class_docstr: This class is used for concept embedding (knowledge graph types (ontology classes, wiki categories)
class_docstr_tok: ["This","class","is","used","for","concept","embedding","(","knowledge","graph","types","(","ontology","classes",",","wiki","categories",")"]
code: def concepts_vector(self, concepts):
      v_concepts = [
          self._model.docvecs[c] for c in self.check_concepts(concepts)
      ]
      return (
          matutils.unitvec(array(v_concepts).mean(axis=0))
          if v_concepts
          else None
      )
  
imports: from numpy import array
  from gensim import matutils
label_desc: Use image node_id 9 for calling the ConceptRelatedness obj's underlying member method code with example usage: obj.concepts_vector(concepts) and returns: unknown