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fixed super.init in SentenceTransformerPatched #617

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fixed super.init in SentenceTransformerPatched #617

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7 changes: 4 additions & 3 deletions libs/infinity_emb/infinity_emb/transformer/embedder/sentence_transformer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -69,13 +69,14 @@ def __init__(self, *, engine_args=EngineArgs):
if ls.loading_dtype is not None:
model_kwargs["torch_dtype"] = ls.loading_dtype

super().__init__(
engine_args.model_name_or_path,
temp_model = SentenceTransformer(**dict(
model_name_or_path=engine_args.model_name_or_path,
revision=engine_args.revision,
trust_remote_code=engine_args.trust_remote_code,
device=ls.device_placement,
model_kwargs=model_kwargs,
)
))
self.__dict__.update(temp_model.__dict__)
self.to(ls.device_placement)
Comment on lines +72 to 80
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@greptile-apps greptile-apps bot Jul 10, 2025

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style: This pattern of creating a temp instance and copying state bypasses normal inheritance. Consider adding comment explaining why dictionary update is safer than inheritance here

Suggested change
temp_model = SentenceTransformer(**dict(
model_name_or_path=engine_args.model_name_or_path,
revision=engine_args.revision,
trust_remote_code=engine_args.trust_remote_code,
device=ls.device_placement,
model_kwargs=model_kwargs,
)
))
self.__dict__.update(temp_model.__dict__)
self.to(ls.device_placement)
# Create temporary model instance and copy its state to bypass SentenceTransformer's
# __init__ which doesn't support our extended configuration. This allows us to
# customize initialization while preserving all the model's internal state.
temp_model = SentenceTransformer(**dict(
model_name_or_path=engine_args.model_name_or_path,
revision=engine_args.revision,
trust_remote_code=engine_args.trust_remote_code,
device=ls.device_placement,
model_kwargs=model_kwargs,
))
self.__dict__.update(temp_model.__dict__)
self.to(ls.device_placement)

# make a copy of the tokenizer,
# to be able to could the tokens in another thread
Expand Down