code: def test_k_warning(self):
      for k in [10, 100, 2000, "max_bin_count"]:
          AC = accuracy_calculator.AccuracyCalculator(k=k)
          embeddings = torch.randn(10000, 32)
          labels = torch.randint(0, 10, size=(10000,))
          level = "WARNING" if k in [10, 100] else "INFO"
          with self.assertLogs(level=level):
              AC.get_accuracy(embeddings, labels)
  
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 TestCalculateAccuraciesValidK obj's underlying member method code with example usage: obj.test_k_warning() without return types