code: def configure_finetune_callback(
      self,
      strategy: Union[
          str,
          BaseFinetuning,
          Tuple[str, int],
          Tuple[str, Tuple[int, int]],
      ] = "no_freeze",
      train_bn: bool = True,
  ):
      return [NoFreeze(), NoFreeze()]
  
imports: from argparse import ArgumentParser
  from typing import Any, Tuple, Union
  import pytest
  import torch
  from flash import Trainer
  from flash.core.classification import ClassificationTask
  from flash.core.utilities.imports import _TOPIC_CORE_AVAILABLE
  from pytorch_lightning.callbacks.early_stopping import EarlyStopping
  from pytorch_lightning.callbacks.finetuning import BaseFinetuning
  from pytorch_lightning.core.lightning import LightningModule
  from torch import nn
  from torch.nn import functional
  from torch.optim.optimizer import Optimizer
  from torch.utils.data import DataLoader
label_desc: Use image node_id 1 for calling the MultiFinetuneClassificationTask obj's underlying member method code with example usage: obj.configure_finetune_callback(strategy, train_bn) and returns: list