code: def test_no_preprocessing(self):
      train_set = PyODDataset(X=self.X_train)
      train_loader = torch.utils.data.DataLoader(
          train_set, batch_size=self.batch_size, shuffle=True
      )
  
      for data, data_idx in train_loader:
          assert data.shape[0] == self.batch_size
          assert data.shape[1] == self.n_features
  
imports: from __future__ import division
  from __future__ import print_function
  import os
  import sys
  import unittest
  import numpy
  import torch
  from numpy.testing import assert_almost_equal
  from numpy.testing import assert_equal
  from numpy.testing import assert_raises
  from sklearn.metrics import roc_auc_score
  from pyod.models.auto_encoder_torch import AutoEncoder
  from pyod.utils.data import generate_data
  from pyod.models.auto_encoder_torch import PyODDataset
label_desc: Use image node_id 2 for calling the TestPyODDataset obj's underlying member method code with example usage: obj.test_no_preprocessing() without return types