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()