code: def test_json_bool_values():
      buffer = "[true,1]\n[false,false]\n[true,true]"
      cu_df = cudf.read_json(buffer, lines=True)
      pd_df = pd.read_json(buffer, lines=True)
  
      # types should be ['bool', 'int64']
      np.testing.assert_array_equal(pd_df.dtypes, cu_df.dtypes)
      np.testing.assert_array_equal(pd_df[0], cu_df["0"].to_numpy())
      # boolean values should be converted to 0/1
      np.testing.assert_array_equal(pd_df[1], cu_df["1"].to_numpy())
  
      cu_df = cudf.read_json(
          buffer, lines=True, dtype={"0": "bool", "1": "long"}
      )
      np.testing.assert_array_equal(pd_df.dtypes, cu_df.dtypes)
  
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 20 for calling a global function with example usage: test_json_bool_values() without return types