code: def __call__(self, df_or_series, index=None, dtypes=None):
      output_type = (
          self.output_types[0]
          if self.output_types
          else get_output_types(df_or_series)[0]
      )
      shape = self._kwargs.pop("shape", None)
  
      if output_type == OutputType.df_or_series:
          return self.new_df_or_series([df_or_series])
      elif dtypes is not None:
          index = index if index is not None else pd.RangeIndex(-1)
          index_value = parse_index(
              index, df_or_series, self._func, self._args, self._kwargs
          )
          if shape is None:  # pragma: no branch
              shape = (
                  (np.nan,)
                  if output_type == OutputType.series
                  else (np.nan, len(dtypes))
              )
      else:
          # try run to infer meta
          try:
              attrs = self._infer_attrs_by_call(df_or_series)
              output_type = attrs["output_type"]
              index_value = attrs["index_value"]
              shape = attrs["shape"]
              dtypes = attrs["dtypes"]
          except:  # noqa: E722  # nosec
              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'"
              )
  
      inputs = (
          [df_or_series]
          + find_objects(self.args, ENTITY_TYPE)
          + find_objects(self.kwargs, ENTITY_TYPE)
      )
      if output_type == OutputType.series:
          return self.new_series(
              inputs,
              dtype=dtypes.iloc[0],
              shape=shape,
              index_value=index_value,
              name=dtypes.name,
          )
      else:
          # dataframe
          columns_value = parse_index(dtypes.index, store_data=True)
          return self.new_dataframe(
              inputs,
              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, get_output_types, ENTITY_TYPE, CHUNK_TYPE
  from ...core.custom_log import redirect_custom_log
  from ...serialization.serializables import KeyField, FunctionField, TupleField, DictField, BoolField, StringField, AnyField
  from ...utils import enter_current_session, has_unknown_shape, quiet_stdio, find_objects, replace_objects
  from ..operands import DataFrameOperand, DataFrameOperandMixin, OutputType
  from ..utils import build_df, build_empty_df, build_series, parse_index, validate_output_types, build_empty_series, clean_up_func, restore_func
label_desc: Use image node_id 16 for calling the DataFrameMapChunk obj's underlying member method code with example usage: obj.__call__(df_or_series, index, dtypes) and returns: self, self, self