code: def test_arrow_roundtrip(
      dtype, string_storage2, request, using_infer_string
  ):
      # roundtrip possible from arrow 1.0.0
      pa = pytest.importorskip("pyarrow")
  
      if using_infer_string and string_storage2 != "pyarrow_numpy":
          request.applymarker(
              pytest.mark.xfail(
                  reason="infer_string takes precedence over string storage"
              )
          )
  
      data = pd.array(["a", "b", None], dtype=dtype)
      df = pd.DataFrame({"a": data})
      table = pa.table(df)
      if dtype.storage == "python":
          assert table.field("a").type == "string"
      else:
          assert table.field("a").type == "large_string"
      with pd.option_context("string_storage", string_storage2):
          result = table.to_pandas()
      assert isinstance(result["a"].dtype, pd.StringDtype)
      expected = df.astype(f"string[{string_storage2}]")
      tm.assert_frame_equal(result, expected)
      # ensure the missing value is represented by NA and not np.nan or None
      assert result.loc[2, "a"] is na_val(result["a"].dtype)
  
imports: import operator
  import numpy
  import pytest
  from pandas.compat.pyarrow import pa_version_under12p0
  from pandas.core.dtypes.common import is_dtype_equal
  import pandas
  import pandas._testing
  from pandas.core.arrays.string_arrow import ArrowStringArray, ArrowStringArrayNumpySemantics
label_desc: Use image node_id 32 for calling a global function with example usage: test_arrow_roundtrip(dtype, string_storage2, request, using_infer_string) without return types