code: def test_zip_data_container_should_merge_two_data_sources_together():
      data_inputs_3d, expected_outputs_3d = _create_data_source(
          (10, 10, 2)
      )
      data_inputs_2d, expected_outputs_2d = _create_data_source(
          (10, 10)
      )
      data_container_2d = DACT(
          data_inputs=data_inputs_2d,
          expected_outputs=expected_outputs_2d,
      )
      data_container = DACT(
          data_inputs=data_inputs_3d,
          expected_outputs=expected_outputs_3d,
      )
  
      zip_data_container = ZipDataContainer.create_from(
          data_container, data_container_2d
      )
  
      assert zip_data_container.ids == data_container.ids
      for i, di in enumerate(zip_data_container.data_inputs):
          assert np.array_equal(di[0], data_inputs_3d[i])
          assert np.array_equal(di[1], data_inputs_2d[i])
  
imports: import numpy
  from neuraxle.data_container import ZipDataContainer, DACT
label_desc: Use image node_id 1 for calling a global function with example usage: test_zip_data_container_should_merge_two_data_sources_together() without return types