model.py

import gradio as gr 
import torch 
import os 
from timeit import default_timer as timer  # Fixed: default_repeat -> default_timer
from typing import List, Tuple, Dict
import torchvision 
from torch import nn 
def create_effnetb2_model(num_classes:int=3,
                          seed:int=42):
    # 1,2,3 Create EffnetB2 pretrained weights,transforms and model 
    weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
    transforms = weights.transforms()
    model = torchvision.models.efficientnet_b2(weights=weights)


    # 4. Freeze
    for params in model.parameters():
        params.requires_grad=False

    # Change Classifier head wih 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