code: def __init__(self, km_path, device):
      import joblib
  
      self.km_model = joblib.load(km_path)
      self.C_np = self.km_model.cluster_centers_.transpose()
      self.Cnorm_np = (self.C_np**2).sum(0, keepdims=True)
  
      self.C = torch.from_numpy(self.C_np).to(device)
      self.Cnorm = torch.from_numpy(self.Cnorm_np).to(device)
  
file_path: audio/examples/hubert/utils/kmeans.py
imports: import logging
  from pathlib import Path
  from typing import Tuple
  import torch
  from sklearn.cluster import MiniBatchKMeans
  from torch import Tensor
  from .common_utils import _get_feat_lens_paths, _get_model_path
label_desc: Use image node_id 1 to create a new ApplyKmeans object  with example: obj = ApplyKmeans(km_path, device)