code: def _log_fields(self, fields: Dict, log_prefix: str = ""):
      for key, val in fields.items():
          key = log_prefix + "/" + key
          if isinstance(val, dict):
              self._log_fields(val, key)
          elif isinstance(val, torch.Tensor):
              torch.set_printoptions(threshold=2)
              logger.info(
                  "%s (Shape: %s)\n%s",
                  key,
                  " x ".join([str(x) for x in val.shape]),
                  val,
              )
              torch.set_printoptions(threshold=1000)
          elif isinstance(val, List):
              logger.info(
                  'Field : "%s" : (Length %d of type "%s")',
                  key,
                  len(val),
                  type(val[0]),
              )
          elif isinstance(val, str):
              logger.info(
                  'Field : "{}" : "{:20.20} ..."'.format(key, val)
              )
          else:
              logger.info('Field : "%s" : %s', key, val)
  
file_path: allennlp/allennlp/training/callbacks/console_logger.py
imports: import logging
  from typing import List, Dict, Any, Optional, TYPE_CHECKING
  import torch
  from allennlp.training.callbacks.callback import TrainerCallback
  from allennlp.training.util import get_train_and_validation_metrics
  from allennlp.data import TensorDict
label_desc: Use image node_id 3 for calling the ConsoleLoggerCallback obj's underlying member method code with example usage: obj._log_fields(fields, log_prefix) without return types