code: def save_embeddings(self, filename):
      fout = open(filename, "w")
      node_num = len(self.vectors.keys())
      fout.write("{} {}\n".format(node_num, self._d))
      for node, vec in self.vectors.items():
          fout.write(
              "{} {}\n".format(node, " ".join([str(x) for x in vec]))
          )
      fout.close()
  
file_path: OpenNE/src/openne/lle.py
imports: from time import time
  import networkx
  import numpy
  import scipy.io
  import scipy.sparse
  import scipy.sparse.linalg
  from .None import graph
  from sklearn.preprocessing import normalize
label_desc: Use image node_id 4 for calling the LLE obj's underlying member method code with example usage: obj.save_embeddings(filename) without return types