code: def test_concat_dataframe_with_multiindex(df1, df2):
      gdf1 = df1
      gdf1 = gdf1.set_index(["k1", "k2"])
  
      gdf2 = df2
      gdf2 = gdf2.set_index(["k1", "k2"])
  
      pdf1 = gdf1.to_pandas()
      pdf2 = gdf2.to_pandas()
  
      actual = gd.concat([gdf1, gdf2], axis=1)
      expected = pd.concat([pdf1, pdf2], axis=1)
  
      # Will need to sort_index before comparing as
      # ordering is not deterministic in case of pandas
      # multiIndex with concat.
      assert_eq(
          expected.sort_index(),
          actual.sort_index(),
          check_index_type=True,
      )
  
imports: from decimal import Decimal
  import numpy
  import pandas
  import pytest
  import cudf
  from cudf.api.types import is_categorical_dtype
  from cudf.core._compat import PANDAS_GE_150, PANDAS_LT_140
  from cudf.core.dtypes import Decimal32Dtype, Decimal64Dtype, Decimal128Dtype
  from cudf.testing._utils import assert_eq, assert_exceptions_equal
label_desc: Use image node_id 23 for calling a global function with example usage: test_concat_dataframe_with_multiindex(df1, df2) without return types