code: def test_fetch_german():
      """Tests German Credit dataset shapes with various options."""
      german = fetch_german()
      assert len(german) == 2
      assert german.X.shape == (1000, 21)
      assert fetch_german(numeric_only=True).X.shape == (1000, 9)
  
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 12 for calling a global function with example usage: test_fetch_german() without return types