code: def stack_batches(
      self, list_output, list_embedded_x, list_obfuscation
  ):
      output = np.vstack(list_output)
      embedded_x = np.vstack(list_embedded_x)
      obf_vars = np.vstack(list_obfuscation)
      return output, embedded_x, obf_vars
  
imports: import torch
  import numpy
  from torch.utils.data import DataLoader
  from pytorch_tabnet import tab_network
  from pytorch_tabnet.utils import create_explain_matrix, filter_weights, SparsePredictDataset, PredictDataset, check_input, create_group_matrix
  from torch.nn.utils import clip_grad_norm_
  from pytorch_tabnet.pretraining_utils import create_dataloaders, validate_eval_set
  from pytorch_tabnet.metrics import UnsupMetricContainer, check_metrics, UnsupervisedLoss
  from pytorch_tabnet.abstract_model import TabModel
  import scipy
label_desc: Use image node_id 14 for calling the TabNetPretrainer obj's underlying member method code with example usage: obj.stack_batches(list_output, list_embedded_x, list_obfuscation) and returns: output,  embedded_x,  obf_vars