code: def __init__(
      self, corpus, term_acceptance_re=re.compile("[a-z]{3,}")
  ):
      self.corpus_ = corpus
      self.category_embeddings_ = {}
      self.category_word2vec_model_ = {}
      self.term_acceptance_re = term_acceptance_re
  
imports: import itertools
  import re
  import warnings
  import numpy
  import pandas
  import scipy
  from sklearn.metrics.pairwise import cosine_similarity
  from scattertext.ParsedCorpus import ParsedCorpus
  from scattertext.representations.Word2VecFromParsedCorpus import Word2VecDefault
label_desc: Use image node_id 1 to create a new CategoryEmbeddingsResolver object  with example: obj = CategoryEmbeddingsResolver(corpus, term_acceptance_re)