code: def __call__(self, left, right, index=None, dtypes=None):
      test_left = self._build_test_obj(left)
      test_right = self._build_test_obj(right)
      output_type = (
          self._output_types[0] if self._output_types else None
      )
  
      if output_type == OutputType.df_or_series:
          return self.new_df_or_series([left, right])
  
      # try run to infer meta
      try:
          with np.errstate(all="ignore"), quiet_stdio():
              obj = self._func(
                  test_left, test_right, *self._args, **self._kwargs
              )
      except:  # noqa: E722  # nosec  # pylint: disable=bare-except
          if output_type == OutputType.series:
              obj = pd.Series([], dtype=np.dtype(object))
          elif (
              output_type == OutputType.dataframe and dtypes is not None
          ):
              obj = build_empty_df(dtypes)
          else:
              raise TypeError(
                  "Cannot determine `output_type`, "
                  "you have to specify it as `dataframe` or `series`, "
                  "for dataframe, `dtypes` is required as well "
                  "if output_type='dataframe'"
              )
  
      if (
          getattr(obj, "ndim", 0) == 1
          or output_type == OutputType.series
      ):
          shape = self._kwargs.pop("shape", (np.nan,))
          if index is None:
              index = obj.index
          index_value = parse_index(
              index, left, right, self._func, self._args, self._kwargs
          )
          return self.new_series(
              [left, right],
              dtype=obj.dtype,
              shape=shape,
              index_value=index_value,
              name=obj.name,
          )
      else:
          dtypes = dtypes if dtypes is not None else obj.dtypes
          # dataframe
          shape = (np.nan, len(dtypes))
          columns_value = parse_index(dtypes.index, store_data=True)
          if index is None:
              index = obj.index
          index_value = parse_index(
              index, left, right, self._func, self._args, self._kwargs
          )
          return self.new_dataframe(
              [left, right],
              shape=shape,
              dtypes=dtypes,
              index_value=index_value,
              columns_value=columns_value,
          )
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import recursive_tile
  from ...core.custom_log import redirect_custom_log
  from ...serialization.serializables import KeyField, FunctionField, TupleField, DictField
  from ...utils import has_unknown_shape, enter_current_session, quiet_stdio
  from ..operands import DataFrameOperand, DataFrameOperandMixin, OutputType
  from ..utils import build_df, build_series, build_empty_df, parse_index, validate_output_types
label_desc: Use image node_id 9 for calling the DataFrameCartesianChunk obj's underlying member method code with example usage: obj.__call__(left, right, index, dtypes) and returns: self, self, self