code: def test_torch_dataloader_two_inputs_with_label():
      dataset = torch.utils.data.TensorDataset(
          torch.randn(8, 3, 10, 10),
          torch.randn(8, 3, 10, 10),
          torch.randn(8, 1),
      )
  
      dataloader = torch.utils.data.DataLoader(dataset, batch_size=2)
      data_manager = DataManager.from_dataloader(dataloader)
  
      assert len(data_manager) == 4
      assert len(data_manager[0]) == 2
      assert len(data_manager[0][0]) == 2
      assert data_manager[0][0][0].shape == (2, 3, 10, 10)
      assert data_manager[0][0][1].shape == (2, 3, 10, 10)
      assert data_manager[0][1].shape == (2, 1)
  
file_path: nebuly/optimization/nebullvm/nebullvm/tools/tests/test_data.py
imports: import tensorflow
  import torch
  from nebullvm.tools.data import DataManager
label_desc: Use image node_id 3 for calling a global function with example usage: test_torch_dataloader_two_inputs_with_label() without return types