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.
code: def _opCreationDigestToDataObject(self, op_creation_digest, graph):
      if op_creation_digest is None:
          return None
      json_object = op_creation_digest.to_json()
      del json_object["graph_id"]
      json_object["graph_ids"] = self._getGraphStackIds(
          op_creation_digest.graph_id
      )
      # TODO(cais): "num_outputs" should be populated in to_json() instead.
      json_object["num_outputs"] = op_creation_digest.num_outputs
      del json_object["input_names"]
  
      json_object["inputs"] = []
      for input_tensor_name in op_creation_digest.input_names or []:
          input_op_name, output_slot = parse_tensor_name(
              input_tensor_name
          )
          json_object["inputs"].append(
              {"op_name": input_op_name, "output_slot": output_slot}
          )
      json_object["consumers"] = []
      for _ in range(json_object["num_outputs"]):
          json_object["consumers"].append([])
      for (
          src_slot,
          consumer_op_name,
          dst_slot,
      ) in graph.get_op_consumers(json_object["op_name"]):
          json_object["consumers"][src_slot].append(
              {"op_name": consumer_op_name, "input_slot": dst_slot}
          )
      return json_object
  
imports: import threading
  from tensorboard import errors
label_desc: Use image node_id 15 for calling the DebuggerV2EventMultiplexer obj's underlying member method code with example usage: obj._opCreationDigestToDataObject(op_creation_digest, graph) and returns: json_object, None