class_docstr: A class used for accessing tfdbg v2 DebugEvent data on local filesystem.
  
  This class is a short-term hack, mirroring the EventMultiplexer for the main
  TensorBoard plugins (e.g., scalar, histogram and graphs.) As such, it only
  implements the methods relevant to the Debugger V2 pluggin.
  
  TODO(cais): Integrate it with EventMultiplexer and use the integrated class
  from MultiplexerDataProvider for a single path of accessing debugger and
  non-debugger data.
docstr: Get the information regarding a TensorFlow graph.
  
  Args:
    run: Name of the run.
    graph_id: Debugger-generated ID of the graph in question.
      This information is available in the return values
      of `GraphOpInfo`, `GraphExecution`, etc.
  
  Returns:
    A JSON-serializable object containing the information regarding
      the TensorFlow graph.
  
  Raises:
    NotFoundError if the graph_id is not known to the debugger.
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code: def GraphInfo(self, run, graph_id):
      """Get the information regarding a TensorFlow graph.
  
      Args:
        run: Name of the run.
        graph_id: Debugger-generated ID of the graph in question.
          This information is available in the return values
          of `GraphOpInfo`, `GraphExecution`, etc.
  
      Returns:
        A JSON-serializable object containing the information regarding
          the TensorFlow graph.
  
      Raises:
        NotFoundError if the graph_id is not known to the debugger.
      """
      runs = self.Runs()
      if run not in runs:
          return None
      try:
          graph = self._reader.graph_by_id(graph_id)
      except KeyError:
          raise errors.NotFoundError(
              'There is no graph with ID "%s"' % graph_id
          )
      return graph.to_json()
  
imports: import threading
  from tensorboard import errors
label_desc: Use image node_id 13 for calling the DebuggerV2EventMultiplexer obj's underlying member method code with example usage: obj.GraphInfo(run, graph_id) and returns: graph, None