code: def test_quantile_loss():
      for label in TIME_SERIES:
          for forecast in TIME_SERIES:
              q = 0.9
              data = {"label": label, str(q): forecast}
              actual = quantile_loss(data, q=q)
              expected = 2 * np.abs(
                  (label - forecast) * ((forecast >= label) - q)
              )
  
              np.testing.assert_almost_equal(actual, expected)
  
file_path: gluonts/test/ev/test_stats.py
imports: import numpy
  from gluonts.ev.stats import absolute_error, absolute_label, absolute_percentage_error, coverage, error, quantile_loss, squared_error, symmetric_absolute_percentage_error, scaled_interval_score, absolute_scaled_error, scaled_quantile_loss
  from gluonts.ev.ts_stats import seasonal_error
label_desc: Use image node_id 5 for calling a global function with example usage: test_quantile_loss() without return types