code: def load_graph_embedding(filename):
      embed = []
      with open(filename, "r") as f:
          for line in f:
              nid, vec = line.strip().split("\t")
              vec_list = list(map(float, vec.split(" ")))
              embed.append(vec_list)
  
      return np.array(embed, dtype="float32")
  
imports: import argparse
  import numpy
  from scipy.cluster.vq import vq, kmeans, whiten
  from sklearn import metrics
  import pgl
label_desc: Use image node_id 1 for calling a global function with example usage: load_graph_embedding(filename) and returns: np