class_docstr: Takes an initial labeling and uses a mixture of Gaussians to approximate each classes
  distribution in the feature space. Each unlabeled element is then assigned a probability
  of belonging to each class based on it's fit to each classes approximated distribution.
  
  See:
      https://en.wikipedia.org/wiki/Mixture_model
docstr: Resets the parameters of the model.
code: def reset(self):
      """
      Resets the parameters of the model.
      """
      self.params, self.scratch = self.compiled_extension.init()
  
file_path: MONAI/monai/networks/layers/gmm.py
imports: from __future__ import annotations
  import torch
  from monai._extensions.loader import load_module
label_desc: Use image node_id 2 for calling the GaussianMixtureModel obj's underlying member method code with example usage: obj.reset() without return types