class_docstr: Log statistics writer implementation for Tensorboard.
  :param log_dir: log_dir for TensorBoard
  :param tensorboard_render_figure: Indicates whether to visualize the actions taken in TensorBoard.
class_docstr_tok: ["Log","statistics","writer","implementation","for","Tensorboard",".",":","param","log_dir",":","log_dir","for","TensorBoard",":","param","tensorboard_render_figure",":","Indicates","whether","to","visualize","the","actions","taken","in","TensorBoard","."]
docstr: Hooked into increment_log_step, called by the logging system immediately before the increment.
docstr_tok: ["Hooked","into","increment_log_step",",","called","by","the","logging","system","immediately","before","the","increment","."]
code: def on_log_step_increment(self):
      """Hooked into increment_log_step, called by the logging system immediately before the increment."""
      # write nan values explicitly to stop tensorboard from interpolating missing values in the graphs
      for tag in self.previous_step_tags:
          if tag not in self.this_step_tags:
              self.summary_writer.add_scalar(
                  tag, math.nan, GlobalLogState.global_step
              )
  
      # update previous tags and reset tags for next step
      self.previous_step_tags = self.this_step_tags
      self.this_step_tags = set()
  
      self.summary_writer.flush()
  
file_path: maze/maze/core/log_stats/log_stats_writer_tensorboard.py
imports: import logging
  import math
  import numbers
  from typing import Callable, Union, List, Optional
  import numpy
  from torch.utils.tensorboard import SummaryWriter
  from maze.core.annotations import override
  from maze.core.log_stats.log_stats import LogStatsWriter, LogStats, GlobalLogState
label_desc: Use image node_id 3 for calling the LogStatsWriterTensorboard obj's underlying member method code with example usage: obj.on_log_step_increment() without return types