code: def __init__(self, experiment):
      get_logger()
      np.random.seed(experiment.seed)
      from pyod.models.knn import KNN
  
      args = {
          "n_jobs": experiment.n_jobs_param,
      }
      tune_args = {}
      tune_grid = {}
      tune_distributions = {}
  
      super().__init__(
          id="knn",
          name="K-Nearest Neighbors Detector",
          class_def=KNN,
          args=args,
          tune_grid=tune_grid,
          tune_distribution=tune_distributions,
          tune_args=tune_args,
      )
  
imports: from typing import Any, Dict, Optional
  import numpy
  import pycaret.containers.base_container
  import pycaret.internal.cuml_wrappers
  from pycaret.containers.models.base_model import ModelContainer
  from pycaret.internal.distributions import Distribution
  from pycaret.utils.generic import get_logger, param_grid_to_lists
label_desc: Use image node_id 1 to create a new KNNAnomalyContainer object from inherited base classes: AnomalyContainer with example: obj = KNNAnomalyContainer(experiment)