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Move num_parallel_tree to model parameter. (#7751)

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The size of forest should be a property of model itself instead of a training
hyper-parameter.
This commit is contained in:
Jiaming Yuan
2022-03-29 02:32:42 +08:00
committed by GitHub
parent 8b3ecfca25
commit 3c9b04460a
11 changed files with 158 additions and 101 deletions
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4
tests/python/test_with_dask.py
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@@ -530,7 +530,7 @@ def test_dask_regressor(model: str, client: "Client") -> None:
forest = int(
json.loads(regressor.get_booster().save_config())["learner"][
"gradient_booster"
]["gbtree_train_param"]["num_parallel_tree"]
]["gbtree_model_param"]["num_parallel_tree"]
)
if model == "boosting":
@@ -584,7 +584,7 @@ def run_dask_classifier(
assert n_threads != 0 and n_threads != os.cpu_count()
forest = int(
config["learner"]["gradient_booster"]["gbtree_train_param"]["num_parallel_tree"]
config["learner"]["gradient_booster"]["gbtree_model_param"]["num_parallel_tree"]
)
if model == "boosting":
assert len(history["validation_0"][metric]) == 2