docstr: Tests GluonTS mixer 
docstr_tok: ["Tests","GluonTS","mixer"]
code: def test_12_gluonts(self):
      """Tests GluonTS mixer"""
      from lightwood.mixer import GluonTSMixer
  
      if GluonTSMixer is not None:
          data = pd.read_csv("tests/data/arrivals.csv")
          order_by = "T"
          train_df, test_df = self.split_arrivals(data, grouped=True)
          pdef = {
              "target": "Traffic",
              "timeseries_settings": {
                  "order_by": order_by,
                  "group_by": ["Country"],
                  "window": 4 * 5,
                  "horizon": 4 * 2,
              },
          }
          jai = json_ai_from_problem(
              train_df, ProblemDefinition.from_dict(pdef)
          )
          jai.model["args"]["submodels"] = [
              {"module": "GluonTSMixer", "args": {}}
          ]
          predictor = predictor_from_json_ai(jai)
          predictor.learn(train_df)
          predictor.predict(test_df, args={"time_format": "infer"})
          predictor.predict(
              test_df.iloc[[-1]], args={"time_format": "infer"}
          )
  
          # adjust
          adjust_n_epochs = 5
          predictor.adjust(
              test_df, adjust_args={"n_epochs": adjust_n_epochs}
          )
          predictor.predict(
              test_df.iloc[[-1]], args={"time_format": "infer"}
          )
          assert predictor.mixers[0].n_epochs == adjust_n_epochs
  
imports: import random
  from datetime import datetime
  from datetime import timedelta
  import unittest
  import numpy
  import pandas
  from typing import List
  from scipy import signal
  from sklearn.metrics import r2_score
  from lightwood.api.types import ProblemDefinition
  from tests.utils.timing import train_and_check_time_aim
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.forecasting.statsforecast import StatsForecastAutoARIMA
  from dataprep_ml.splitters import stratify
  from lightwood.api.high_level import json_ai_from_problem, code_from_json_ai, predictor_from_code, predictor_from_problem, predictor_from_json_ai
  from lightwood.mixer.sktime import SkTime
label_desc: Use image node_id 16 for calling the TestTimeseries obj's underlying member method code with example usage: obj.test_12_gluonts() without return types