code: def test_short_fit_length(params):
      params["model_configs"][0].fit_length = "29D"
      model = MultistageForecastEstimator(**params)
      with LogCapture(cst.LOGGER_NAME) as log_capture:
          model._initialize()
          log_capture.check_present(
              (
                  cst.LOGGER_NAME,
                  "INFO",
                  "Some `fit_length` is None or is shorter than `train_length`. "
                  "These `fit_length` have been replaced with `train_length`.",
              )
          )
  
imports: import datetime
  import numpy
  import pandas
  import pytest
  from testfixtures import LogCapture
  import greykite.common.constants
  from greykite.common.testing_utils import generate_df_for_tests
  from greykite.sklearn.estimator.lag_based_estimator import LagBasedEstimator
  from greykite.sklearn.estimator.multistage_forecast_estimator import MultistageForecastEstimator
  from greykite.sklearn.estimator.multistage_forecast_estimator import MultistageForecastModelConfig
  from greykite.sklearn.estimator.simple_silverkite_estimator import SimpleSilverkiteEstimator
  from greykite.sklearn.uncertainty.uncertainty_methods import UncertaintyMethodEnum
label_desc: Use image node_id 23 for calling a global function with example usage: test_short_fit_length(params) without return types