docstr: :param keyed_vectors: KeyedVectors containing nodes and embeddings to calculate edges for
docstr_tok: [":","param","keyed_vectors",":","KeyedVectors","containing","nodes","and","embeddings","to","calculate","edges","for"]
code: def __init__(self, keyed_vectors: KeyedVectors, quiet: bool = False):
      """
      :param keyed_vectors: KeyedVectors containing nodes and embeddings to calculate edges for
      """
  
      self.kv = keyed_vectors
      self.quiet = quiet
  
imports: from abc import ABC, abstractmethod
  from functools import reduce
  from itertools import combinations_with_replacement
  import numpy
  import pkg_resources
  from gensim.models import KeyedVectors
  from tqdm import tqdm
label_desc: Use image node_id 1 to create a new EdgeEmbedder object from inherited base classes: ABC with example: obj = EdgeEmbedder(keyed_vectors, quiet)