model.py

import torch
import torchvision
from torch import nn

def create_efficientnet(output_shape: int):
  weights = torchvision.models.EfficientNet_V2_L_Weights.IMAGENET1K_V1.DEFAULT
  model = torchvision.models.efficientnet_v2_l(weights=weights)

  for param in model.parameters():
    param.requires_grad = False

  model.classifier = nn.Sequential(
      nn.Dropout(p=0.10, inplace=True),
      nn.Linear(in_features=1280, out_features=output_shape)
  )

  return model, weights.transforms()