docstr: Called at the end of a training batch in `fit` methods.
  Subclasses should override for any actions to run.
  :param batch: Integer, index of batch within the current epoch.
  :param logs: Dict. Aggregated metric results up until this batch.
docstr_tok: ["Called","at","the","end","of","a","training","batch","in","`","fit","`","methods",".","Subclasses","should","override","for","any","actions","to","run",".",":","param","batch",":","Integer",",","index","of","batch","within","the","current","epoch",".",":","param","logs",":","Dict",".","Aggregated","metric","results","up","until","this","batch","."]
code: def after_train_iter(self, runner):
      """
      Called at the end of a training batch in `fit` methods.
      Subclasses should override for any actions to run.
      :param batch: Integer, index of batch within the current epoch.
      :param logs: Dict. Aggregated metric results up until this batch.
      """
      if self.freq != "epoch" and self._is_rank_zero(runner):
          if (
              self.freq == "batch"
              or runner.batch_idx % int(self.freq) == 0
          ):
              writer = SummaryWriter(
                  log_dir=self.tmp_dir, **self.kwargs
              )
              for name, value in runner.metrics_stats.items():
                  if name not in self.unlog_items:
                      writer.add_scalar(name, value, runner.batch_idx)
              writer.close()
  
file_path: BigDL/python/orca/src/bigdl/orca/learn/pytorch/callbacks/tensorboard.py
imports: import os
  import shutil
  import tempfile
  from torch.utils.tensorboard import SummaryWriter
  from bigdl.orca.data.file import put_local_dir_tree_to_remote
  from bigdl.orca.learn.pytorch.callbacks import Callback
  from bigdl.dllib.utils.log4Error import invalidInputError
label_desc: Use image node_id 2 for calling the TensorBoardCallback obj's underlying member method code with example usage: obj.after_train_iter(runner) without return types