code: def configure_logger(
      self, logger: Union[bool, Logger, Iterable[Logger]]
  ) -> None:
      if not logger:
          # logger is None or logger is False
          self.trainer.loggers = []
      elif logger is True:
          # default logger
          if _TENSORBOARD_AVAILABLE or _TENSORBOARDX_AVAILABLE:
              logger_ = TensorBoardLogger(
                  save_dir=self.trainer.default_root_dir,
                  version=SLURMEnvironment.job_id(),
              )
          else:
              warning_cache.warn(
                  "Starting from v1.9.0, `tensorboardX` has been removed as a dependency of the `lightning.pytorch`"
                  " package, due to potential conflicts with other packages in the ML ecosystem. For this reason,"
                  " `logger=True` will use `CSVLogger` as the default logger, unless the `tensorboard`"
                  " or `tensorboardX` packages are found."
                  " Please `pip install lightning[extra]` or one of them to enable TensorBoard support by default"
              )
              logger_ = CSVLogger(save_dir=self.trainer.default_root_dir)  # type: ignore[assignment]
          self.trainer.loggers = [logger_]
      elif isinstance(logger, Iterable):
          self.trainer.loggers = list(logger)
      else:
          self.trainer.loggers = [logger]
  
imports: from typing import Any, Iterable, Optional, Union
  from lightning_utilities.core.apply_func import apply_to_collection
  from torch import Tensor
  import lightning.pytorch
  from lightning.fabric.loggers.tensorboard import _TENSORBOARD_AVAILABLE, _TENSORBOARDX_AVAILABLE
  from lightning.fabric.plugins.environments import SLURMEnvironment
  from lightning.fabric.utilities import move_data_to_device
  from lightning.fabric.utilities.apply_func import convert_tensors_to_scalars
  from lightning.pytorch.loggers import CSVLogger, Logger, TensorBoardLogger
  from lightning.pytorch.trainer.connectors.logger_connector.result import _METRICS, _OUT_DICT, _PBAR_DICT
  from lightning.pytorch.utilities.rank_zero import WarningCache
label_desc: Use image node_id 4 for calling the _LoggerConnector obj's underlying member method code with example usage: obj.configure_logger(logger) without return types