docstr: Converts a dictionary of metrics into a string for logging purposes.
  
  Parameters
  ----------
  metrics
      Dictionary of metrics to be converted into a string.
  
  Returns
  -------
  String representation of the metrics.
docstr_tok: ["Converts","a","dictionary","of","metrics","into","a","string","for","logging","purposes",".","Parameters","--","--","--","--","--","metrics","Dictionary","of","metrics","to","be","converted","into","a","string",".","Returns","--","--","--","-","String","representation","of","the","metrics","."]
code: def _metrics_to_str(metrics: Dict[str, float]) -> str:
      """
      Converts a dictionary of metrics into a string for logging purposes.
  
      Parameters
      ----------
      metrics
          Dictionary of metrics to be converted into a string.
  
      Returns
      -------
      String representation of the metrics.
      """
      str_losses = ""
      for key in metrics:
          str_losses += "%s: %.4f\t" % (key, metrics[key])
      return str_losses
  
imports: import torch
  import torch.nn
  import torch.optim
  from torch.utils.data import DataLoader
  from tqdm import tqdm
  from typing import List, Dict, Callable, Union, Tuple, Optional
  from alibi.models.pytorch.metrics import Metric, LossContainer
label_desc: Use image node_id 10 for calling the Model obj's underlying member method code with example usage: obj._metrics_to_str(metrics) and returns: str_losses