code: def test_quantile_levels():
      from gluonts.dataset.common import ListDataset
      from gluonts.mx.model.tft import (
          TemporalFusionTransformerEstimator,
      )
      from gluonts.mx.trainer import Trainer
  
      dataset = ListDataset(
          [{"start": "2020-01-01", "target": [10.0] * 50}], freq="D"
      )
  
      estimator = TemporalFusionTransformerEstimator(
          freq="D", prediction_length=2, trainer=Trainer(epochs=1)
      )
      predictor = estimator.train(training_data=dataset)
  
      forecast = next(iter(predictor.predict(dataset)))
  
      assert isinstance(forecast, QuantileForecast)
      assert isinstance(predictor, GluonPredictor)
      assert isinstance(
          predictor.prediction_net,
          TemporalFusionTransformerPredictionNetwork,
      )
      assert all(
          float(k) == q
          for k, q in zip(
              forecast.forecast_keys,
              predictor.prediction_net.output.quantiles,
          )
      )
  
file_path: gluonts/test/mx/model/tft/test_model.py
imports: import pytest
  from gluonts.model.forecast import QuantileForecast
  from gluonts.mx.model.predictor import GluonPredictor
  from gluonts.mx import TemporalFusionTransformerEstimator
  from gluonts.mx.model.tft._network import TemporalFusionTransformerPredictionNetwork
label_desc: Use image node_id 4 for calling a global function with example usage: test_quantile_levels() without return types