model.py

import torch
import torchvision

from torch import nn


def create_effnetb0_model(num_classes: int = 3, seed: int = 42):
    """Creates an EfficientNetB0 Model and Transforms"""
    # 1. Setup Weights
    weights = torchvision.models.EfficientNet_B0_Weights.DEFAULT

    # 2. Get transforms
    transforms = weights.transforms()

    # 3. Setup pretrained model
    model = torchvision.models.efficientnet_b0(weights=weights)

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

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

    model.classifier = nn.Sequential(
        nn.Dropout(p=0.2, inplace=True),
        nn.Linear(in_features=1280, out_features=num_classes, bias=True),
    )

    return model, transforms