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import torch
import torchvision
from torch import nn
def create_effnetb2_model(num_classes: int):
"""Creates an EfficientNetB2 model."""
# Create model and transforms
weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
transforms = weights.transforms()
model = torchvision.models.efficientnet_b2(weights=weights)
# Freeze layers
for param in model.parameters():
param.requires_grad = False
# Change classifier
model.classifier = nn.Sequential(
nn.Dropout(p=0.3, inplace=True),
nn.Linear(in_features=1408, out_features=num_classes)
)
return model, transforms
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