code: def _tile_series(cls, op):
      series = op.inputs[0]
      if len(series.chunks) == 1:
          chunk = series.chunks[0]
          chunk_op = op.copy().reset_key()
          out_chunks = [
              chunk_op.new_chunk(
                  series.chunks,
                  shape=chunk.shape,
                  index=chunk.index,
                  index_value=op.outputs[0].index_value,
                  dtype=chunk.dtype,
                  name=chunk.name,
              )
          ]
          new_op = op.copy()
          kws = op.outputs[0].params.copy()
          kws["nsplits"] = series.nsplits
          kws["chunks"] = out_chunks
          return new_op.new_seriess(op.inputs, **kws)
      else:
          if op.na_position != "last":  # pragma: no cover
              raise NotImplementedError(
                  "Only support puts NaNs at the end."
              )
          # use parallel sorting by regular sampling
          return (yield from cls._tile_psrs(op, series))
  
imports: import numpy
  import pandas
  from ...None import opcodes
  from ...core import OutputType
  from ...serialization.serializables import ListField
  from ...tensor.base.sort import _validate_sort_psrs_kinds
  from ..utils import parse_index, validate_axis, build_concatenated_rows_frame
  from ..core import IndexValue
  from .core import DataFrameSortOperand
  from .psrs import DataFramePSRSOperandMixin, execute_sort_values
label_desc: Use image node_id 3 for calling the DataFrameSortValues obj's underlying member method code with example usage: obj._tile_series(cls, op) and returns: new_op, unknown