code: def __init__(
      self, milestones: tuple = (5, 10), train_bn: bool = False
  ):
      super().__init__()
      self.milestones = milestones
      self.train_bn = train_bn
  
imports: import logging
  from pathlib import Path
  from typing import Union
  import torch
  import torch.nn.functional
  from lightning.pytorch import LightningDataModule, LightningModule, cli_lightning_logo
  from lightning.pytorch.callbacks.finetuning import BaseFinetuning
  from lightning.pytorch.cli import LightningCLI
  from lightning.pytorch.utilities import rank_zero_info
  from lightning.pytorch.utilities.model_helpers import get_torchvision_model
  from torch import nn, optim
  from torch.optim.lr_scheduler import MultiStepLR
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
  from torchmetrics import Accuracy
  from torchvision import transforms
  from torchvision.datasets import ImageFolder
  from torchvision.datasets.utils import download_and_extract_archive
label_desc: Use image node_id 1 to create a new MilestonesFinetuning object from inherited base classes: BaseFinetuning with example: obj = MilestonesFinetuning(milestones, train_bn)