code: def execute(cls, ctx, op: "KMeansPlusPlusInit"):
      try:
          from sklearn.cluster._kmeans import _kmeans_plusplus
      except ImportError:  # pragma: no cover
          try:
              from sklearn.cluster._kmeans import _k_init
          except ImportError:
              from sklearn.cluster.k_means_ import _k_init
  
          def _kmeans_plusplus(*args, **kwargs):
              return _k_init(*args, **kwargs), None
  
      (x, x_squared_norms), device_id, _ = as_same_device(
          [ctx[inp.key] for inp in op.inputs],
          device=op.device,
          ret_extra=True,
      )
  
      with device(device_id):
          arg_spec = inspect.getfullargspec(_kmeans_plusplus)
          kw = {}
          if "sample_weight" in arg_spec.args:
              kw["sample_weight"] = np.ones(x.shape[0])
  
          ctx[op.outputs[0].key] = _kmeans_plusplus(
              x,
              op.n_clusters,
              x_squared_norms=x_squared_norms,
              random_state=op.state,
              n_local_trials=op.n_local_trials,
              **kw,
          )[0]
  
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 12 for calling the KMeansPlusPlusInit obj's underlying member method code with example usage: obj.execute(cls, ctx, op) and returns: _k_init,  None