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 numpy
  import torch
  import torch.nn.functional
  from torch import nn, optim
  from torch.optim.lr_scheduler import MultiStepLR
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader, Subset
  from torchmetrics.classification import MulticlassAccuracy
  from torchvision import models, transforms
  from torchvision.datasets import ImageFolder
  from torchvision.datasets.utils import download_and_extract_archive
  from pytorch_lightning import LightningDataModule, LightningModule
  from pytorch_lightning.callbacks.finetuning import BaseFinetuning
  from pytorch_lightning.utilities.rank_zero import rank_zero_info
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)