code: def test_torch_dataloader(self):
      import torch
  
      class ExampleTorchDataset(torch.utils.data.Dataset):
          def __init__(self, x, y):
              self.x = x
              self.y = y
  
          def __len__(self):
              return len(self.x)
  
          def __getitem__(self, idx):
              return self.x[idx], self.y[idx]
  
      torch_dataset = ExampleTorchDataset(
          np.random.random((64, 2)), np.random.random((64, 1))
      )
      torch_dataloader = torch.utils.data.DataLoader(
          torch_dataset, batch_size=8, shuffle=True
      )
      iterator = epoch_iterator.EpochIterator(torch_dataloader)
      for _, batch in iterator.enumerate_epoch(return_type="np"):
          batch = batch[0]
          self.assertEqual(batch[0].shape, (8, 2))
          self.assertEqual(batch[1].shape, (8, 1))
  
imports: import numpy
  import pytest
  import tensorflow
  from keras import backend
  from keras import testing
  from keras.trainers import data_adapters
  from keras.trainers import epoch_iterator
label_desc: Use image node_id 7 for calling the TestEpochIterator obj's underlying member method code with example usage: obj.test_torch_dataloader() and returns: len, self,  self