code: def train_kmeans(kmeans_model, features_batch):
      """Train a k-means clustering model using the provided features."""
      start_time = time.time()
      kmeans_model.fit(features_batch)
      time_taken = round((time.time() - start_time) // 60, 2)
      return kmeans_model, time_taken
  
imports: import sys
  import logging
  import time
  import random
  import itertools
  import pathlib
  import joblib
  import torch
  import torchaudio
  import tqdm
  import numpy
  from sklearn.cluster import MiniBatchKMeans
  from hyperpyyaml import load_hyperpyyaml
  import speechbrain
  from ljspeech_prepare import prepare_ljspeech
  from speechbrain.lobes.models.huggingface_wav2vec import HuggingFaceWav2Vec2
label_desc: Use image node_id 7 for calling a global function with example usage: train_kmeans(kmeans_model, features_batch) and returns: kmeans_model,  time_taken