code: def test_tensorflow_dataloader_three_inputs_with_label():
      dataset = tf.data.Dataset.from_tensor_slices(
          (
              tf.random.normal([8, 10, 10, 3]),
              tf.random.normal([8, 10, 10, 3]),
              tf.random.normal([8, 10, 10, 3]),
              tf.random.normal([8, 1]),
          )
      )
      data_manager = DataManager.from_dataloader(dataset.batch(2))
  
      assert len(data_manager) == 4
      assert len(data_manager[0]) == 2
      assert len(data_manager[0][0]) == 3
      assert data_manager[0][0][0].shape == (2, 10, 10, 3)
      assert data_manager[0][0][1].shape == (2, 10, 10, 3)
      assert data_manager[0][0][2].shape == (2, 10, 10, 3)
      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 8 for calling a global function with example usage: test_tensorflow_dataloader_three_inputs_with_label() without return types