code: def _execute_combine(cls, ctx, op: "KMeansScalablePlusPlusInit"):
      out = op.outputs[0]
      all_distances, all_min_distance_ids = tuple(
          zip(*(ctx[inp.key] for inp in op.inputs))
      )
      distances = np.stack(all_distances).T
      min_distance_ids = np.stack(all_min_distance_ids).T
  
      combined_min_distance_id = np.argmin(distances, axis=1)
      min_distance_ids = min_distance_ids[
          range(len(distances)), combined_min_distance_id
      ]
      count = np.bincount(min_distance_ids)
      result = np.zeros(out.shape[0], dtype=np.int64)
      result[: len(count)] = count
      ctx[out.key] = result
  
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 KMeansScalablePlusPlusInit obj's underlying member method code with example usage: obj._execute_combine(cls, ctx, op) without return types