code: def lloyd_iter(
      X,
      sample_weight,
      x_squared_norms,
      centers_old,
      labels,
      center_shift,
      update_centers=True,
      session=None,
      run_kwargs=None,
  ):
      update_op = KMeansLloydUpdate(
          x=X,
          sample_weight=sample_weight,
          x_squared_norms=x_squared_norms,
          centers_old=centers_old,
          labels=labels,
          update_centers=update_centers,
          n_clusters=centers_old.shape[0],
      )
      to_run = []
      ret = update_op()
      to_run.extend(ret)
      labels, centers_new, weight_in_clusters = ret
  
      if update_centers:
          centers_new, weight_in_clusters = _relocate_empty_clusters(
              X,
              sample_weight,
              centers_old,
              centers_new,
              weight_in_clusters,
              labels,
              to_run=to_run,
              session=session,
              run_kwargs=run_kwargs,
          )
          postprocess = KMeansLloydPostprocess(
              centers_old=centers_old,
              centers_new=centers_new,
              center_shift=center_shift,
              weight_in_clusters=weight_in_clusters,
          )
          centers_new, center_shift = postprocess()
  
      return centers_new, weight_in_clusters, labels, center_shift
  
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 1 for calling a global function with example usage: lloyd_iter(X, sample_weight, x_squared_norms, centers_old, labels, center_shift, update_centers, session, run_kwargs) and returns: centers_new,  weight_in_clusters,  labels,  center_shift