code: def test_cuda_data_prefetcher(self) -> None:
      device = torch.device("cuda:0")
  
      num_samples = 12
      batch_size = 4
      dataloader = torch.utils.data.DataLoader(
          self._generate_dataset(num_samples, 2), batch_size=batch_size
      )
  
      num_prefetch_batches = 2
      data_prefetcher = CudaDataPrefetcher(
          dataloader, device, num_prefetch_batches
      )
      self.assertEqual(
          num_prefetch_batches, data_prefetcher.num_prefetch_batches
      )
  
      # make sure data_prefetcher has same number of samples as original dataloader
      num_batches_in_data_prefetcher = 0
      for inputs, targets in data_prefetcher:
          num_batches_in_data_prefetcher += 1
          # len(inputs) should equal the batch size
          self.assertEqual(len(inputs), batch_size)
          self.assertEqual(len(targets), batch_size)
          # make sure batch is on correct device
          self.assertEqual(inputs.device, device)
          self.assertEqual(targets.device, device)
  
      self.assertEqual(
          num_batches_in_data_prefetcher, num_samples / batch_size
      )
  
file_path: tnt/tests/utils/data/test_data_prefetcher.py
imports: import unittest
  from typing import Tuple
  import torch
  from torch.utils.data.dataset import Dataset, TensorDataset
  from torchtnt.utils.data.data_prefetcher import CudaDataPrefetcher
label_desc: Use image node_id 4 for calling the DataTest obj's underlying member method code with example usage: obj.test_cuda_data_prefetcher() without return types