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Code Activity

fix(gbdt): correct dtrain assignment in finetune() to use Dataset instead of tuple (#2049)

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Linlang
2025-11-13 11:50:43 +08:00
committed by GitHub
parent ac3fe9476f
commit 2b41782f0c
1 changed files with 5 additions and 3 deletions
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8
qlib/contrib/model/gbdt.py
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@@ -51,7 +51,7 @@ class LGBModel(ModelFT, LightGBMFInt):
w = reweighter.reweight(df) w = reweighter.reweight(df)
else: else:
raise ValueError("Unsupported reweighter type.") raise ValueError("Unsupported reweighter type.")
ds_l.append((lgb.Dataset(x.values, label=y, weight=w), key)) ds_l.append((lgb.Dataset(x.values, label=y, weight=w, free_raw_data=False), key))
return ds_l return ds_l
def fit( def fit(
@@ -109,8 +109,10 @@ class LGBModel(ModelFT, LightGBMFInt):
verbose level verbose level
""" """
# Based on existing model and finetune by train more rounds # Based on existing model and finetune by train more rounds
dtrain, _ = self._prepare_data(dataset, reweighter) # pylint: disable=W0632 ds_l = self._prepare_data(dataset, reweighter)
if dtrain.empty: dtrain, _ = ds_l[0]
if dtrain.construct().num_data() == 0:
raise ValueError("Empty data from dataset, please check your dataset config.") raise ValueError("Empty data from dataset, please check your dataset config.")
verbose_eval_callback = lgb.log_evaluation(period=verbose_eval) verbose_eval_callback = lgb.log_evaluation(period=verbose_eval)
self.model = lgb.train( self.model = lgb.train(