xgboost/tests/python-gpu/load_pickle.py
Jiaming Yuan cf70864fa3
Move Python testing utilities into xgboost module. (#8379)
- Add typehints.
- Fixes for pylint.

Co-authored-by: Hyunsu Philip Cho <chohyu01@cs.washington.edu>
2022-10-26 16:56:11 +08:00

74 lines
2.5 KiB
Python

'''Loading a pickled model generated by test_pickling.py, only used by
`test_gpu_with_dask.py`'''
import json
import os
import numpy as np
import pytest
from test_gpu_pickling import build_dataset, load_pickle, model_path
import xgboost as xgb
from xgboost import testing as tm
class TestLoadPickle:
def test_load_pkl(self):
'''Test whether prediction is correct.'''
assert os.environ['CUDA_VISIBLE_DEVICES'] == '-1'
bst = load_pickle(model_path)
x, y = build_dataset()
if isinstance(bst, xgb.Booster):
test_x = xgb.DMatrix(x)
res = bst.predict(test_x)
else:
res = bst.predict(x)
assert len(res) == 10
bst.set_params(n_jobs=1) # triggers a re-configuration
res = bst.predict(x)
assert len(res) == 10
def test_predictor_type_is_auto(self):
'''Under invalid CUDA_VISIBLE_DEVICES, predictor should be set to
auto'''
assert os.environ['CUDA_VISIBLE_DEVICES'] == '-1'
bst = load_pickle(model_path)
config = bst.save_config()
config = json.loads(config)
assert config['learner']['gradient_booster']['gbtree_train_param'][
'predictor'] == 'auto'
def test_predictor_type_is_gpu(self):
'''When CUDA_VISIBLE_DEVICES is not specified, keep using
`gpu_predictor`'''
assert 'CUDA_VISIBLE_DEVICES' not in os.environ.keys()
bst = load_pickle(model_path)
config = bst.save_config()
config = json.loads(config)
assert config['learner']['gradient_booster']['gbtree_train_param'][
'predictor'] == 'gpu_predictor'
def test_wrap_gpu_id(self):
assert os.environ['CUDA_VISIBLE_DEVICES'] == '0'
bst = load_pickle(model_path)
config = bst.save_config()
config = json.loads(config)
assert config['learner']['generic_param']['gpu_id'] == '0'
x, y = build_dataset()
test_x = xgb.DMatrix(x)
res = bst.predict(test_x)
assert len(res) == 10
def test_training_on_cpu_only_env(self):
assert os.environ['CUDA_VISIBLE_DEVICES'] == '-1'
rng = np.random.RandomState(1994)
X = rng.randn(10, 10)
y = rng.randn(10)
with tm.captured_output() as (out, err):
# Test no thrust exception is thrown
with pytest.raises(xgb.core.XGBoostError):
xgb.train({'tree_method': 'gpu_hist'}, xgb.DMatrix(X, y))
assert out.getvalue().find('No visible GPU is found') != -1