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Refactor improve codes for ranker (#8936)

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### What problem does this PR solve?
Use the normalize method directly

### Type of change

- [x] Refactoring
This commit is contained in:
Stephen Hu
2025-07-21 10:22:20 +08:00
committed by GitHub
parent fca9203f18
commit 46caf6ae72
1 changed files with 2 additions and 8 deletions
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10
rag/llm/rerank_model.py
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@ -32,11 +32,6 @@ from api.utils.file_utils import get_home_cache_dir
from api.utils.log_utils import log_exception from api.utils.log_utils import log_exception
from rag.utils import num_tokens_from_string, truncate from rag.utils import num_tokens_from_string, truncate
def sigmoid(x):
return 1 / (1 + np.exp(-x))
class Base(ABC): class Base(ABC):
def __init__(self, key, model_name): def __init__(self, key, model_name):
pass pass
@ -133,10 +128,9 @@ class DefaultRerank(Base):
def _compute_batch_scores(self, batch_pairs, max_length=None): def _compute_batch_scores(self, batch_pairs, max_length=None):
if max_length is None: if max_length is None:
scores = self._model.compute_score(batch_pairs) scores = self._model.compute_score(batch_pairs, normalize=True)
else: else:
scores = self._model.compute_score(batch_pairs, max_length=max_length) scores = self._model.compute_score(batch_pairs, max_length=max_length, normalize=True)
scores = sigmoid(np.array(scores))
if not isinstance(scores, Iterable): if not isinstance(scores, Iterable):
scores = [scores] scores = [scores]
return scores return scores