class_docstr: Text logger of training information.
  
  Arguments
  ---------
  save_file : str
      The file to use for logging train information.
  precision : int
      Number of decimal places to display. Default 2, example: 1.35e-5.
  summary_fns : dict of str:function pairs
      Each summary function should take a list produced as output
      from a training/validation pass and summarize it to a single scalar.
docstr: Convert one item to string, handling floats
docstr_tok: ["Convert","one","item","to","string",",","handling","floats"]
code: def _item_to_string(self, key, value, dataset=None):
      """Convert one item to string, handling floats"""
      if isinstance(value, float) and 1.0 < value < 100.0:
          value = f"{value:.{self.precision}f}"
      elif isinstance(value, float):
          value = f"{value:.{self.precision}e}"
      if dataset is not None:
          key = f"{dataset} {key}"
      return f"{key}: {value}"
  
imports: import logging
  import torch
  import os
  from speechbrain.utils.distributed import main_process_only, if_main_process
label_desc: Use image node_id 2 for calling the FileTrainLogger obj's underlying member method code with example usage: obj._item_to_string(key, value, dataset) and returns: key, str, value