code: def _decode_histogram_from_plugin(value):
      """
      Convert from tensorflow histogram plugin representation of the data as a tensor back into
      a `aim` `Distribution`
  
      Representation of histogram given by tf summary is obtained from here:
      https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/histogram/summary_v2.py
  
      :param value: value with a tensor that contains three columns, left_edge, right_edge,
                    bin_values
      :return: aim Distribution
      """
      left_right_bins = tensor_util.make_ndarray(value.tensor)
      if left_right_bins is None:
          return None
  
      left_edge = left_right_bins[:, 0]
      right_edge = left_right_bins[:, 1]
      bin_counts = left_right_bins[:, 2]
  
      bin_range = (left_edge[0], right_edge[-1])
  
      is_empty = False
      is_empty |= left_right_bins.shape[0] == 0
      is_empty |= bin_range[0] == bin_range[1]
      if is_empty:
          return None
  
      track_val = Distribution(hist=bin_counts, bin_range=bin_range)
      return track_val
  
imports: from tensorboard.backend.event_processing.directory_watcher import DirectoryWatcher
  from tensorboard.backend.event_processing import event_file_loader
  import tensorflow
  from tensorboard.util import tensor_util
  import time
  import threading
  from pathlib import Path
  import logging
  import os
  import weakref
  import queue
  from typing import Any
  from aim import Audio, Image, Distribution
label_desc: Use image node_id 2 for calling a global function with example usage: _decode_histogram_from_plugin(value) and returns: track_val, None, None