code: def test_json_array_of_arrays(data, lines):
      data = data if lines else "[" + data.replace("\n", ",") + "]"
      pdf = pd.read_json(data, orient="values", lines=lines)
      df = cudf.read_json(
          StringIO(data),
          engine="cudf",
          orient="values",
          lines=lines,
      )
      # if mixed with dict/list type, replace other types with None.
      if 2 in pdf.columns and any(
          pdf[2].apply(
              lambda x: isinstance(x, dict) or isinstance(x, list)
          )
      ):
          pdf[2] = pdf[2].apply(
              lambda x: x
              if isinstance(x, dict) or isinstance(x, list)
              else None
          )
      # TODO: Replace string column names with integer column names
      # for values orient in cudf json reader
      pdf.rename(
          columns={name: str(name) for name in pdf.columns},
          inplace=True,
      )
      # assert_eq(pdf, df)
      pa_table_pdf = pa.Table.from_pandas(
          pdf, schema=df.to_arrow().schema, safe=False
      )
      assert df.to_arrow().equals(pa_table_pdf)
  
imports: import copy
  import gzip
  import itertools
  import os
  from io import BytesIO, StringIO
  from pathlib import Path
  import numpy
  import pandas
  import pyarrow
  import pytest
  import cudf
  from cudf.testing._utils import DATETIME_TYPES, NUMERIC_TYPES, TIMEDELTA_TYPES, assert_eq
label_desc: Use image node_id 41 for calling a global function with example usage: test_json_array_of_arrays(data, lines) without return types