code: def run_clustering(data, k):
      distance = sg.create_distance("EuclideanDistance")
      distance.init(data, data)
      kmeans = sg.create_machine(
          "KMeans", k=k, distance=distance, seed=1
      )
  
      # print("Running clustering...")
      kmeans.train()
  
      return kmeans.get("cluster_centers")
  
imports: import shogun
  from numpy import *
label_desc: Use image node_id 1 for calling a global function with example usage: run_clustering(data, k) and returns: kmeans