code: def tile(cls, op: "KMeansLloydPostprocess"):
      assert len(op.centers_old.chunks) == 1
      assert len(op.centers_new.chunks) == 1
      assert len(op.center_shift.chunks) == 1
      assert len(op.weight_in_clusters.chunks) == 1
  
      centers_old_chunk = op.centers_old.chunks[0]
      centers_new_chunk = op.centers_new.chunks[0]
      center_shift_chunk = op.center_shift.chunks[0]
      weight_in_clusters_chunk = op.weight_in_clusters.chunks[0]
      centers_new_chunk, center_shift_chunk = KMeansLloydPostprocess(
          centers_old=centers_old_chunk,
          centers_new=centers_new_chunk,
          center_shift=center_shift_chunk,
          weight_in_clusters=weight_in_clusters_chunk,
      ).new_chunks(
          [
              centers_old_chunk,
              centers_new_chunk,
              center_shift_chunk,
              weight_in_clusters_chunk,
          ],
          kws=[centers_new_chunk.params, center_shift_chunk.params],
      )
  
      centers_new_kw = op.centers_new.params
      centers_new_kw["chunks"] = [centers_new_chunk]
      centers_new_kw["nsplits"] = op.centers_new.nsplits
      center_shift_kw = op.center_shift.params
      center_shift_kw["chunks"] = [center_shift_chunk]
      center_shift_kw["nsplits"] = op.center_shift.nsplits
      new_op = op.copy()
      return new_op.new_tileables(
          op.inputs, kws=[centers_new_kw, center_shift_kw]
      )
  
imports: import numpy
  from sklearn.utils.extmath import row_norms
  from ...None import opcodes
  from ...core import OutputType, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import KeyField, BoolField, Int32Field
  from ...tensor.array_utils import as_same_device, device, sparse
  from ...tensor.core import TensorOrder
  from ...utils import has_unknown_shape
  from ..operands import LearnOperand, LearnOperandMixin
  from ._k_means_common import _execute_merge_update, _relocate_empty_clusters
  from ._k_means_fast import update_center
  from ._k_means_lloyd import update_chunk_dense, update_chunk_sparse
label_desc: Use image node_id 10 for calling the KMeansLloydPostprocess obj's underlying member method code with example usage: obj.tile(cls, op) and returns: new_op