class_docstr: Density estimation based on Gaussian Mixture Model.
  
  Args:
      n_components (int): Number of components used in the GMM.
docstr: Compute min-max normalization statistics over the feature bank.
code: def _compute_normalization_statistics(self):
      """Compute min-max normalization statistics over the feature bank."""
      training_scores = self.predict(self.memory_bank, normalize=False)
      self.normalization_statistics.update(training_scores)
      self.normalization_statistics.compute()
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Any
  import torch
  from sklearn.mixture import GaussianMixture
  from torch import Tensor, nn
  from anomalib.models.ai_vad.features import FeatureType
  from anomalib.utils.metrics.min_max import MinMax
label_desc: Use image node_id 5 for calling the GMMEstimator obj's underlying member method code with example usage: obj._compute_normalization_statistics() without return types