code: def __init__(self, checkpoint_path):
      super().__init__()
      self.register_buffer(
          "_float_tensor", torch.tensor([0], dtype=torch.float)
      )
      self.kmeans_model = self.load_kmeans_model(checkpoint_path)
  
file_path: textlesslib/textless/data/kmeans_quantizer.py
imports: import torch
  import joblib
  import warnings
label_desc: Use image node_id 1 to create a new KMeansQuantizer object from inherited base classes: torch.nn with example: obj = KMeansQuantizer(checkpoint_path)