code: def __init__(self, problem_type, device):
      super().__init__()
      self.device = device
      self.loss_funct = (
          nn.MSELoss()
          if problem_type == REGRESSION
          else nn.CrossEntropyLoss()
      )
  
file_path: autogluon/tabular/src/autogluon/tabular/models/tab_transformer/pretexts.py
imports: from copy import deepcopy
  import numpy
  import torch
  import torch.nn
  from autogluon.core.constants import REGRESSION
label_desc: Use image node_id 1 to create a new SupervisedPretext object from inherited base classes: nn with example: obj = SupervisedPretext(problem_type, device)