code: def __init__(self, experiment):
      logger = get_logger()
      np.random.seed(experiment.seed)
      gpu_imported = False
  
      id = "kmeans"
      self._set_engine_related_vars(
          id=id,
          all_allowed_engines=ALL_ALLOWED_ENGINES,
          experiment=experiment,
      )
  
      if self.engine == "sklearn":
          from sklearn.cluster import KMeans
      elif self.engine == "sklearnex":
          if _check_soft_dependencies(
              "sklearnex", extra=None, severity="warning"
          ):
              from sklearnex.cluster import KMeans
          else:
              from sklearn.cluster import KMeans
  
      if experiment.gpu_param == "force":
          from cuml.cluster import KMeans
  
          logger.info("Imported cuml.cluster.KMeans")
          gpu_imported = True
      elif experiment.gpu_param:
          if _check_soft_dependencies(
              "cuml", extra=None, severity="warning"
          ):
              from cuml.cluster import KMeans
  
              logger.info("Imported cuml.cluster.KMeans")
              gpu_imported = True
  
      args = {
          "n_clusters": _DEFAULT_N_CLUSTERS,
          "random_state": experiment.seed,
      }
      tune_args = {}
      tune_grid = {}
      tune_distributions = {}
  
      if gpu_imported:
          KMeans = get_kmeans()
  
      super().__init__(
          id=id,
          name="K-Means Clustering",
          class_def=KMeans,
          args=args,
          tune_grid=tune_grid,
          tune_distribution=tune_distributions,
          tune_args=tune_args,
          is_gpu_enabled=gpu_imported,
      )
  
imports: from typing import Any, Dict, List, Optional
  import numpy
  import pycaret.containers.base_container
  import pycaret.internal.cuml_wrappers
  from pycaret.containers.models.base_model import ModelContainer
  from pycaret.internal.cuml_wrappers import get_dbscan, get_kmeans
  from pycaret.internal.distributions import Distribution
  from pycaret.utils._dependencies import _check_soft_dependencies
  from pycaret.utils.generic import get_logger, param_grid_to_lists
label_desc: Use image node_id 1 to create a new KMeansClusterContainer object from inherited base classes: ClusterContainer with example: obj = KMeansClusterContainer(experiment)