code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self.csv_name = join(rootdir, "data", "example.csv")
      self.test_len = 2048
      data = csv_to_time_series(
          self.csv_name, timestamp_unit="ms", data_cols=["kpi"]
      )[::10]
      self.vals_train = data[: -self.test_len]
      self.vals_test = data[-self.test_len :].univariates[data.names[0]]
  
imports: import logging
  from os.path import abspath, dirname, join
  import sys
  import unittest
  import numpy
  import pandas
  from merlion.models.ensemble.forecast import ForecasterEnsemble, ForecasterEnsembleConfig
  from merlion.models.ensemble.combine import ModelSelector, Mean
  from merlion.evaluate.forecast import ForecastMetric
  from merlion.models.automl.autoprophet import AutoProphet, AutoProphetConfig
  from merlion.models.forecast.arima import Arima, ArimaConfig
  from merlion.models.factory import ModelFactory
  from merlion.transform.base import Identity
  from merlion.transform.normalize import BoxCoxTransform
  from merlion.transform.resample import TemporalResample
  from merlion.utils.data_io import csv_to_time_series, TimeSeries
label_desc: Use image node_id 1 to create a new TestForecastEnsemble object from inherited base classes: unittest with example: obj = TestForecastEnsemble()