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a434b46 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | import torch.nn as nn
from torchvision.models import efficientnet_v2_s, EfficientNet_V2_S_Weights
class EfficientNetAuthModel(nn.Module):
"""
Outputs P(AI-generated)
"""
def __init__(self):
super().__init__()
weights = EfficientNet_V2_S_Weights.IMAGENET1K_V1
self.model = efficientnet_v2_s(weights=weights)
# Freeze all parameters first
for p in self.model.parameters():
p.requires_grad = False
# Unfreeze last 2 feature blocks for fine-tuning
for block in self.model.features[-2:]:
for p in block.parameters():
p.requires_grad = True
in_f = self.model.classifier[1].in_features
self.model.classifier = nn.Sequential(
nn.Linear(in_f, 512),
nn.ReLU(),
nn.Dropout(0.3),
nn.Linear(512, 256),
nn.ReLU(),
nn.Dropout(0.2),
nn.Linear(256, 1),
nn.Sigmoid()
)
def forward(self, x):
return self.model(x)
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