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JSON configuration IO. (#5111)

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* Add saving/loading JSON configuration.
* Implement Python pickle interface with new IO routines.
* Basic tests for training continuation.
This commit is contained in:
Jiaming Yuan
2019-12-15 17:31:53 +08:00
committed by GitHub
parent 5aa007d7b2
commit 3136185bc5
24 changed files with 761 additions and 390 deletions
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25
tests/python-gpu/test_gpu_training_continuation.py
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@@ -7,23 +7,25 @@ rng = np.random.RandomState(1994)
class TestGPUTrainingContinuation(unittest.TestCase):
def test_training_continuation_binary(self):
kRows = 32
kCols = 16
def run_training_continuation(self, use_json):
kRows = 64
kCols = 32
X = np.random.randn(kRows, kCols)
y = np.random.randn(kRows)
dtrain = xgb.DMatrix(X, y)
params = {'tree_method': 'gpu_hist', 'max_depth': '2'}
bst_0 = xgb.train(params, dtrain, num_boost_round=4)
params = {'tree_method': 'gpu_hist', 'max_depth': '2',
'gamma': '0.1', 'alpha': '0.01',
'enable_experimental_json_serialization': use_json}
bst_0 = xgb.train(params, dtrain, num_boost_round=64)
dump_0 = bst_0.get_dump(dump_format='json')
bst_1 = xgb.train(params, dtrain, num_boost_round=2)
bst_1 = xgb.train(params, dtrain, num_boost_round=2, xgb_model=bst_1)
bst_1 = xgb.train(params, dtrain, num_boost_round=32)
bst_1 = xgb.train(params, dtrain, num_boost_round=32, xgb_model=bst_1)
dump_1 = bst_1.get_dump(dump_format='json')
def recursive_compare(obj_0, obj_1):
if isinstance(obj_0, float):
assert np.isclose(obj_0, obj_1)
assert np.isclose(obj_0, obj_1, atol=1e-6)
elif isinstance(obj_0, str):
assert obj_0 == obj_1
elif isinstance(obj_0, int):
@@ -42,7 +44,14 @@ class TestGPUTrainingContinuation(unittest.TestCase):
for i in range(len(obj_0)):
recursive_compare(obj_0[i], obj_1[i])
assert len(dump_0) == len(dump_1)
for i in range(len(dump_0)):
obj_0 = json.loads(dump_0[i])
obj_1 = json.loads(dump_1[i])
recursive_compare(obj_0, obj_1)
def test_gpu_training_continuation_binary(self):
self.run_training_continuation(False)
def test_gpu_training_continuation_json(self):
self.run_training_continuation(True)