code: def __post_init__(self):
      super(TabNetPretrainer, self).__post_init__()
      self._task = "unsupervised"
      self._default_loss = UnsupervisedLoss
      self._default_metric = "unsup_loss_numpy"
  
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 1 for calling the TabNetPretrainer obj's underlying member method code with example usage: obj.__post_init__() without return types