class_docstr: TensorBoardX Logger.
  
  Note that hparams will be written only after a trial has terminated.
  This logger automatically flattens nested dicts to show on TensorBoard:
  
      {"a": {"b": 1, "c": 2}} -> {"a/b": 1, "a/c": 2}
code: def log_trial_start(self, trial: "Trial"):
      if trial in self._trial_writer:
          self._trial_writer[trial].close()
      trial.init_local_path()
      self._trial_writer[trial] = self._summary_writer_cls(
          trial.local_path, flush_secs=30
      )
      self._trial_result[trial] = {}
  
imports: import logging
  import numpy
  from typing import TYPE_CHECKING, Dict
  from ray.air.constants import TRAINING_ITERATION
  from ray.tune.logger.logger import _LOGGER_DEPRECATION_WARNING, Logger, LoggerCallback
  from ray.util.debug import log_once
  from ray.tune.result import TIME_TOTAL_S, TIMESTEPS_TOTAL
  from ray.tune.utils import flatten_dict
  from ray.util.annotations import Deprecated, PublicAPI
label_desc: Use image node_id 2 for calling the TBXLoggerCallback obj's underlying member method code with example usage: obj.log_trial_start(trial) without return types