import torch
import torchvision
from torch import nn
def create_effnetb2_feature_extractor(num_classes: int, seed:int=42):
  weights = torchvision.models.EfficientNet_B2_Weights.DEFAULT
  transforms = weights.transforms()
  model = torchvision.models.efficientnet_b2(weights=weights)
  
  for param in model.parameters():
    param.requires_grad = False

  model.classifier = nn.Sequential(
      nn.Dropout(p=0.3, inplace=True),
      nn.Linear(in_features=1408, out_features=num_classes, bias = True)
  )
  return model, transforms