model.py

import torch
import torchvision

from torch import nn


def create_densenet121_model(num_classes:int=3,
                          seed:int=42):
    # Create DenseNet121 pretrained weights, transforms and model
    weights = torchvision.models.DenseNet121_Weights.DEFAULT 
    transforms = weights.transforms()
    model = torchvision.models.densenet121(weights=weights)

    # Freeze all layers in base model
    for param in model.parameters():
        param.requires_grad = False

    # Change classifier head with random seed for reproducibility
    torch.manual_seed(seed)

    model.classifier = torch.nn.Sequential(
    torch.nn.Dropout(p=0.2, inplace=True),
    torch.nn.Linear(in_features=1024,
                    out_features=3,
                    bias=True))

    return model, transforms