code: def test_many_tied_distances(self):
      # This tests for the avoidance of a shape error
      emb = torch.zeros(10000, 2)
      labels = torch.randint(0, 2, size=(10000,))
      AC = accuracy_calculator.AccuracyCalculator(
          include=("precision_at_1",), k=1
      )
      accuracies = AC.get_accuracy(emb, labels)
      self.assertTrue(
          np.isclose(accuracies["precision_at_1"], 0.5, rtol=0.1)
      )
  
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 TestEmbeddingsComeFromSameSource obj's underlying member method code with example usage: obj.test_many_tied_distances() without return types