class_docstr: A tracker for TensorBoard.
docstr: Initialize result tracking via Tensorboard.
  
  :param experiment_path:
      The experiment path. A custom path at which the tensorboard logs will be saved.
  :param experiment_name:
      The name of the experiment, will be used as a sub directory name for the logging. If no default is given,
      the current time is used. If set, experiment_path is set, this argument has no effect.
code: def __init__(
      self,
      experiment_path: Union[None, str, pathlib.Path] = None,
      experiment_name: Optional[str] = None,
  ):
      """
      Initialize result tracking via Tensorboard.
  
      :param experiment_path:
          The experiment path. A custom path at which the tensorboard logs will be saved.
      :param experiment_name:
          The name of the experiment, will be used as a sub directory name for the logging. If no default is given,
          the current time is used. If set, experiment_path is set, this argument has no effect.
      """
      import torch.utils.tensorboard
  
      if experiment_name is None:
          experiment_name = time.strftime("%Y-%m-%d-%H-%M-%S")
      experiment_path = normalize_path(
          experiment_path,
          default=PYKEEN_LOGS.joinpath("tensorboard", experiment_name),
      )
  
      # if we really need access to the path later, we can expose it as a property
      #  via self.writer.log_dir
      self.writer = torch.utils.tensorboard.SummaryWriter(
          log_dir=experiment_path
      )
  
file_path: pykeen/src/pykeen/trackers/tensorboard.py
imports: import pathlib
  import time
  from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
  from .base import ResultTracker
  from ..constants import PYKEEN_LOGS
  from ..utils import flatten_dictionary, normalize_path
label_desc: Use image node_id 1 to create a new TensorBoardResultTracker object from inherited base classes: ResultTracker with example: obj = TensorBoardResultTracker(experiment_path, experiment_name)