code: def train(self, embed_size=128, window_size=5, workers=3, iter=5):
      # pd.read_pickle(self.temp_path+'walks.pkl')
      sentences = self.sentences
  
      print("Learning representation...")
      model = Word2Vec(
          sentences,
          vector_size=embed_size,
          window=window_size,
          min_count=0,
          hs=1,
          sg=1,
          workers=workers,
          epochs=iter,
      )
      print("Learning representation done!")
      self.w2v_model = model
  
      return model
  
imports: import math
  import os
  import shutil
  from collections import ChainMap, deque
  import numpy
  import pandas
  from fastdtw import fastdtw
  from gensim.models import Word2Vec
  from joblib import Parallel, delayed
  from ..alias import create_alias_table
  from ..utils import partition_dict, preprocess_nxgraph
  from ..walker import BiasedWalker
label_desc: Use image node_id 4 for calling the Struc2Vec obj's underlying member method code with example usage: obj.train(embed_size, window_size, workers, iter) and returns: model