code: def __init__(
      self,
      x=None,
      n_clusters=None,
      x_squared_norms=None,
      state=None,
      init_iter=None,
      oversampling_factor=None,
      output_types=None,
      **kw,
  ):
      super().__init__(
          _x=x,
          _n_clusters=n_clusters,
          _x_squared_norms=x_squared_norms,
          _state=state,
          _init_iter=init_iter,
          _oversampling_factor=oversampling_factor,
          _output_types=output_types,
          **kw,
      )
      if self._output_types is None:
          self._output_types = [OutputType.tensor]
  
imports: import inspect
  import numpy
  from ...None import opcodes
  from ...None import tensor
  from ...core import OutputType, recursive_tile
  from ...core.operand import OperandStage
  from ...serialization.serializables import KeyField, Int32Field
  from ...tensor.array_utils import as_same_device, device
  from ...tensor.core import TensorOrder
  from ...tensor.random import RandomStateField
  from ...utils import has_unknown_shape
  from ..metrics import euclidean_distances
  from ..operands import LearnOperand, LearnOperandMixin
label_desc: Use image node_id 1 to create a new KMeansScalablePlusPlusInit object from inherited base classes: LearnOperand, LearnOperandMixin with example: obj = KMeansScalablePlusPlusInit(x, n_clusters, x_squared_norms, state, init_iter, oversampling_factor, output_types)