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@@ -3,31 +3,41 @@ import pytest
import unittest
sys.path.append('tests/python/')
import test_linear
import testing as tm
import test_linear # noqa: E402
import testing as tm # noqa: E402
class TestGPULinear(unittest.TestCase):
datasets = ["Boston", "Digits", "Cancer", "Sparse regression",
"Boston External Memory"]
datasets = ["Boston", "Digits", "Cancer", "Sparse regression"]
common_param = {
'booster': ['gblinear'],
'updater': ['gpu_coord_descent'],
'eta': [0.5],
'top_k': [10],
'tolerance': [1e-5],
'alpha': [.005, .1],
'lambda': [0.005],
'coordinate_selection': ['cyclic', 'random', 'greedy']}
@pytest.mark.skipif(**tm.no_sklearn())
def test_gpu_coordinate(self):
variable_param = {
'booster': ['gblinear'],
'updater': ['coord_descent'],
'eta': [0.5],
'top_k': [10],
'tolerance': [1e-5],
'nthread': [2],
'alpha': [.005, .1],
'lambda': [0.005],
'coordinate_selection': ['cyclic', 'random', 'greedy'],
'n_gpus': [-1]
}
for param in test_linear.parameter_combinations(variable_param):
parameters = self.common_param.copy()
parameters['n_gpus'] = [1]
for param in test_linear.parameter_combinations(parameters):
results = test_linear.run_suite(
param, 200, self.datasets, scale_features=True)
param, 150, self.datasets, scale_features=True)
test_linear.assert_regression_result(results, 1e-2)
test_linear.assert_classification_result(results)
@pytest.mark.mgpu
@pytest.mark.skipif(**tm.no_sklearn())
def test_gpu_coordinate_mgpu(self):
parameters = self.common_param.copy()
parameters['n_gpus'] = [-1]
parameters['gpu_id'] = [1]
for param in test_linear.parameter_combinations(parameters):
results = test_linear.run_suite(
param, 150, self.datasets, scale_features=True)
test_linear.assert_regression_result(results, 1e-2)
test_linear.assert_classification_result(results)