code: def test_get_topk_most_similar_users(header):
      model = SAR(**header)
      # 1, 2, and 4 used the same items, but 1 and 2 have the same ratings also
      train = pd.DataFrame(
          {
              header["col_user"]: [1, 1, 2, 2, 3, 3, 3, 3, 4, 4],
              header["col_item"]: [1, 2, 1, 2, 3, 4, 5, 6, 1, 2],
              header["col_rating"]: [
                  3.0,
                  4.0,
                  3.0,
                  4.0,
                  3.0,
                  2.0,
                  1.0,
                  5.0,
                  5.0,
                  1.0,
              ],
          }
      )
      model.fit(train)
  
      similar_users = model.get_topk_most_similar_users(user=1, top_k=1)
      expected = pd.DataFrame(dict(UserId=[2], prediction=[25.0]))
      assert_frame_equal(expected, similar_users)
  
      similar_users = model.get_topk_most_similar_users(user=2, top_k=1)
      expected = pd.DataFrame(dict(UserId=[1], prediction=[25.0]))
      assert_frame_equal(expected, similar_users)
  
      similar_users = model.get_topk_most_similar_users(user=1, top_k=2)
      expected = pd.DataFrame(
          dict(UserId=[2, 4], prediction=[25.0, 19.0])
      )
      assert_frame_equal(expected, similar_users)
  
imports: import json
  import pytest
  import itertools
  import numpy
  import pandas
  from pandas.testing import assert_frame_equal
  from recommenders.utils.constants import DEFAULT_PREDICTION_COL
  from recommenders.models.sar import SAR
label_desc: Use image node_id 13 for calling a global function with example usage: test_get_topk_most_similar_users(header) without return types