code: def __call__(self):
      params = []
      # labels
      params.append(
          {
              "shape": (self._x.shape[0],),
              "dtype": np.dtype(np.int32),
              "order": TensorOrder.C_ORDER,
          }
      )
      # upper bounds
      params.append(
          {
              "shape": (self._x.shape[0],),
              "dtype": self._x.dtype,
              "order": TensorOrder.C_ORDER,
          }
      )
      # lower bounds
      params.append(
          {
              "shape": (self._x.shape[0], self._n_clusters),
              "dtype": self._x.dtype,
              "order": TensorOrder.C_ORDER,
          }
      )
      return self.new_tileables(
          [self._x, self._centers, self._center_half_distances],
          kws=params,
      )
  
imports: import numpy
  from ...None import opcodes
  from ...core import OutputType, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import KeyField, Int32Field, BoolField
  from ...tensor.array_utils import as_same_device, device, cp, 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_elkan import init_bounds_dense, init_bounds_sparse, update_chunk_dense, update_chunk_sparse
  from ._k_means_fast import update_center, update_upper_lower_bounds
label_desc: Use image node_id 8 for calling the KMeansElkanInitBounds obj's underlying member method code with example usage: obj.__call__() and returns: self