code: def test_cache_meps(panel):
      """Tests if cached MEPS matches raw."""
      meps_raw = fetch_meps(panel, cache=False, accept_terms=True)[0]
      fetch_meps(panel, cache=True, accept_terms=True)
      meps_cached = fetch_meps(panel, cache=True)[0]
      assert_frame_equal(
          meps_raw,
          meps_cached,
          check_dtype=False,
          check_categorical=False,
      )
      assert_array_equal(meps_raw.to_numpy(), meps_cached.to_numpy())
  
imports: from functools import partial
  import numpy
  from numpy.testing import assert_array_equal
  import pandas
  from pandas.api.types import is_numeric_dtype
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.compose import make_column_transformer
  from sklearn.preprocessing import OneHotEncoder, minmax_scale
  from aif360.datasets import AdultDataset, GermanDataset, CompasDataset, LawSchoolGPADataset, MEPSDataset19, MEPSDataset20, MEPSDataset21
  from aif360.sklearn.datasets import standardize_dataset, NumericConversionWarning, fetch_adult, fetch_bank, fetch_german, fetch_compas, fetch_lawschool_gpa, fetch_meps
label_desc: Use image node_id 19 for calling a global function with example usage: test_cache_meps(panel) without return types