code: def ft_ngram_hashes(word, minn, maxn, num_buckets):
      """Calculate the ngrams of the word and hash them.
  
      Parameters
      ----------
      word : str
          The word to calculate ngram hashes for.
      minn : int
          Minimum ngram length
      maxn : int
          Maximum ngram length
      num_buckets : int
          The number of buckets
  
      Returns
      -------
          A list of hashes (integers), one per each detected ngram.
  
      """
      encoded_ngrams = compute_ngrams_bytes(word, minn, maxn)
      hashes = [ft_hash_bytes(n) % num_buckets for n in encoded_ngrams]
      return hashes
  
imports: import logging
  import numpy
  from numpy import ones, vstack, float32
  import gensim.models._fasttext_bin
  from gensim.models.word2vec import Word2Vec
  from gensim.models.keyedvectors import KeyedVectors, prep_vectors
  from gensim import utils
  from gensim.utils import deprecated
  from gensim.models import keyedvectors
label_desc: Use image node_id 10 for calling a global function with example usage: ft_ngram_hashes(word, minn, maxn, num_buckets) and returns: hashes