class_docstr: TensorBoard-internal utility for warning when data is too new.
  
  Specify a maximum known `version` number as stored in summary
  metadata, and automatically reject and warn on data from newer
  versions. This keeps a (single) bit of internal state to handle
  logging a warning to the user at most once.
  
  This should only be used by plugins bundled with TensorBoard, since
  it may instruct users to upgrade their copy of TensorBoard.
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docstr: Initialize a `_MetadataVersionChecker`.
  
  Args:
    data_kind: A human-readable description of the kind of data
      being read, like "scalar" or "histogram" or "PR curve".
    latest_known_version: Highest tolerated value of `version`,
      like `0`.
docstr_tok: ["Initialize","a","`","_MetadataVersionChecker","`",".","Args",":","data_kind",":","A","human-readable","description","of","the","kind","of","data","being","read",",","like","``","scalar","''","or","``","histogram","''","or","``","PR","curve","''",".","latest_known_version",":","Highest","tolerated","value","of","`","version","`",",","like","`","0","`","."]
code: def __init__(self, data_kind, latest_known_version):
      """Initialize a `_MetadataVersionChecker`.
  
      Args:
        data_kind: A human-readable description of the kind of data
          being read, like "scalar" or "histogram" or "PR curve".
        latest_known_version: Highest tolerated value of `version`,
          like `0`.
      """
      self._data_kind = data_kind
      self._latest_known_version = latest_known_version
      self._warned = False
  
imports: import threading
  from bleach.sanitizer import Cleaner
  import markdown
  from tensorboard import context
  from tensorboard.backend import experiment_id
  from tensorboard.util import tb_logging
label_desc: Use image node_id 1 to create a new _MetadataVersionChecker object  with example: obj = _MetadataVersionChecker(data_kind, latest_known_version)