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Update normalized_scorer.py

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Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
Signed-off-by: weichen <calvin_zhu0210@outlook.com>
This commit is contained in:
Pr0Wh1teGivee 2025-12-04 10:19:36 +08:00 committed by weichen
parent b04f678659
commit ed2a808252
1 changed files with 8 additions and 9 deletions
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17
vllm/v1/core/sched/policy/normalized_scorer.py
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@ -27,7 +27,8 @@ class ScoreDim:
class NormalizedScorer:
"""
Normalize unbounded N-dimensional values into a composite score using the Sigmoid function.
Normalize unbounded N-dimensional values into a composite score using the Sigmoid
function.
"""
def __init__(self, dim_list: list[ScoreDim]) -> None:
@ -48,7 +49,9 @@ class NormalizedScorer:
@staticmethod
def _inv_sigmoid_normalize(value, median, norm_scale):
"""Inverse Sigmoid: Used for dimensions where a larger value yields a lower score."""
"""Inverse Sigmoid: Used for dimensions where a larger value yields a lower
score.
"""
# Equivalent to sigmoid(-x), but more numerically stable.
return 1 / (1 + math.exp(norm_scale * (value - median)))
@ -74,12 +77,7 @@ class NormalizedScorer:
score = self._sigmoid_normalize(
dim_value, dim_info.median, dim_info.norm_scale
)
logger.debug(
"%s(%s) : %.10f",
dim_info.name,
dim_info.reverse,
score
)
logger.debug("%s(%s) : %.10f", dim_info.name, dim_info.reverse, score)
# Weighted summation.
final_score += score * dim_info.weight
@ -88,7 +86,8 @@ class NormalizedScorer:
class TimeAndLengthScorer(NormalizedScorer):
"""
Scorer for time and length dimensions; defaults to forward scoring with equal weights (0.5 each).
Scorer for time and length dimensions; defaults to forward scoring with equal
weights (0.5 each).
"""
def __init__(