model.py

import torch
import torchvision

from torch import nn

def create_efficientb2_model(
    num_classes: int=4,
    seed: int=42):
  
  weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
  model = torchvision.models.efficientnet_b2(weights=weights)
  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(1408,num_classes)
  )

  return model, auto_transform