code: def train_env(listify_dataset) -> ContextManager[TrainEnv]:
      hyperparameters = {
          "context_length": context_length,
          "prediction_length": prediction_length,
          "num_samples": num_samples,
          "listify_dataset": listify_dataset,
          "num_workers": 3,
          "num_prefetch": 4,
          "shuffle_buffer_length": 256,
          "epochs": 3,
          "quantiles": [0.1, 0.25, 0.5, 0.75, 0.9],
          "test_quantiles": [0.25, 0.75],
      }
      with testutil.temporary_train_env(
          hyperparameters, "constant"
      ) as env:
          yield env
  
imports: import json
  import logging
  import sys
  from typing import ContextManager
  import numpy
  import pytest
  from gluonts.core.component import equals
  from gluonts.dataset.jsonl import encode_json
  from gluonts.model.trivial.mean import MeanPredictor
  from gluonts.shell.env import ServeEnv, TrainEnv
  from gluonts.shell.train import run_train_and_test
label_desc: Use image node_id 1 for calling a global function with example usage: train_env(listify_dataset) without return types