code: def as_json_dict(self, forecast: Forecast) -> dict:
      result = {}
  
      if "mean" in self.output_types:
          result["mean"] = forecast.mean.tolist()
  
      if "quantiles" in self.output_types:
          quantiles = map(Quantile.parse, self.quantiles)
  
          result["quantiles"] = {
              quantile.name: forecast.quantile(quantile.value).tolist()
              for quantile in quantiles
          }
  
      if "samples" in self.output_types:
          samples = getattr(forecast, "samples", None)
          if samples is not None:
              samples = samples.tolist()
  
          result["samples"] = samples
  
          valid_length = getattr(forecast, "valid_length", None)
          if valid_length is not None:
              result["valid_length"] = valid_length.tolist()
  
      return result
  
imports: import json
  import logging
  import multiprocessing
  import os
  import signal
  import time
  import traceback
  from queue import Empty
  from typing import Callable, Iterable, List, NamedTuple, Set, Tuple
  from typing_extensions import Literal
  from flask import Flask, Response, jsonify, request
  from gluonts.dataset.common import ListDataset
  from gluonts.dataset.jsonl import encode_json
  from gluonts.model.forecast import Forecast, Quantile
  from gluonts.pydantic import BaseModel, Field
  from gluonts.shell.util import forecaster_type_by_name
label_desc: Use image node_id 1 for calling the ForecastConfig obj's underlying member method code with example usage: obj.as_json_dict(forecast) and returns: result