docstr: Tensorboard files should be written to the path returned to be shown properly in the UI.
  
  For example, the path should be passed to PyTorch profiler as shown below:
  
  .. code-block:: python
  
      torch.profiler.profile(
          activities=...,
          schedule=...,
          on_trace_ready=torch.profiler.tensorboard_trace_handler(<tensorboard_path>),
      )
code: def get_tensorboard_path(self) -> pathlib.Path:
      """
      Tensorboard files should be written to the path returned to be shown properly in the UI.
  
      For example, the path should be passed to PyTorch profiler as shown below:
  
      .. code-block:: python
  
          torch.profiler.profile(
              activities=...,
              schedule=...,
              on_trace_ready=torch.profiler.tensorboard_trace_handler(<tensorboard_path>),
          )
  
      """
      return self._tensorboard_path
  
imports: import abc
  import json
  import logging
  import math
  import os
  import pathlib
  import uuid
  import warnings
  from typing import TYPE_CHECKING, Any, ContextManager, Dict, Optional, Set, Sized, Type
  import torch
  import torch.distributed
  from torch import nn
  from torch.utils import data
  import determined
  from determined import common, core, pytorch
label_desc: Use image node_id 4 for calling the TorchBatchProcessorContext obj's underlying member method code with example usage: obj.get_tensorboard_path() and returns: self