code: def evaluate_predictions(
      neighbors_true, neigbhors_computed, n_neighbors
  ):
      n_correct = 0
      n_all = neighbors_true.shape[0] * n_neighbors
      for i in range(neighbors_true.shape[0]):
          n_correct += np.sum(
              np.in1d(neighbors_true[i], neigbhors_computed[i])
          )
      return n_correct / n_all
  
imports: import os
  import io
  import re
  import pytest
  from contextlib import redirect_stdout
  import numpy
  from sklearn.neighbors import KDTree
  from sklearn.neighbors import NearestNeighbors
  from sklearn.preprocessing import normalize
  import pickle
  import joblib
  import scipy
  from pynndescent import NNDescent, PyNNDescentTransformer
label_desc: Use image node_id 26 for calling a global function with example usage: evaluate_predictions(neighbors_true, neigbhors_computed, n_neighbors) and returns: unknown