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[ci] prevent train.binary.bin and lgb_train_data.bin files being left behind after testing #6606

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Aug 15, 2024
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[ci] prevent train.binary.bin and lgb_train_data.bin files being left behind after testing #6606

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afa30c0
Implement
bili2002 Aug 13, 2024
e4055ea
Merge branch 'master' into improve-tmp-path
StrikerRUS Aug 14, 2024
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7 changes: 4 additions & 3 deletions tests/c_api_test/test_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -160,7 +160,7 @@ def free_dataset(handle):
LIB.LGBM_DatasetFree(handle)


def test_dataset():
def test_dataset(tmp_path):
binary_example_dir = Path(__file__).absolute().parents[2] / "examples" / "binary_classification"
train = load_from_file(binary_example_dir / "binary.train", None)
test = load_from_mat(binary_example_dir / "binary.test", train)
Expand All @@ -169,9 +169,10 @@ def test_dataset():
free_dataset(test)
test = load_from_csc(binary_example_dir / "binary.test", train)
free_dataset(test)
save_to_binary(train, "train.binary.bin")
train_binary = str(tmp_path / "train.binary.bin")
save_to_binary(train, train_binary)
free_dataset(train)
train = load_from_file("train.binary.bin", None)
train = load_from_file(train_binary, None)
free_dataset(train)


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13 changes: 7 additions & 6 deletions tests/python_package_test/test_engine.py
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Expand Up @@ -2021,7 +2021,7 @@ def train_and_get_predictions(features, labels):
np.testing.assert_allclose(origin_pred, sliced_pred)


def test_init_with_subset(rng):
def test_init_with_subset(tmp_path, rng):
data = rng.uniform(size=(50, 2))
y = [1] * 25 + [0] * 25
lgb_train = lgb.Dataset(data, y, free_raw_data=False)
Expand All @@ -2035,16 +2035,17 @@ def test_init_with_subset(rng):
assert lgb_train.get_data().shape[0] == 50
assert subset_data_1.get_data().shape[0] == 30
assert subset_data_2.get_data().shape[0] == 20
lgb_train.save_binary("lgb_train_data.bin")
lgb_train_from_file = lgb.Dataset("lgb_train_data.bin", free_raw_data=False)
lgb_train_data = str(tmp_path / "lgb_train_data.bin")
lgb_train.save_binary(lgb_train_data)
lgb_train_from_file = lgb.Dataset(lgb_train_data, free_raw_data=False)
subset_data_3 = lgb_train_from_file.subset(subset_index_1)
subset_data_4 = lgb_train_from_file.subset(subset_index_2)
init_gbm_2 = lgb.train(params=params, train_set=subset_data_3, num_boost_round=10, keep_training_booster=True)
with np.testing.assert_raises_regex(lgb.basic.LightGBMError, "Unknown format of training data"):
lgb.train(params=params, train_set=subset_data_4, num_boost_round=10, init_model=init_gbm_2)
assert lgb_train_from_file.get_data() == "lgb_train_data.bin"
assert subset_data_3.get_data() == "lgb_train_data.bin"
assert subset_data_4.get_data() == "lgb_train_data.bin"
assert lgb_train_from_file.get_data() == lgb_train_data
assert subset_data_3.get_data() == lgb_train_data
assert subset_data_4.get_data() == lgb_train_data


def test_training_on_constructed_subset_without_params(rng):
Expand Down
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