code: def test_legal_data_format(self):
      # we can now easily support this test!
      dataset = ChainTensorDataset(input1, input2, label1)
      dataloader = DataLoader(dataset, batch_size=5)
      trainer = Trainer()
      model = ModelWithMultipleInputs()
  
      trainer.quantize(
          model,
          calib_data=dataloader,
          metric=torchmetrics.F1Score("multiclass", num_classes=10),
      )
  
imports: from unittest import TestCase
  import operator
  import pytest
  import torch
  from torch.utils.data import TensorDataset, DataLoader, Dataset
  from torch import nn
  import torchmetrics
  from bigdl.nano.pytorch import Trainer
  from bigdl.nano.utils.common import compare_version
label_desc: Use image node_id 2 for calling the TestDataloader obj's underlying member method code with example usage: obj.test_legal_data_format() without return types