code: def test_rolling_forecast_cv_passing(cv):
      # get all splits
      splits = list(cv.split(y))
      last_train_step = None
      for train, test in splits:
          assert test.shape[0] == cv.h
          assert test[-1] == train[-1] + cv.h
  
          if last_train_step is not None:
              assert train[-1] == last_train_step + cv.step
          last_train_step = train[-1]
  
file_path: pmdarima/pmdarima/model_selection/tests/test_split.py
imports: from pmdarima.compat.pytest import pytest_error_str
  from pmdarima.model_selection import RollingForecastCV, SlidingWindowForecastCV, check_cv, train_test_split
  from pmdarima.datasets import load_wineind
  import pytest
  import numpy
  from numpy.testing import assert_array_equal
label_desc: Use image node_id 1 for calling a global function with example usage: test_rolling_forecast_cv_passing(cv) without return types