docstr: Log useful information to TensorBoard. Users are expected to
  write their customized `log_metrics` method to log information
  such as loss values, metric scores, etc.
  
  Args:
      batch (Batch): Batch tuple from the dataloader.
      output: Output generated by the model.
      loss (Tensor): Generated class
      step_type (str): Type of step. Choices are "train", "val", and "test".
code: def log_metrics(self, batch: Batch, output, loss, step_type):
      """Log useful information to TensorBoard. Users are expected to
      write their customized `log_metrics` method to log information
      such as loss values, metric scores, etc.
  
      Args:
          batch (Batch): Batch tuple from the dataloader.
          output: Output generated by the model.
          loss (Tensor): Generated class
          step_type (str): Type of step. Choices are "train", "val", and "test".
      """
      pass
  
file_path: audio/examples/self_supervised_learning/lightning_modules.py
imports: from collections import namedtuple
  from typing import Callable, Optional
  import lightning.pytorch
  import torch
  import torch.nn
  from torch.optim.optimizer import Optimizer
label_desc: Use image node_id 2 for calling the SSLPretrainModule obj's underlying member method code with example usage: obj.log_metrics(batch, output, loss, step_type) without return types