text: import rdflib
  import sys
  import numpy as np
  
  from owl2vec_star.rdf2vec.embed import RDF2VecTransformer
  from owl2vec_star.rdf2vec.graph import KnowledgeGraph, Vertex
  from owl2vec_star.rdf2vec.walkers.random import RandomWalker
  from owl2vec_star.rdf2vec.walkers.weisfeiler_lehman import WeisfeilerLehmanWalker
  
  
  def construct_kg_walker(onto_file, walker_type, walk_depth):
      g = rdflib.Graph()
      if onto_file.endswith('ttl') or onto_file.endswith('TTL'):
          g.parse(onto_file, format='turtle')
      else:
          g.parse(onto_file)
      kg = KnowledgeGraph()
      for (s, p, o) in g:
          s_v, o_v = Vertex(str(s)), Vertex(str(o))
          p_v = Vertex(str(p), predicate=True, _from=s_v, _to=o_v)
          kg.add_vertex(s_v)
          kg.add_vertex(p_v)
          kg.add_vertex(o_v)
          kg.add_edge(s_v, p_v)
          kg.add_edge(p_v, o_v)
  
      if walker_type.lower() == 'random':
          walker = RandomWalker(depth=walk_depth, walks_per_graph=float('inf'))
      elif walker_type.lower() == 'wl':
          walker = WeisfeilerLehmanWalker(depth=walk_depth, walks_per_graph=float('inf'))
      else:
          print('walker %s not implemented' % walker_type)
          sys.exit()
  
      return kg, walker
  
  
  def get_rdf2vec_embed(onto_file, walker_type, walk_depth, embed_size, classes):
      kg, walker = construct_kg_walker(onto_file=onto_file, walker_type=walker_type, walk_depth=walk_depth)
      transformer = RDF2VecTransformer(walkers=[walker], vector_size=embed_size)
      instances = [rdflib.URIRef(c) for c in classes]
      walk_embeddings = transformer.fit_transform(graph=kg, instances=instances)
      return np.array(walk_embeddings)
  
  
  def get_rdf2vec_walks(onto_file, walker_type, walk_depth, classes):
      kg, walker = construct_kg_walker(onto_file=onto_file, walker_type=walker_type, walk_depth=walk_depth)
      instances = [rdflib.URIRef(c) for c in classes]
      walks_ = list(walker.extract(graph=kg, instances=instances))
      return walks_
  