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Fix token_lengths kwarg leaking into the labels encoder #372

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Merged
Ingvarstep merged 1 commit into from
Jul 6, 2026
Merged

Fix token_lengths kwarg leaking into the labels encoder #372

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9 changes: 7 additions & 2 deletions gliner/modeling/encoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -943,15 +943,20 @@ def encode_labels(
input_ids: Label token IDs of shape (batch_size, seq_len).
attention_mask: Attention mask of shape (batch_size, seq_len).
*args: Additional positional arguments.
**kwargs: Additional keyword arguments (packing_config and pair_attention_mask
are removed as they're not supported for labels).
**kwargs: Additional keyword arguments (packing_config, pair_attention_mask
and token_lengths are removed as they're not supported for labels).

Returns:
Pooled label embeddings of shape (batch_size, hidden_size).
"""
label_kwargs = dict(kwargs)
label_kwargs.pop("packing_config", None)
label_kwargs.pop("pair_attention_mask", None)
# token_lengths carries precomputed lengths for the *text* inputs (see
# collator); forwarding it to the labels encoder crashes plain HF
# backbones ("BertModel.forward() got an unexpected keyword argument
# 'token_lengths'", #370).
label_kwargs.pop("token_lengths", None)
label_kwargs["attention_mask"] = attention_mask
labels_embeddings = self.labels_encoder(input_ids, *args, **label_kwargs)
if hasattr(self, "labels_projection"):
Expand Down