code: def test_concat_decimal_dataframe(ltype, rtype):
      gdf1 = gd.DataFrame(
          {
              "id": np.random.randint(0, 10, 3),
              "val": ["22.3", "59.5", "81.1"],
          }
      )
      gdf2 = gd.DataFrame(
          {
              "id": np.random.randint(0, 10, 3),
              "val": ["2.35", "5.59", "8.14"],
          }
      )
  
      gdf1["val"] = gdf1["val"].astype(ltype)
      gdf2["val"] = gdf2["val"].astype(rtype)
  
      pdf1 = gdf1.to_pandas()
      pdf2 = gdf2.to_pandas()
  
      got = gd.concat([gdf1, gdf2])
      expected = pd.concat([pdf1, pdf2])
  
      assert_eq(expected, got, 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 38 for calling a global function with example usage: test_concat_decimal_dataframe(ltype, rtype) without return types