code: def test_order_does_not_matter_with_date_transformer():
      (
          train_y_dates,
          test_y_dates,
          train_X_dates,
          test_X_dates,
      ) = train_test_split(y_dates, X_dates, test_size=15)
  
      pipeline_a = Pipeline(
          [
              ("fourier", FourierFeaturizer(m=3, prefix="FOURIER")),
              (
                  "dates",
                  DateFeaturizer(column_name="date", prefix="DATE"),
              ),
              (
                  "arima",
                  AutoARIMA(
                      seasonal=False,
                      stepwise=True,
                      suppress_warnings=True,
                      maxiter=3,
                      error_action="ignore",
                  ),
              ),
          ]
      ).fit(train_y_dates, train_X_dates)
      Xt_a = pipeline_a.transform(X=test_X_dates)
      pred_a = pipeline_a.predict(X=test_X_dates)
  
      pipeline_b = Pipeline(
          [
              (
                  "dates",
                  DateFeaturizer(column_name="date", prefix="DATE"),
              ),
              ("fourier", FourierFeaturizer(m=3, prefix="FOURIER")),
              (
                  "arima",
                  AutoARIMA(
                      seasonal=False,
                      stepwise=True,
                      suppress_warnings=True,
                      maxiter=3,
                      error_action="ignore",
                  ),
              ),
          ]
      ).fit(train_y_dates, train_X_dates)
      Xt_b = pipeline_b.transform(X=test_X_dates)
      pred_b = pipeline_b.predict(X=test_X_dates)
  
      # dates in A should differ from those in B
      assert pipeline_a.x_feats_[0].startswith("FOURIER")
      assert pipeline_a.x_feats_[-1].startswith("DATE")
  
      assert pipeline_b.x_feats_[0].startswith("DATE")
      assert pipeline_b.x_feats_[-1].startswith("FOURIER")
  
      # columns should be identical once ordered appropriately
      assert Xt_a.equals(Xt_b[pipeline_a.x_feats_])
  
      # forecasts should be identical
      assert_array_almost_equal(pred_a, pred_b, decimal=3)
  
imports: from pmdarima.compat.pytest import pytest_error_str
  from pmdarima.model_selection import train_test_split
  from pmdarima.pipeline import Pipeline, _warn_for_deprecated
  from pmdarima.preprocessing import BoxCoxEndogTransformer, FourierFeaturizer, DateFeaturizer, LogEndogTransformer
  from pmdarima.arima import ARIMA, AutoARIMA
  from pmdarima.datasets import load_wineind
  from pmdarima.datasets._base import load_date_example
  import numpy
  from numpy.testing import assert_array_almost_equal
  import pytest
label_desc: Use image node_id 5 for calling a global function with example usage: test_order_does_not_matter_with_date_transformer() without return types