import torch
import torchvision

from torch import nn


def create_mobilenetv2_model(num_classes:int=5, 
                          seed:int=42):
    
    model=torch.load('model.pth')
    model.to(device)

    # 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 = nn.Sequential(
        nn.Dropout(p=0.3, inplace=True),
        nn.Linear(in_features=1408, out_features=num_classes),
    )
    
    return model, transforms # Assuming 'transforms' is defined somewhere