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dadf189 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | from __future__ import annotations
import torch
import torch.nn as nn
class ScoreAggregator(nn.Module):
"""Aggregate concept vector into scalar score in [0, 100]."""
def __init__(self, k: int = 6):
super().__init__()
self.mlp = nn.Sequential(
nn.Linear(k, 32),
nn.GELU(),
nn.Linear(32, 1),
nn.Sigmoid(),
)
def forward(self, concepts: torch.Tensor) -> torch.Tensor:
return self.mlp(concepts) * 100.0
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