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Fix bugs related to lightning 2.6.0 and transformer 5.0.0 #28

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Merged
chcwww merged 6 commits into from
Feb 15, 2026
Merged

Fix bugs related to lightning 2.6.0 and transformer 5.0.0 #28

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7b609c8
Merge branch 'master' of github.com:chcwww/LibMultiLabel
chcwww Feb 12, 2026
65bb7b0
start fixing the workflow
chcwww Feb 12, 2026
5557a6a
set weights_only to False
chcwww Feb 12, 2026
ae94b8b
remove torchscript
chcwww Feb 12, 2026
d831cdb
remove another torchscript
chcwww Feb 12, 2026
2e9719f
remove "torchscript=True" since it is no longer supported by "AutoMod…
chcwww Feb 13, 2026
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4 changes: 3 additions & 1 deletion libmultilabel/nn/attentionxml.py
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Original file line number Diff line number Diff line change
Expand Up @@ -287,7 +287,7 @@ def fit(self, datasets):
logger.info(f"Finish training level 0")

logger.info(f"Best model loaded from {best_model_path}")
model_0 = Model.load_from_checkpoint(best_model_path)
model_0 = Model.load_from_checkpoint(best_model_path, weights_only=False)

logger.info(
f"Predicting clusters by level-0 model. We then select {self.beam_width} clusters for each instance and "
Expand Down Expand Up @@ -422,11 +422,13 @@ def test(self, dataset):
model_0 = Model.load_from_checkpoint(
self.get_best_model_path(level=0),
save_k_predictions=self.beam_width,
weights_only=False,
)
model_1 = PLTModel.load_from_checkpoint(
self.get_best_model_path(level=1),
save_k_predictions=self.save_k_predictions,
metrics=self.metrics,
weights_only=False,
)

word_dict_path = os.path.join(os.path.dirname(self.get_best_model_path(level=1)), self.WORD_DICT_NAME)
Expand Down
1 change: 0 additions & 1 deletion libmultilabel/nn/networks/bert.py
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Expand Up @@ -34,7 +34,6 @@ def __init__(
hidden_dropout_prob=encoder_hidden_dropout,
attention_probs_dropout_prob=encoder_attention_dropout,
classifier_dropout=post_encoder_dropout,
torchscript=True,
)

def forward(self, input):
Expand Down
1 change: 0 additions & 1 deletion libmultilabel/nn/networks/bert_attention.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,6 @@ def __init__(

self.lm = AutoModel.from_pretrained(
lm_weight,
torchscript=True,
hidden_dropout_prob=encoder_hidden_dropout,
attention_probs_dropout_prob=encoder_attention_dropout,
)
Expand Down
2 changes: 1 addition & 1 deletion torch_trainer.py
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Expand Up @@ -150,7 +150,7 @@ def _setup_model(

if checkpoint_path is not None:
logging.info(f"Loading model from `{checkpoint_path}` with the previously saved hyper-parameter...")
self.model = Model.load_from_checkpoint(checkpoint_path, log_path=log_path)
self.model = Model.load_from_checkpoint(checkpoint_path, log_path=log_path, weights_only=False)
word_dict_path = os.path.join(os.path.dirname(checkpoint_path), self.WORD_DICT_NAME)
if os.path.exists(word_dict_path):
with open(word_dict_path, "rb") as f:
Expand Down