code: def test_model_most_similar_cache(s2v):
      query = "beekeepers|NOUN"
      assert s2v.cache
      assert query in s2v
      indices = s2v.cache["indices"]
      # Modify cache to test that the cache is used and values aren't computed
      query_row = s2v.vectors.find(key=s2v.ensure_int_key(query))
      scores = numpy.array(
          s2v.cache["scores"], copy=True
      )  # otherwise not writable
      honey_bees_row = s2v.vectors.find(key="honey_bees|NOUN")
      beekeepers_row = s2v.vectors.find(key="Beekeepers|NOUN")
      for i in range(indices.shape[0]):
          for j in range(indices.shape[1]):
              if indices[i, j] == honey_bees_row:
                  scores[i, j] = 2.0
              elif indices[i, j] == beekeepers_row:
                  scores[i, j] = 3.0
      s2v.cache["scores"] = scores
      ((key1, score1), (key2, score2)) = s2v.most_similar([query], n=2)
      assert key1 == "honey_bees|NOUN"
      assert score1 == 2.0
      assert key2 == "Beekeepers|NOUN"
      assert score2 == 3.0
  
file_path: sense2vec/sense2vec/tests/test_model.py
imports: import pytest
  from pathlib import Path
  from sense2vec import Sense2Vec
  import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: test_model_most_similar_cache(s2v) without return types