code: def test_train_model_with_bn_creator(self):
      class SimpleTorchModel(nn.Module):
          def __init__(self):
              super(SimpleTorchModel, self).__init__()
              self.dense1 = nn.Linear(2, 4)
              self.bn1 = torch.nn.BatchNorm1d(4)
              self.dense2 = nn.Linear(4, 1)
  
          def forward(self, x):
              x = self.dense1(x)
              x = self.bn1(x)
              x = torch.sigmoid(self.dense2(x))
              return x
  
      self.sc.stop()
      self.sc = init_nncontext()
      torch_model = SimpleTorchModel()
      loss_fn = torch.nn.BCELoss()
      az_model = TorchModel.from_pytorch(torch_model)
      zoo_loss = TorchLoss.from_pytorch(loss_fn)
  
      def train_dataloader():
          inputs = torch.Tensor(
              [[1, 2], [1, 3], [3, 2], [5, 6], [8, 9], [1, 9]]
          )
          targets = torch.Tensor([[0], [0], [0], [1], [1], [1]])
          return DataLoader(
              TensorDataset(inputs, targets), batch_size=2
          )
  
      train_featureset = FeatureSet.pytorch_dataloader(train_dataloader)
      val_featureset = FeatureSet.pytorch_dataloader(train_dataloader)
      zooOptimizer = Adam()
      estimator = Estimator(az_model, optim_methods=zooOptimizer)
      estimator.train_minibatch(
          train_featureset,
          zoo_loss,
          end_trigger=MaxEpoch(4),
          checkpoint_trigger=EveryEpoch(),
          validation_set=val_featureset,
          validation_method=[Accuracy()],
      )
  
      trained_model = az_model.to_pytorch()
  
file_path: BigDL/python/orca/test/bigdl/orca/torch/test_torch_estimator.py
imports: import torch
  from torch import nn
  import pytest
  from unittest import TestCase
  from bigdl.orca.torch import TorchModel, TorchLoss
  from bigdl.dllib.nncontext import *
  from torch.utils.data import TensorDataset, DataLoader
  from bigdl.dllib.estimator import *
  from bigdl.dllib.keras.optimizers import Adam
  from bigdl.dllib.optim.optimizer import MaxEpoch, EveryEpoch
  from bigdl.dllib.keras.metrics import Accuracy
  from bigdl.dllib.feature.common import FeatureSet
label_desc: Use image node_id 3 for calling the TestPytorch obj's underlying member method code with example usage: obj.test_train_model_with_bn_creator() and returns: DataLoader, x