code: def training_step(self, batch, batch_idx):
      output, y = self.forward_pass(batch)
      # y is not None for SSL task.Rest of the tasks target is
      # fetched from the batch
      y = batch["target"] if y is None else y
      y_hat = output["logits"]
      loss = self.calculate_loss(output, y, tag="train")
      self.calculate_metrics(y, y_hat, tag="train")
      return 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 22 for calling the BaseModel obj's underlying member method code with example usage: obj.training_step(batch, batch_idx) and returns: loss