code: def test_predict_in_sample_X(model, X, confints):
      model.fit(wineind, X=X)
      res = model.predict_in_sample(X, return_conf_int=confints)
      if confints:
          assert isinstance(res, tuple) and len(res) == 2
      else:
          assert isinstance(res, np.ndarray)
  
imports: import numpy
  import pandas
  from pmdarima.arima import ARIMA, auto_arima, AutoARIMA, ARMAtoMA
  from pmdarima.arima import _validation
  from pmdarima.compat.pytest import pytest_error_str
  from pmdarima.datasets import load_lynx, load_wineind, load_heartrate
  from numpy.random import RandomState
  from numpy.testing import assert_array_almost_equal, assert_almost_equal, assert_allclose
  from statsmodels import api
  from sklearn.metrics import mean_squared_error
  import datetime
  import joblib
  import os
  import pickle
  import pytest
  import tempfile
  import time
label_desc: Use image node_id 6 for calling a global function with example usage: test_predict_in_sample_X(model, X, confints) without return types