code: def to_dict(self, model_run):
          
          # Get the basic Json object from the super class
          json_obj = super(DefaultModelRunManager, self).to_dict(model_run)
          # Add run state
          json_obj['state'] = ModelRunState.to_dict(model_run.state)
          # Add run scheduling Timestamps
          json_obj['schedule'] = model_run.schedule
          # Add experiment information
          json_obj['experiment'] = model_run.experiment_id
          # Add model information
          json_obj['model'] = model_run.model_id
          # Transform dictionary of attributes into list of key-value pairs.
          json_obj['arguments'] = attribute.attributes_to_dict(model_run.arguments)
          # Include attachments
          json_obj['attachments'] = [
              attachment.to_dict()
                  for attachment in model_run.attachments.values()
              ]
          return json_obj
docs: Create a Json-like dictionary for a model run object. Extends the
          basic object with run state, arguments, and optional prediction results
          or error descriptions.
  
          Parameters
          ----------
          model_run : PredictionHandle
  
          Returns
          -------
          (JSON)
              Json-like object, i.e., dictionary.