code: def _setup_loss(self):
      if self.custom_loss is None:
          try:
              self.loss = getattr(nn, self.hparams.loss)()
          except AttributeError as e:
              logger.error(
                  f"{self.hparams.loss} is not a valid loss defined in the torch.nn module"
              )
              raise e
      else:
          self.loss = self.custom_loss
  
imports: import importlib
  import warnings
  from abc import ABCMeta, abstractmethod
  from functools import partial
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import numpy
  import pytorch_lightning
  import torch
  import torch.nn
  import torchmetrics
  from omegaconf import DictConfig, OmegaConf
  from pandas import DataFrame
  from torch import Tensor
  from torch.optim import Optimizer
  from pytorch_tabular.models.common.heads import blocks
  from pytorch_tabular.models.common.layers import PreEncoded1dLayer
  from pytorch_tabular.utils import get_logger, reset_all_weights
label_desc: Use image node_id 8 for calling the BaseModel obj's underlying member method code with example usage: obj._setup_loss() without return types