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import torch
import torchvision
from torch import nn
def create_densenet_model(
num_classes: int=3,
seed: int=42):
weights = torchvision.models.EfficientNet_V2_S_Weights.DEFAULT
model = torchvision.models.efficientnet_v2_s(weights=weights).to("cpu")
auto_transform = weights.transforms()
for params in model.parameters():
params.requires_grad = False
model.classifier = nn.Sequential(
nn.Dropout(p=0.3,inplace=True),
nn.Linear(1280,3)
)
return model, auto_transform
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