code: def correct_precision_at_1(
      self, ref_includes_query, avg_of_avgs, return_per_class
  ):
      if not ref_includes_query:
          accs = [0, 0.5, 0, 1, 0]
          if not (avg_of_avgs or return_per_class):
              return 2.0 / 6
      else:
          accs = [0, 0.5, 0, 0, 0]
          if not (avg_of_avgs or return_per_class):
              return 1.0 / 6
  
      if avg_of_avgs:
          return np.mean(accs)
      if return_per_class:
          return accs
  
imports: import itertools
  import logging
  import unittest
  import numpy
  import torch
  from pytorch_metric_learning.distances import LpDistance
  from pytorch_metric_learning.utils import accuracy_calculator
  from pytorch_metric_learning.utils.common_functions import LOGGER
  from pytorch_metric_learning.utils.inference import CustomKNN, FaissKMeans, FaissKNN
  from ..None import TEST_DEVICE
label_desc: Use image node_id 2 for calling the TestCalculateAccuracies obj's underlying member method code with example usage: obj.correct_precision_at_1(ref_includes_query, avg_of_avgs, return_per_class) and returns: np, accs, unknown, unknown