xgboost/tests/python-gpu/load_pickle.py
Jiaming Yuan 61286c6e8f
Fix wrapping GPU ID and prevent data copying. (#5160)
* Removed some data copying.

* Make sure gpu_id is valid before any configuration is carried out.
2019-12-27 16:51:08 +08:00

52 lines
1.8 KiB
Python

'''Loading a pickled model generated by test_pickling.py, only used by
`test_gpu_with_dask.py`'''
import unittest
import os
import xgboost as xgb
import json
from test_gpu_pickling import build_dataset, model_path, load_pickle
class TestLoadPickle(unittest.TestCase):
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()
test_x = xgb.DMatrix(x)
res = bst.predict(test_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