code: def _infer_df_func_returns(
      self, df, dtypes, dtype=None, name=None, index=None
  ):
      if isinstance(self._func, np.ufunc):
          output_type = OutputType.dataframe
          new_dtypes = None
          index_value = "inherit"
          new_elementwise = True
      else:
          if self.output_types is not None and (
              dtypes is not None or dtype is not None
          ):
              ret_dtypes = (
                  dtypes if dtypes is not None else (name, dtype)
              )
              ret_index_value = (
                  parse_index(index) if index is not None else None
              )
              self._elementwise = False
              return ret_dtypes, ret_index_value
  
          output_type = new_dtypes = index_value = None
          new_elementwise = False
  
      try:
          empty_df = build_df(df, size=2)
          with np.errstate(all="ignore"), quiet_stdio():
              infer_df = empty_df.apply(
                  self._func,
                  axis=self._axis,
                  raw=self._raw,
                  result_type=self._result_type,
                  args=self.args,
                  **self.kwds,
              )
          if index_value is None:
              if infer_df.index is empty_df.index:
                  index_value = "inherit"
              else:
                  index_value = parse_index(pd.RangeIndex(-1))
  
          if isinstance(infer_df, pd.DataFrame):
              output_type = output_type or OutputType.dataframe
              new_dtypes = new_dtypes or infer_df.dtypes
          else:
              output_type = output_type or OutputType.series
              new_dtypes = (
                  name or infer_df.name,
                  dtype or infer_df.dtype,
              )
          new_elementwise = (
              False if new_elementwise is None else new_elementwise
          )
      except:  # noqa: E722  # nosec
          pass
  
      self.output_types = (
          [output_type] if not self.output_types else self.output_types
      )
      dtypes = new_dtypes if dtypes is None else dtypes
      index_value = index_value if index is None else parse_index(index)
      self._elementwise = (
          new_elementwise
          if self._elementwise is None
          else self._elementwise
      )
      return dtypes, index_value
  
imports: import inspect
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...core import OutputType, recursive_tile
  from ...core.custom_log import redirect_custom_log
  from ...core.operand import OperatorLogicKeyGeneratorMixin
  from ...serialization.serializables import StringField, AnyField, BoolField, TupleField, DictField, FunctionField
  from ...utils import enter_current_session, quiet_stdio, get_func_token, tokenize
  from ..arrays import ArrowArray
  from ..operands import DataFrameOperandMixin, DataFrameOperand
  from ..utils import build_df, build_series, parse_index, validate_axis, validate_output_types, make_dtypes, make_dtype, build_empty_df, build_empty_series, clean_up_func, restore_func
label_desc: Use image node_id 22 for calling the ApplyOperand obj's underlying member method code with example usage: obj._infer_df_func_returns(df, dtypes, dtype, name, index) and returns: dtypes,  index_value, ret_dtypes,  ret_index_value