code: def test_within_autocast(self):
      if TEST_DEVICE == torch.device("cpu"):
          return
      AC = accuracy_calculator.AccuracyCalculator()
      embeddings = torch.randn(1000, 32)
      labels = torch.randint(0, 10, size=(1000,))
      with torch.autocast(device_type="cuda", dtype=torch.float16):
          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 1 for calling the TestWithinAutocast obj's underlying member method code with example usage: obj.test_within_autocast() without return types