code: def _tile_one_chunk(cls, op):
      return_value, return_indices = op.return_value, op.return_indices
      out = op.outputs[0]
      chunk_op = op.copy().reset_key()
      kws = []
      if return_value:
          kws.append(
              {
                  "shape": out.shape,
                  "order": out.order,
                  "index": (0,) * out.ndim,
                  "dtype": out.dtype,
                  "type": "topk",
              }
          )
      if return_indices:
          kws.append(
              {
                  "shape": out.shape,
                  "order": TensorOrder.C_ORDER,
                  "index": (0,) * out.ndim,
                  "dtype": np.dtype(np.int64),
                  "type": "argtopk",
              }
          )
      chunks = chunk_op.new_chunks([op.input.chunks[0]], kws=kws)
      kws = [out.params for out in op.outputs]
      nsplits = tuple((s,) for s in out.shape)
      if return_value:
          kws[0]["nsplits"] = nsplits
          kws[0]["chunks"] = [chunks[0]]
      if return_indices:
          kws[-1]["nsplits"] = nsplits
          kws[-1]["chunks"] = [chunks[1]]
      new_op = op.copy()
      return new_op.new_tensors(op.inputs, kws=kws)
  
imports: import itertools
  import numpy
  from ...None import opcodes
  from ...config import options
  from ...core import ExecutableTuple, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import FieldTypes, KeyField, Int64Field, Int32Field, BoolField, StringField, ListField
  from ...utils import ceildiv, flatten
  from ..array_utils import as_same_device, device
  from ..core import TensorOrder
  from ..datasource import tensor
  from ..operands import TensorOperand, TensorOperandMixin
  from ..utils import validate_axis, validate_order
  from .sort import _validate_sort_psrs_kinds
label_desc: Use image node_id 16 for calling the TensorTopk obj's underlying member method code with example usage: obj._tile_one_chunk(cls, op) and returns: new_op